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thesis entitled
Productivity analysis of microtunneling pipe installation using
simulation
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has been accepted towards fulfillment
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Date

MSU is an Affirmative Action/Equal Opportunity Institution

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PLACE IN RETURN Box to remove this checkout from your record.
To AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE
NOV 0 7 2007

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2/05 c:/ClRC/DateDue.lndd—p. 15

 

 

PRODUCTIVITY ANALYSIS OF MICROTUNNELING PIPE
INSTALLATION USING SIMULATION

By

Yu Luo

A THESIS
Submitted to
Michigan State University

In partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE

Construction Management Program

2005

ABSTRACT

PRODUCTIVITY ANALYSIS OF MICROTUNNELING PIPE INSTALLATION
USING SIMULATION

By
Yu Luo
Microtunneling is a construction method in the family of trenchless technology, which is
used to install underground utilities with minimum impacts on ground surface.
Microtunneling is a complex operation that requires the integration of several systems, a
variety of supporting equipments and experienced personnel, and is heavily influenced by
subsurface conditions. The use of this technology is increasing as the underground
infrastructures become more complicated and denser. As a result, the need to better
understand the operations involved becomes crucial to improve planning, cost estimating,
resource selection, and productivity. Simulation can be used to study microtunneling
operations before they are actually performed, thereby identifying problems at the
different stages of the project. Simulation can be used to aid in the decision-making
process to control costs and shorten project duration. The objective of this research is to
analyze and to evaluate the factors that affect the productivity in microtunneling
operations. For this purpose, an actual microtunneling project was selected. Based on the
data collected from the project, this research developed a CYCLic Operations NEtwork
(CYCLONE) model with highlight on the impact of variations in soil compositions on
the productivity of the operation. Simulations were repetitively conducted with different
soil compositions. The results were used in a regression analysis to find a function of
productivity and soil compositions. Various combinations of resource utilization were

also simulated with the model to optimize the productivity.

This Thesis Is Dedicated To My Wife Huixia For Her Love, Affection,
And Encouragement To Successfully Complete The Graduate Study,
And
To My Parents For Their Encouragement And Continued Support

Throughout My Entire Education

iii

ACKNOWLEDGEMENTS

It is my pleasure to extend my appreciation to all those who helped me to accomplish this
master thesis work. Gratitude must be personally extended to the following key

individuals.

Most importantly, I am greatly indebted to my advisor and mentor, Dr. Mohammad
Najafi, P.E., Director, Center for Underground Infrastructure Research and Education
(CUIRE), for his invaluable support, precious advice, and constant guidance as a mentor,
major professor, and thesis committee member. I would also like to thank my committee
members, Dr. Tariq Abdelhamid and Dr. Rigoberto Burguefio for their valuable

suggestions.

My sincere thanks to all the Board Members of Center for Underground Infrastructure
Research and Education (CUIRE), Michigan State University, for all the support and
help. I would like to thank Michigan Department of Transportation for funding my
research. Especially thanks to Mr. Mark Dionise, MDOT real estate division manager.
Mr. Mark Bruce, president of CanClay Corporation, and Mr. David Abbott, principal of
Jason Consultants Group, deserved of a heartfelt appreciation for providing technical

details.

Thanks to my wife, Huixia (Judy) Wang, for her patience, and emotional support. I would

like to thank all my friends for all their help, constant support, and encouragement.

iv

TABLE OF CONTENTS

 

 

 

 

LIST OF TABLES- - - - - - VII
LIST OF FIGURES - - - - -- IX
1 INTRODUCTION - -- - ...... -- - - - - - - - -- 1
1.1 OVERVIEW ........................................................................................................... l
1.2 PROBLEM AND NEED STATEMENT ........................................................................ 3
1.3 GOAL AND OBJECTIVES ....................................................................................... 4
1.4 METHODOLOGY .................................... 6
1.5 SCOPE AND LIMITATIONS OF THE THESIS ............................................................. 8
1.6 ORGANIZATION OF THE THESIS ............................................................................ 9

2 LITERATURES AND PROJECT REVIEW-- ............ - 10
2.1 MICROTUNNELING METHODS ............................................................................ 10
2.1.] Method Description .................................................................................. I 1
2.1.1.1 Slurry Microtunneling Boring Machine (MTBM) ................................ 12
2.1.1.2 J acklng System ...................................................................................... 15
2.1.1.3 Automated Spoil Transportation ........................................................... 17

2.1.1.4 Guidance and Remote Control System ................................................. 18

. 2.1.1.5 Active Direction Control ....................................................................... 22

2.2 JACKING PIPE MATERIALS USED IN MICROTUNNELING ..................................... 23

2. 2. 1 General Requirements .............................................................................. 23
2.2.2 Material Types .......................................................................................... 24
2.2.3 Material Selection ..................................................................................... 25

2.3 SOIL CONDITIONS .............................................................................................. 27
2.3.1 Soil Classifications .................................................................................... 27
2.3.2 Soil Classification Common Systems ........................................................ 28
2.3.3 The Unified Soil Classification (USC) System .......................................... 30
2.3.4 Soil Selection in the Candidate Project .................................................... 33

2.4 SIMULATION CANDIDATE PROJECT DESCRIPTION .............................................. 35
2.4.1 Project Location and Soil Profile ............................................................. 35
2.4.2 Jacking Forces .......................................................................................... 38
2.4.3 Microtunneling Pipes ................................................................................ 38
2.4.4 Microtunneling Equipment ....................................................................... 41
2.4.5 Other Equipments ..................................................................................... 43
2.4.6 Labor Crews .............................................................................................. 44

2. 4. 7 Project Site Layout .................................................................................... 45

2.5 CONSTRUCTION SIMULATION ............................................................................. 49
2.5.1 Computer Simulation Overview ................................................................ 49
2.5.2 Construction Simulation ........................................................................... 52
2.5.3 Simulation Modeling ................................................................................. 54
2.5.4 Tunneling and Microtunneling Simulation Tools and Applications ......... 5 7

2.6 SUMMARY OF LITERATURE REVIEW .................................................................. 60

3 CYCLONE METHODOLOGY AND APPLICATION 62

 

 

 

 

3.1 CYCLONE METHODOLOGY ................................................................................. 62
3.2 MICROTUNNELING OPERATION PROCEDURES .................................................... 66
3.3 FLOW UNIT AND RECOURSES IDENTIFICATION .................................................. 71
3.4 INTEGRATION OF INDEPENDENT RESOURCE CYCLES ......................................... 80
3.5 RESOURCES INITIALIZATION .................................................................... 87
3 .6 MODELING ASSUMPTIONS .................................................................................. 88
3.7 MODEL ENHANCEMENT WITH SOIL COMPOSITION CHANGES ............................ 90
4 STATISTICAL ANALYSIS OF OBSERVED DURATION DATA .................. 94
4.1 DATA COLLECTED FROM THE PROJECT .............................................................. 95
4.2 INTRODUCTION To STATISTICAL DISTRIBUTIONS IN WEBCYCLONE ............... 96
4.3 KOLMOGOROV-SMIRNOV GOODNESS-OF-FIT TEST .......................................... 103
4.4 DISTRIBUTIONS SUGGESTED FOR THE DURATION TIME RANDOM VARIABLES. 104
‘ 4.5 COMPARE THE DURATION TIME OF JACKING PIPE SECTION IN DIFFERENT SOIL
CONDITIONS ................................................................................................................. ‘ 108
5 SIMULATION RESULTS AND DISCUSSION - - - 111
5.1 SIMULATION RESULTS WITH PROTOTYPE CYCLONE MODEL ........ ’ ................ 111
5.2 VALIDATION OF THE PROTOTYPE SIMULATION MODEL ................................... 114
5.3 SIMULATION RESULTS WITH ENHANCED MODEL CONSIDERING SOIL
COMPOSITION CHANGES .............................................................................................. 115
5.4 SENSITIVITY ANALYSIS .................................................................................... 124
5.5 IMPACTS OF DIFFERENT SOIL CONDITIONS ...................................................... 127
6 SUMMARY AND CONCLUSIONS - -- - -- - -- 132
6.1 OVERALL SUMMARY ........................................................................................ 132
6.2 CONCLUSIONS BASED ON THE SIMULATION ..................................................... 133
6.3 LIMITATIONS OF THIS RESEARCH ..................................................................... 136
6.4 RECOMMENDATIONS AND AREAS OF FUTURE RESEARCH ................................ 137
APPENDICES - - - - 141
BIBLIOGRAPHY -- -- ...... - - -- - 206

 

vi

LIST OF TABLES

TABLE 2.1 -TYPICAL LENGTHS OF PIPE SECTIONS USED IN MICROTUNNELING ................ 26

TABLE 2.2 -APPLICABILITY OF SLURRY MICROTUNNELING FOR DIFFERENT SOIL

CONDITIONS ....................................................................................................... 27
TABLE 2.3 —SOIL CLASSIFICATION SYSTEMS ..................................................................... 29
TABLE 2.4 —PRINCIPAL SOIL GROUPS IN USC ................................................................... 30
TABLE 2.5—DESCRIPTIONS OF GROUP SYMBOLS IN USC ................................................... 31
TABLE 2.6 —COARSE-GRAINED SOILS ................................................................................. 32
TABLE 2.7 — SOIL CLASSIFICATIONS IN THE CANDIDATE PROJECT .................. . ................... 35
TABLE 2.8 —LIST OF MICROTUNNELING EQUIPMENT PROVIDED FOR THE PROJECT ............ 42
TABLE 3.1 —CYCLONE MODELING ELEMENTS ................................................................ 64
TABLE 3.2 —CYCLONE ELEMENTS PRECEDENCE TABLE ................................................. 65
TABLE 4.1—DISTRIBUTIONS, PARAMETERS, TEST STATISTICS, AND P-VALUES ................ 105
TABLE 4.2 —DURATION INFORMATION ............................................................................. 108

TABLE 4.3 — SAMPLE MEANS AND STANDARD DEVIATIONS OF JACKING DURATIONS IN

DIFFERENT SOILS ............................................................................................. 109
TABLE 4.4 — PAIRWISE COMPARISON RESULTS FROM TWO SAMPLE T-TEST ...................... 1 10
TABLE 4.5 - PAIRWISE COMPARISON RESULTS FROM WILCOXON RANK TEST .................. 1 10
TABLE 4.6 —JACI<ING PIPE DURATION DISTRIBUTIONS IN DIFFERENT SOILS .................... 1 10

vii

TABLE 5.1 —SIMULATED MICROTUNNELING PROCESS PRODUCTIVITY INFORMATION BY
CYCLE .............................................................................................................. 1 12

TABLE 5.2 —OVERALL SIMULATED MICROTUNNELING PROCESS PRODUCTIVITY

INFORMATION .................................................................................................. 1 12
TABLE 5.3 —ACTUAL CYCLE TIME MEASURED IN THE FIELD ........................................... 1 14

TABLE 5.4 —SIMULATED MICROTUNNELING PROCESS PRODUCTIVITY INFORMATION BY
CYCLE .............................................................................................................. 116

TABLE 5.5 —OVERALL SIMULATED MICROTUNNELING PROCESS PRODUCTIVITY

INFORMATION .................................................................................................. I 17

viii

LIST OF FIGURES

FIGURE 1.1 -CUMULATIVE MICROTUNNELING FOOTAGE IN THE USA AND CANADA AS OF

MARCH 2000 ....................................................................................................... 2
FIGURE 1.2 -FLOWCHART OF THE THESIS STUDY ................................................................. 6
FIGURE 2.1 -TYPICAL SLURRY TYPE MTBM ..................................................................... 13
FIGURE 2.2 - MTBM .......................................................................................................... 14
FIGURE 2.3 - CUTTING HEAD ............................................................................................. 14
FIGURE 2.4 - INSIDE OF MTBM ......................................................................................... 14
FIGURE 2.5 - JACKING FRAME FOR MICROTUNNELING ....................................................... 15
FIGURE 2.6 - STEEL CASING BEING JACKED ....................................................................... 16
FIGURE 2.7 - SOIL SEPARATION SYSTEM ............................................................................ 17
FIGURE 2.8 - LASER FOR GUIDANCE OF MTBM ................................................................. 19
FIGURE 2.9 - TARGET MOUNTED IN THE MTBM ............................................................... 20
FIGURE 2.10 - OPERATION BOARD OF A MTBM ................................................................ 20
FIGURE 2.1 1- COMPUTER SCREEN ...................................................................................... 21
FIGURE 2.12 - MONITOR FOR COMMUNICATION ................................................................ 22
FIGURE 2.13 - MONITOR SHOWING A VIEW INSIDE THE MTBM ........................................ 22
FIGURE 2.14 - TEST BED PLAN .......................................................................................... 36
FIGURE 2.15 — TEST BED CROSS SECTION ......................................................................... 37

ix

FIGURE 2.16 —TEST BED CONSTRUCTION .......................................................................... 37

FIGURE 2.17 — CONE-SHAPED BUILD-IN CRUSHER ............................................................. 42
FIGURE 2.18 -TYPICAL LAYOUT FOR SMALL MICROTUNNELING SYSTEM ......................... 46
FIGURE 2.19 - TYPICAL LAYOUT FOR LARGE MICROTUNNELING SYSTEM ......................... 47
FIGURE 2.20 —SITE LAYOUT OF THE CANDIDATE MICROTUNNELING PROJECT .................. 48
FIGURE 2.21 -A GLANCE AT WEBCYCLONE USER INTERFACE ........................................ 57
FIGURE 3.1 - SLURRY LINES AND HYDRAULIC HOSES ........................................................ 67

FIGURE 3.2 —INSIDE VIEW OF PVC PIPE SHOWING LINER CASING, SLURRY PIPES,

BENTONITE HOSES AND CABLES ........................................................................ 68
FIGURE 3.3 - AIR GRIPPER USED IN THE PROJECT ............................................................. 68
FIGURE 3.4 — LOWER PIPE SECTION INTO DRIVING SHAFT ................................................. 69
FIGURE 3.5 -— PVC PIPE JOINT BEING PUSHED IN ............................................................... 69
FIGURE 3.6 - MTBM AT THE RECEIVING SHAFT ................................................................. 70
FIGURE 3.7 —PIPE SECTION RESOURCE CYCLE ................................................................... 73
FIGURE 3.8 —— AIR ADAPTOR INSTALLATION ON PIPE SECTION RESOURCE CYCLE ............. 74
FIGURE 3.9 ——.IACKING SYSTEM RESOURCE CYCLE ............................................................. 75
FIGURE 3.10 -—LABOR A RESOURCE CYCLE ....................................................................... 75
FIGURE 3.11 --LABOR B RESOURCE CYCLE ........................................................................ 76
FIGURE 3.12 -—LUBRICATION RESOURCE CYCLE ................................................................ 77

FIGURE 3.13 —WATER RESOURCE CYCLE .......................................................................... 77

FIGURE 3.14 —SPOIL CYCLE ............................................................................................... 78
FIGURE 3.15 — SUPERVISOR RESOURCE CYCLE .................................................................. 79
FIGURE 3.16 —- CRANE RESOURCE CYCLE ............................................ ............................. 79
FIGURE 3.17 —COMBINATION ELEMENTS IN PROTOTYPE MODEL ....................................... 81
FIGURE 3.18 — QUEUE ELEMENTS IN PROTOTYPE MODEL .................................................. 85
FIGURE 3.19 —FUNCTION ELEMENTS IN PROTOTYPE MODEL ............................................. 86
FIGURE 3.20 — NORMAL ELEMENTS IN PROTOTYPE MODEL ............................................... 86
FIGURE 3.21 —RESOURCE INITIALIZATION ..... ‘ .................................................................... 88
FIGURE 4.1 — TIME CONSUMING OF THE WEBCYCLONE SIMULATION PROGRAM ........... 94
FIGURE 4.2 —PDFS OF EXPONENTIAL DISTRIBUTION ......................................................... 97
FIGURE 4.3 —PDFS OF TRIANGULAR DISTRIBUTION ........................................................... 98
FIGURE 4.4 —PDF OF UNIFORM DISTRIBUTION .................................................................. 99
FIGURE 4.5 -PDFS OF LOGNORMAL DISTRIBUTIONS ....................................................... 101
FIGURE 4.6 — PDFS OF BETA DISTRIBUTIONS .................................................................. 103
FIGURE 4.7 —CDF OF NORMAL 42 JACK PIPE SECTION ................................................. 106
FIGURE 4.8 —CDF OF COMBI 5 INSTALL PIPE SECTION ON GUARDRAIL ......................... 106
7 FIGURE 4.9 — CDF OF COMBI 10 BRING SECTION AND INSTALL LINER CASING ............ 107

xi

FIGURE 4.10 —CDF OF COMBI 3 DISMANTLE CABLES & HOSES/ RETRACK JACK FRAME

........................................................................................................................ 107

FIGURE 5.1 —SIMULATION CYCLE DURATIONS WITH PROTOTYPE MODEL ....................... 114
FIGURE 5.2 —TRACE CHART FOR QUEUE-11 SECTION ON STORAGE ............................... 117
FIGURE 5.3 —TRACE CHART FOR QUEUE-12 POSITION AVAILABLE ............................... 118
FIGURE 5.4 —TRACE CHART FOR QUEUE-13 LABOR A IDLE .......................................... 1 18
FIGURE 5.5 —TRACE CHART FOR QUEUE- 14 SUPERVISOR IDLE ...................................... 118
FIGURE 5.6 —TRACE CHART FOR QUEUE-15 AIR GRIPPER READY ........................ ..... 1 19
FIGURE 5.7 —TRACE CHART FOR QUEUE-16 CRANE IDLE .............................................. 119
FIGURE 5.8 —TRACE CHART FOR QUEUE-17 CONTROL CRANE ...................................... 1 19
FIGURE 5.9 —TRACE CHART FOR QUEUE-18 LABOR B IDLE ........................................... 120
FIGURE 5.10 —TRACE CHART FOR QUEUE-19 TRUCK IDLE ............................................ 120
FIGURE 5.11 —TRACE CHART FOR QUEUE-20 BACKHOE IDLE ....................................... 121
FIGURE 5.12 —TRACE CHART FOR QUEUE-22 BENTONITE READY ................................. 121
FIGURE 5.13 —TRACE CHART FOR QUEUE-23 JACKING SYSTEM IDLE ............................ 121
FIGURE 5.14 —-TRACE CHART FOR QUEUE-25 NEED AIR GRIPPER .............................. 122
FIGURE 5.15 —TRACE CHART FOR QUEUE-26 AIR GRIPPER NEED ADJUST .................... 122
FIGURE 5.16_—TRACE CHART FOR QUEUE—28 POSITION OCCUPIED ................................ 122
‘ FIGURE 5.17 —SENSITIVITY ANALYSIS RESULTS .............................................................. 125

xii

FIGURE 5.19 -—PRODUCTIVITY IN DIFFERENT SOIL COMPOSITIONS ................................... 127

FIGURE 5.20 —CONFINEMENTS ESTIMATION .................................................................... 129

FIGURE 5.21 —DATA PLOTS ON X AND Y ......................................................................... 130

xiii

1 INTRODUCTION

1.1 Overview

The development of underground infrastructure, environmental concerns and economic
trends are influencing society resulting in the advancement of technology for more
efficient and cost-effective utility installation, maintenance, repair and renewal (Allouche
et a1. 2003). Trenchless methods can be classified under two main categories which are
new pipeline construction, and pipeline renewal (Najafi, 2005). This research focuses on
microtunneling, one of the many methods and the fastest growing method in new pipeline

installation category.

Microtunneling was spawned in Japan in the early 19705 and eventually spread to Europe
before landing in the United States. Growth was slow throughout its first decade in the
US, going from about 10,000 ft pipeline installation in 1986 to about 55,000 it in 1994.
The use of microtunneling in the United States really took off in 1995 at the height of the
Greater Houston Wastewater Program. That year saw a two-fold increase in installed
footage from the year before, going from 55,000 ft in 1994 to more than 110,000 fl in
1995 (Figure 1.2). Today, more than 1 million it of pipe has been installed in the United
States by microtunneling (Rush 2004). The advantage of microtunneling is it can be
performed in a highly urban environment with a low risk of injury and less potential for

settlement and resulting damage to structures and roads.

 

Figure 1.1 Cumulative Microtunneling Footage in the USA and Canada as of March 2000 (Source:
Trenchless Technology Center, Louisiana Tech University) '

To better understand microtunneling operations, variety of research methods have been
approached. Among them, a firll-scale field test was conducted at Louisiana Tech
University in June 1992. The main purpose was to investigate the capability of a
microtunneling propulsion system called “LLB” (Laying pipes of LOW Bearing force) to

install a polyvinyl chloride (PVC) pipe in a range of soil conditions.

Highlights of the test included use of PVC pipe and microtunneling in four different types
of lab selected soil conditions. Traditionally, the types of usable pipes for microtunneling
have been limited, because the jacking force is directly exerted on the pipe itself, making
it necessary to have a sufficient strength of the pipe to resist that force. This excluded a

wide variety of pipe materials with excellent corrosion and hydraulic characteristics but

low end-bearing strength, such as polyvinyl chloride (PVC) from microtunneling
operation. Since a major portion of costs for microtunneling is the cost of thick-wall pipe
to resist axial jacking loads, utilization of less expensive pipes would make
microtunneling more cost competitive with open-trench construction (Nido et al. 1999).
The LLB system developed by Kidoh Construction Company of Osaka, Japan, is aimed
to enable microtunneling machines to install a wide variety of less expensive, thin-wall

pipes (Najafi, 1993).

The field test included construction of the test bed with four types of soils, construction
of drive and receive shafts, conducting testing operation and evaluation of results. The
field test was focused on jacking force acting on the pipe and longitudinal and
circumferential deflection of the pipe after installation. However, procedures of the
microtunneling operation and associated data as activity cycle times, production rates,
joint installation method, and soil friction factors were reported, which provided an
opportunity for a thorough study on the productivity of microtunneling operation with

PVC pipe and in variety of soil conditions.

1.2 Problem and Need Statement

Microtunneling is a complex operation that requires the integration of several systems, a
variety of supporting equipment and experienced personnel. The uses of microtunneling
methods for underground pipeline installation is increasing as this technology can
significantly minimize the social and environmental impacts related to the traditional
open-trench method of conduit construction. At the same time, microtunneling has

proven to be a cost-effective means of new subsurface infrastructure construction. This

cost-effectiveness is apparent in both the direct costs of the construction and reduced
social costs, and increases in intangible benefits (Bhavani, 2004). Furthermore, utilization
of thin-wall pipe in microtunneling will potentially decrease the cost and increase
competitiveness. As a result, the need to better understand the Operations involved
becomes crucial for improved planning, estimating and resource selection (Nido et a1.

1999).

Computer simulation can be used to study microtunneling operations before they are
actually‘perfonned. For the repetitive nature of microtunneling operation, data collected
from the site can be input to well designed simulation model to repeat the operation in
computer thousands of times, which will be impossible in real world. The big amount of
data generated from simulation can magnify any inefficiency of resource used in the
operation to easilyidentify problems at different stages of the project. The model can be
modified to include possibilities of soil compositions and simulate corresponding
productivity. Therefore, the statistical relationship between soil composition and

microtunneling productivity can be studied.

1.3 Goal and Objectives

The main goal of this study is to analyze and to evaluate the factors that affect the
productivity of microtunneling operation, thereby to refine the microtunneling process
and optimize productivity. In addition, the relationship between different soil conditions
and microtunneling productivity will be studied. In order to analyze microtunneling
technology an actual project was chosen, the data was collected at the Louisiana Tech

University LLB Microtunneling Field Test Project in Ruston, Louisiana. The operation

analysis will be performed using simulation based on the CYCLONE methodology.

Specifically, the research has following objectives:

1. Portray the process of microtunneling operation, identify resources,

2. Develop the model for simulation,

3. Analyze the production cycle data and find statistical distributions,

4. Input the distribution data in the model and run simulation with WebCYCLONE,

5. Compare the simulated productivity results with actual observations at the project,
and modify the model if necessary,

6. Perform sensitivity analysis by varying resource assignments, to measure their
effects on the operation’s productivity and find the optimization,

7. Enhance CYCLONE model with consideration of soil compositions,

8. Run Simulation with variety of soil compositions to obtain corresponding
productivity and

9. Study of the correlation between soil composition and microtunneling.

1.4 Methodology

 

Review
Microtunneling
Methods

 

 

 

 

 

 

nhanced Mode
with Soil

Composition
Factors

Run Simulation
in WebCYCLONE

  
     
     
 

  

un Simulation in
WebCYCLONE with
Different Soil
Compositions

Resource

Sensitivity

 

Analysis

ind Correlation

 

 

 

 

    

Review
Review Procedures of
Construction Actual
Simulation Microtunneling
(CYCLONE) ”01°91
Build Prototype   Statistical
CYCLONE Analysis of
Microtunneling Activity
Simulation Model Durations

Modify

A

Run Simulation
in WebCYCLONE

 

Validate
Simulation

 

 

N9

 

 

 

 

Ye_s Results

 

 

Find Bottlenecks
and Give
Recommendations

 

 

 

 

Composition and
Productivity

 

Provide Functions of
Productivity and Soil
Com ositions

Figure 1.2 -Flowchart of the Thesis Study

/

As illustrated in Figure 1.2, this study consists of several steps. At first, overviews on

microtunneling methods in general and the candidate project in‘specific, and construction

simulations are presented. Upon finishing reviews, a prototype simulation model with

CYCLONE methodology is developed, Which need inputs from the project procedures
and collected duration data. The candidate project data collected on Site need to be
analyzed statistically to find distributions before running simulation in WebCYCLONE
software. Prototype model and data distributions input together with resource
initialization are coded to run WebCYCLONE simulations. Productivity results from
multiple simulations are averaged and validated with actual cycle duration measured
from the project. According to the comparison of Simulation result and actual data, the

model may be adjusted and Simulations need to be redone to validate the model.

After validation of the prototype model, the same structure and logic are used with
enhancement of soil compositions to build a new model. The enhanced model is coded
together with soil cOndition specified activity duration distribution data into
WebCYCLONE simulations. Resource sensitivity analysis is conducted on the simulation
results to find bottlenecks on productivity and Optimize the operation. Recommendations
on streamlining the candidate project in specific and microtunneling operations in general

are presented.

In addition, the enhanced model is modified to reflect different soil compositions faced
by the microtunneling operation. The productivities simulated with corresponding soil
compositions are studied with statistical regression analysis to find any correlations
between them. Microtunneling productivity as a function of soil composition is stated in

the conclusion of the thesis.

1.5 Scope and Limitations of the Thesis

The scope of this thesis research is limited to the micrOtunneling productivity study
through operational simulation of the LLB microtunneling propulsion system field test,
which includes details of simulation model developments, statistical analysis of activity
duration data, simulation results validation, sensitivity analysis, soil composition
alternatives study with simulation. In addition, background information on

microtunneling operation, construction simulation, and soil classifications are presented.

The simulation will be conducted on the cyclic parts of the microtunneling process,
including from pipe section preparation to pipe section jacked in place. In mobilization
and demobilization stages, activities including digging shafis, hauling MTBM, setting up

control console etc. will not be modeled into the simulation due to the non-cyclic nature.

In the candidate project, the microtunneling equipment and PVC pipe installed were both
sponsored by manufacturers for scientific research purpose with no monetary charge. Due
to the missing cost data of MTBM and pipes, total cost of the microtunneling operation is
not considered in the scope of this study. Therefore, productivity optimization will not

consider cost factors.

The function of productivity and soil compositions is based on the actual soil samples
used in the project. The correlation is highly related to the microtunneling equipment,
pipe installed, and soil conditions of the project. It can be considered a general rule, but is

not intended to predict productivity in any microtunneling project. Such a goal needs

more complete database from variety of microtunneling projects and requires further

study.

1.6 Organization of the Thesis

This study consists of six chapters. The first chapter provides a brief introduction to the
topic and research proposal statement. The second chapter presents an overview of four
closely related topics of existing literature, which include microtunneling operation in
general, pipe materials used in microtunneling, soil classifications and properties, the
simulation candidate project description, and construction simulation methodologies. The
third chapter contributes the simulation models with and without soil factor enhancement.
The fourth chapter presents statistical analysis of activity duration data distributions as
input of the simulation. The fiflh chapter validates and discusses results from simulations,
and conducts resource sensitivity analysis to identify resource bottlenecks.
Microtunneling operations in different soil conditions are simulated and correlations
between productivity and soil composition are in the fifth chapter also. The sixth and
final chapter presents the conclusion of the research and recommendations for optimizing
the microtunneling operation productivity. Such information can provide an effective tool
to assist project managers in making well-informed decisions. Potential future studies

will also be suggested.

Appendices include microtunneling glossary, actual duration data collected from the
project, codes of two simulation models, and data from simulation results. A list of

referenced materials is presented at the end of this study.

2 LITERATURES AND PROJECT REVIEW

The literature review chapter comprises of five sections. The first section reviews the
microtunneling methods. The second briefly reviews pipe materials used in
microtunneling. The third describes soil classifications and their properties. After
background introduction, the simulation candidate project is described in section four.
Necessary information for model development can be found in this section. The fifth is
the background and brief history of construction Simulation, along with popular
simulation methodologies introduction. The last section summarizes the literature '

review.

2.1 Microtunneling Methods

The term microtunneling is used to describe methods of horizontal earth boring which are
highly sophisticated. Microtunnel Boring Machines (MTBM’S) are laser guided, remotely
controlled boring machines which permit accurate monitoring and adjusting of the
horizontal and vertical alignment as the work proceeds so that the pipe can be installed on
precise line and grade (Iseley and Tanwani, 1992). This method is uniquely suited for the

installation of gravity sewer lines Where a high degree of accuracy is required.

American Society of Civil Engineers (ASCE, 2001) defines microtunneling as a
trenchless construction method for installing pipelines with all following features
utilized.

1. Remote controlled — The microtunneling boring machine (MTBM) is operated

from a control panel, normally located on the ground surface. The system

10

Simultaneously installs pipe as spoil is excavated and removed. Personnel entry to
the tunnel is not required for routine operation.I

2. Guided — The guidance system usually refers to a laser beam projected onto a
target in the MTBM, capable of installing gravity sewers or other types of
pipelines to the required tolerance, for line and grade.l

3. Pipe jacked — The process of constructing a pipeline by consecutively pushing
pipes and MTBM through the ground using a jacking system for thrust.l

4. Continuously supported — Continuous pressure is provided to the face of the

excavation to balance groundwater and earth pressures.l

2.1.1 Method Description

Microtunneling is a trenchless construction method for installing conduits below ground
in a wide range of soil conditions, while maintaining close tolerances to line and grade
from the drive shaft to the reception shaft. The microtunneling process is a cyclic pipe

jacking process.

Based on the mode of operation, the microtunneling method can be subdivided into two
major groups: 1) slurry method and 2) auger method. In the slurry type method, slurry is
pumped to the face of the MTBM. Excavated materials mixed with slurry are transported
to the driving shaft, and discharged at the soil separation unit above the ground. In an
auger type method, excavated materials are transported to the drive Shaft by the auger in a

casing pipe, and then hoisted to ground surface by a crane. However, since slurry

 

l ASCE Standard Construction Guidelines for Microtunneling

ll

microtunneling is more versatile by protecting the tunnel face by slurry pressure
(specially under water table and unstable ground), the auger type MTBM is not common
in the United States. Because the simulation candidate project used slurry type MTBM,
only slurry type microtunneling is reviewed in detail. Both microtunneling systems

consist of the following six major components:

1. Microtunnel boring machine (MTBM),

2. Automated spoil transportation and rate of excavation controls,

3. Pipe jacking equipment suitable for the direct installation of the product pipe,
4. Remote control system,

5. Active direction control, and

9‘

Jacking pipe

2.1.1.1 Slurry Microtunneling Boring Machine (MTBM)

In this method, a rotating cutting head excavates soil mechanically. The rotation of the
cutting head can be eccentric or centric, and the speed of rotation (RPM) can be constant
or variable. Cutter heads are bi-rotational. The head normally rotates in clockwise
direction when looking from the rear of the machine. Reverse rotation can provide more
flexibility in overcoming obstructions and difficult ground condition. The spoil excavated
at the face is extruded through small parts located at the rear of the MTBM face into the
mixing chamber. The main functions of this chamber are to mix the Spoil with clean
water from the separation system and control hydrostatic head imposed on the MTBM
face by a body of water or groundwater. When the spoil and water are mixed to Slurry

with suitable pumping consistency, typically less than 60% solids, the slurry is

12

transported to the solids separation system hydraulically (Iseley et a1. 1999). Figure 2.1
illustrates the inside structure of slurry type MTBM. Drives of up to 1200 it have been
completed in full-face solid granite by MTBM with rock strengths exceeding

20,000psi. Virtually, all ground conditions can be completed with large slurry MTBM.

 

 

 

 

 

1. Cutting wheel 8. Steering cylinder
2. Extraction tool 9. Conveyor pipe

3. Crusher space 10. Supply pipe

4. Nozzles 11. ELS target

5. Main bearing 12. Laser beam

6. Rotation drive 13. Bypass

7. Shield articulation seal 14. Valve block

Figure 2.1 -Typical Slurry Type MTBM (Najafi, 2005)

Some pictures of slurry type MTBMs are shown in Figure 2.2, 2.3, and 2.4.

 

 

Figure 2.4 - Inside of MTBM (Najafi, 2005)

2.1.1.2 Jacking System

The main jacks are mounted in a jacking frame and are located in the drive (starting)
Shaft. A jacking frame is Shown in Figure 2.5. The jacking frame successively pushes the
MTBM along with a string of connected pipes toward a receiving shaft. The jacking
capacity of the system must be sufiicient to push the MTBM and the string of pipes
through the ground. Calculations must be made in advance to determine 1) face
excavation forces, 2) frictional forces, and 3) weight of the MTBM and pipes. The
jacking equipment installed must have capacity greater than the calculated theoretical
jacking load to allow for a safety factor. The hydraulic cylinder extension rate must be
synchronized with the excavation rate of the MTBM, which is determined by the soil
conditions. Figure 2.6 shows a 42 in steel casing with 20 it long section that is being

jacked.

 

 

‘ 4‘ acking Frame 3

- “—3 n wry-1&3

Figure 2.5 - Jacking Frame for Microtunneling (Najafi, 2005)

 

Figure 2.6 - Steel Casing Being Jacked (Najafi, 2005)

_ Intermediate jacking stations are usually provided for diameters larger than 900
millimeters (36 inches) and‘when the calculation of the total jacking force needed to
complete the installation exceeds 80 percent of the capacity of the main jacks or the
designed working compressive loads allowed for the pipe. The jacking system must
develop a uniform distribution of jacking forces on the end of the pipe by the use of

spreader rings and packing.

If the calculated jacking forces on the pipe are expected to exceed the pipe design
strength with a 2.5 to 1 safety factor, a pipe lubrication system can be utilized. An
approved lubricant is injected at the rear of the MTBM and, if necessary, through the pipe

walls to lower the friction developed on the surface of the pipe during jacking.

The jacking capacity ranges from approximately 100 tons to over 1,000 tons. The jacking
capacity is mainly determined by the length and diameter of the bore and the soil. The
soil resistances are generated from face pressure, friction, and adhesion along the length

of the steering head and pipe string. The jacking system determines two major factors of

microttmneling operation: the total force or hydraulic pressure and penetration rate of
pipe. The total jacking force and the penetration rate are critical to control the

counterbalancing forces of the MTBM.

2.1.1.3 Automated Spoil Transportation

The spoil is mixed into the slurry in a chamber located behind the cutting head of the
MTBM. This mixed material is transported through the slurry discharge pipes and
discharged into a Separation system. This system is a closed-loop system because the
slurry is recycled. The velocity of the flow and the pressure should be carefully regulated
because the slurry chamber pressure is used to counterbalance the groundwater pressure.
The machine can be sealed off from external water pressure, allowing underwater
retrieval. Slurry is a mixture of bentonite (a clay material) in a powder form and water.
The bentonite is used to increase the density of water so that it can transport heavy spOil
particles. These heavy particles are filtered from the slurry at the separation units. The
filtered slurry is sent to storage tanks, which will be recirculated through the system.
Figure 2.7 (a) Shows the soil separation system. One of the three screens for the

separation system is shown in Figure 2.7 (b).

Soil Seprtion Pant .-., ‘ i

(a) Soil Separation System (b) Screen for Soil Separation System

      

Figure 2.7 - Soil Separation System (Najafi, 2005)

17

The system is capable of any adjustment required to maintain face stability for the
particular soil condition encountered on the project. The system monitors and
continuously balances and ground water pressure to prevent the loss of slurry and/or

ground water.

In a slurry spoil transportation system, the ground water pressure is managed by the use
of the variable speeds slurry pumps, pressure control valves and a flow meter. A slurry
bypass unit is included in the system to allow the direction of flow to be changed and

isolated as necessary.

A separation process is provided when Using the slurry transportation system. The
process is designed to proved adequate separation of the spoil from the slurry so that the
clean slurry can be returned to the cutting face for reuse. The type of separation process
used is dependent upon the size of the tunnel being constructed, the soil type being

excavated, and the space available for erecting the plant.

2.1.1.4 Guidance and Remote Control System

A remote control system is provided to allow for the operation of the system without the
need for personnel to enter the microtunnel. The control equipment must integrate the
system of excavation and removal of soil and its simultaneous replacement by a pipe. As
each pipe section is jacked forward, the control system will synchronize all of the

Operational fimctions of the system.

18

The laser is the most commonly used guidance system for microtunneling. The laser
gives the line and grade information for the pipe installation. The laser is installed in the
driving shaft and gives afrxed reference point. The laser target and a closed circuit
television (CCTV) camera are installed in the MTBM. There should not be any
Obstruction along the laser beam pathway from the driving shaft to the laser target. There
are two types of laser targets: the passive system and the active system. In the passive
system, a target grid is mounted in the steering head. The CCTV monitors this target and
the information obtained by this CCTV is transferred back to the operator’s control panel.
The operator can make any steering correction based on the information. In the active
system, photosensitive cells are installed on the target and these cells convert information
into digital data. Those data are electronically transmitted to the control panel and give
the operator digital information of the location. Both active and passive systems are
commonly used. Figure 2.8 shows the laser used for the Soltau microtunneling system.

The target mounted in the MTBM is shown in Figure 2.9.

 

Figure 2.8 - Laser for Guidance of MTBM (Najafi, 2005)

19

‘ CuttingI-Iead FEW-‘2»

 

Figure 2.9 - Target Mounted in the MTBM (Najafi, 2005)

Operation boards are usually located in a standard container with 8 by 20 ft dimensions.
Operation board consists of control panel, computer and monitor, and a printer. Through
the operation board, all the microtunneling operations such as tunneling machine, main
jacks, interjack stations, direction and Speed of the cutting wheel, and bentonite
lubrication equipment, etc. can be controlled. An example of operation board of Soltau
Microtunneling is shown in Figure 2.10. The Screen of the computer in operation board
is presented in Figure 2.11.

" - 25—.

 

Control Panel

Figure 2.10 - Operation Board of a MTBM (Najafi, 2005)

20

if? g

'4’
t.
i
.1.
'l
‘2
'2

 

Figure 2.11- Computer Screen (Najafi, 2005)

In addition to the computer monitor, two other monitors are used in the microtunneling
Operation. One is for communication purpose, and the other one is for monitoring the
inside of MTBM. A small camera with microphone is installed at the top of sheet pile at
driving shaft, which provides the overview of the operation. The operator in the cabin can
see and hear the tunneling site so that he/she can control the equipment based on input
from the crews on the site. Another small camera is installed inside the MTBM. This
camera provides a View inside the MTBM. These two monitors are shown in Figure 2.12

and 2.13.

21

 

Figure 2.13 - Monitor Showing a View Inside the MTBM (Najafi, 2005)

2.1.1.5 Active Direction Control

Line and grade is controlled by a guidance system that relates the actual position of the
MTBM to a design reference, by a laser beam transmitted from the jacking shaft along

the centerline of the pipe to a target mounted in the shield. The MTBM is capable of

22

maintaining grade to within :25 millimeters (:1 inch) and line to within :38 millimeters

(:15 inches). The line and grade tolerances are subject to project and ground conditions.

The active steering information is monitored and transmitted to the operation console.
The minimum steering information available to the operator on the control console
usually includes the position relative to the reference, role, inclination, attitude, rate of

advance, installed length, thrust force, and cutter head torque.

2.2 J acking Pipe Materials Used in Microtunneling

2.2.1 General Requirements

In general, pipe used for microtunneling must be round, have a smooth, uniform outer
surface, and with watertight joints that also allow for easy connections between pipes.
Pipe lengths must be within. specified tolerances and pipe ends must be square and
smooth so that jacking loads are evenly distributed around the entire pipe joint and such
that point loads will not occur when the pipe is jacked in a reasonably straight alignment.
Pipe used for microtunneling is capable of withstanding all forces that will be imposed by
the process of installation, as well as the final in-place loading conditions. The driving
ends of the pipe and intermediate joints are protected against damage as specified by the
manufacturer. The detailed method proposed to cushion and distribute the jacking forces
is specified for each particular pipe material. In detail, microtunneling pipe should meet
the following general requirements:

1. Circular shape with a flush outside surface (including at the joints)

23

2. Strength sufficient to withstand both installation loads and the in-place,
long term service loads

3. Dimensional tolerances on length, straightness, roundness, end squareness,
and allowable angular deflection

4. Durability for the service exposure (internal and external corrosion
resistance)

5. Joints capable of the specified level of water-tight performance and

transfer of j acking loads between pipes

In microtunneling operation, any pipe showing signs of failure may be required to be

jacked through to the reception shaft and removed. The pipe manufacturer’s design

jacking loads should not be exceeded during the installation process. The ultimate axial

compressive strength of the pipe must be a minimum of 2.5 times the design jacking

loads of the pipe (Najafi, 1993).

2.2.2 Material Types

At present time the following seven pipe materials specially manufactured for

microtunneling operations are available:

1.

2.

Ductile iron (DI)

Fiberglass-reinforced polymer mortar (RPM)

.' Polymer concrete (PC)

Polyvinyl chloride (PVC)

. Reinforced concrete (RCP)

24

6. Steel

7. Vitrified clay (VCP)2

Pipe installation by microtunneling is most widely done in sewer and drainage
applications. The pipes most often jacked in these nonpressure applications include PC,
RCP, RPM, and VCP. All of these pipe materials have a substantial microtunneling
installation history in sewer applications. Steel pipe, although rarely used in sewers, is
routinely installed by jacking and microtunneling for casings and various other structural
applications. New methods of joining steel pipe and new coating and lining technology
will likely broaden the application of steel pipe to include pressure systems.
Microtunneling of pressure pipes was limited before 1998. Materials suitable for this

application include DI, RCP, reinforced concrete cylinder pipe, RPM, and steel pipe.

In addition, the newest microtunneling pipe is solid-wall PVC, first installed in the USA
in 1997 (ASCE, 2001). The simulation condidate project conducted in Louisiana Tech
University, which will be studied in this thesis, unusually installed PVC sewer pipes with

special microtunneling equipments in the USA.

2.2.3 Material Selection

Pipe Materials used in microtunneling should be selected base on many factors, including
1. Pipeline operating conditions (pressure — operating, test, transient, and

vacuum),

 

2 ASCE Standard Construction Guidelines for Microtunneling

25

2. Pipeline service environment (fluid, temperature, and corrosivity),

3. External loads (soil loads, surface live loads, and water head),

4. Pipe inside diameter required,

5. J acking machine (type and diameter), anticipated jacking loads, and drive
lengths,

6. Pipe deformation and rebound (during jacking) for plastic/elastic materials,

7. Pipe hydraulic characteristics,

8. Pipe performance capabilities,

9. Pipe availability, reliability, and durability,

10. Life cycle cost.

The following are typical lengths of pipe sections for the different pipe materials (Table

2.2).

Table 2.1 -Typical Lengths Of Pipe SectiOns Used In Microtunneling (ASCE, 2001)

 

 

 

 

 

 

 

 

Material Type Standard Available
DI 19.5’ Varies
PC 8’/10’ and lm/2m/3m 3’/6’
PVC 2’/4’/6’ Varies
RCP 7.5’ to 24’ Varies
RPM 10’/20’ . 4’/5’/6.5‘/8’
Steel 8 ’/10’/20’/40’ Any
VCP 4’/6’/8’/10’ and lm/2m/3m 2’/5’

 

 

 

 

 

As material costs comprise about half of the total cost of the microtunneling operation
(Nido et a1. 1999), cost is major concern of pipe selection. Compared to other types of

pipe materials available for microtunneling such as reinforced concrete, steel and

26

glassfiber reinforced plastic mortar pipe (GRP), PVC sewer pipe has less unit cost
(Najafi, 1993). This is the motivation that the simulation candidate project selected PVC

sewer pipe, which is not commonly used in microtunneling.

2.3 Soil Conditions

The most favorable ground condition for slurry microtunneling is wet sand. However, a
wide selection of MTBM cutter heads are available that provide the capability to handle a
range of soil conditions, including boulders and solid rock. Typically, boulders of 20 to
30 percent of the machine diameter can be removed by microtunneling by crushing the
boulders into particle sizes of 1 in and smaller. Table 2.3 presents applicability of slurry

microtunneling for different soil conditions.

Table 2.2 -Applicability of Slurry Microtunneling for Different Soil Conditions (Najafi, 2005)

 

 

 

 

 

 

 

 

 

 

 

Type of Soil Applicability
Soft to very soft clays, silt & organic deposits Yes
Medium to very stiff clays and Silts Yes
Hard clays and highly weathered shales Yes
Very loose to loose sands (above water table) Yes
Medium to dense sands (below the water table) Yes
Medium to dense sands (above the water table) 3 Yes
Gravels & cobbles less than 2-4 in. diameter Yes
Soils with significant cobbles, boulders and obstructions larger than 4-6 in. diameter Marginal
Weathered rocks, marls, chalks and firmly cemented soils Yes
Significantly weathered to unweathered rocks No

 

 

 

 

2.3.1 Soil Classifications

In order to study the impacts of different soil compositions on microtunneling operation

using simulation, the subsurface conditions must be classified. Soil classification systems

27

are for the purpose of identifying soils in a systematic manner to determine suitability for

use in specific applications based on past experience.

0 N oncohesive and cohesive soils: If an inherent physical characteristic of the mass
of soil grains is that on wetting and/or any subsequent drying, the soil grains stick
together so that some force is required to separate them in the dry state, the soil is
cohesive. If the soil grains fall apart after drying and stick together only when wet
because of surface tension forces in the water, the soilgis cohesionless, or noncohesion

(Bowles, 1984).

0 Soil Texture: Soil texture may be defined as the visual appearance of a soil based
on a qualitative composition of soil grain Sizes in a given soil mass (Bowles, 1984).
Large soil particles with some small particles will give a coarse-appearing or coarse-
textured soil. A conglomeration of smaller particles will give a medium-textured
material, and a conglomeration of fine-grained particles yields a fine-textured soil. It can
be observed, however, that lumps of fine-grained materials will give a coarse texture, so
we must also relate texture to the state of elemental soil particles. Texture based on visual
appearance is often used in soil classification of cohesionless materials such as coarse
sand, medium coarse sand and gravel, fine sand, etc. Texture is not used for cohesive

soils, since the soil state is a factor in the texture (i.e., lumps can be pulverized).

2.3.2 Soil Classification Common Systems

28

Soils may be classified in a general way as cohesionless or cohesive, or as coarse- or
fine-grained. These terms are too general to provide either a repeatable or reproducible

identification of similar soils.

A number of classification systems have been proposed in the past. Table 2.4 illustrates

several of the classification systems that have been used.

Table 2.3 -Soil Classification Systems (Bowles, 1984)

 

 

 

 

 

 

 

 

 

4 200
Sieve number:
Unified Cobbles Gravel Sand Silt Clay
Size, mm
76.1 .
4 0.074 0.002

In the Louisiana Tech University microtunneling project, only the Unified Soil
Classification (USC) System was used for selecting soils. The USC System, which was
originally developed for military airfield construction during World War H and
subsequently published with wide acceptance resulting, is most wiklely used System (and
internationally) for foundation engineering such as dams, buildings, and underground

construction.

In the USC system, those physical properties of use in predicting suitability of a soil as a
construction material for fill as in earth dams and levees, for use in building sites as fill,

for road fills, and similar are

0 Percentages of gravel, sand, and fines — requiring a sieve analysis

29

0 Shape of the grain size distribution curve — may require plotting the sieve analysis

data

0 Plasticity (WL, WP, and IP) — requiring Atterberg limits

2.3.3 The Unified Soil Classification (USC) System

This system, originally developed for in airfield construction, was reported by

Casagrande (1948). It had already been in use since about 1942, but was slightly

modified in 1952 to make it apply to dams and other construction.

The principal soil groups of this classification system are given in Table 2.5. As shown in
the table under the column heading “Group Symbols,” the soils are designated by group

symbols consisting of a prefix and suffix. The prefixes indicate the main soil types and

the suffixes indicate the subdivisions within groups as follows:

Table 2.4 —Principal Soil Groups in USC (Bowles, 1984)

 

 

 

 

 

 

 

Soil type Prefix Subgroup Suffix
Well graded W
Gravel G Poorly graded P
Sand S Silty M
Clay C
Silt M
Clay C WL < 50 percent L
Organic 0 WL > 50 percent H
Peat Pt

 

A verbal description should accompany the classification symbols, e.g., brown, coarse,

well-graded sand with trace of gravel, SW. The ASTM D-2487 should be consulted for

30

 

any requirements for classifying the soil. In general, soils that have the same

classifications tend to have the same engineering behavior (Bowles, 1984).

Table 2.5—Descriptions of Group Symbols in USC (Bowles, 1984)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Group Typical Names

Symbols

GW Well-graded gravels, gravel-sand mixtures; little or no fines.

GP Poorly graded gravels, gravel~sand mixtures; little or no fines.

GM Silty gravels, poorly graded gravel—sand-silt mixtures.

GC Clayey gravels, poorly graded gravel-sand-clay mixtures.

SW Well-graded sands, gravelly sands; little or no fines.

SP Poorly graded sands, gravelly sands; little or no fines.

SM Silty sands, poorly graded sand-silt mixtures.

SC Clayey sands, poorly graded sand-clay mixtures.

ML Inorganic silts and very fine sands, rock flour, silty or clayey fine sands with slight
plasticity.

CL 1 Inorganic clays of low to medium plasticity, gravelly clays, sandy clays, silty clays, lean
clays.

0L Organic silts and organic silt-clays of low plasticity.

MH Inorganic silts, micaceous or diatomaceous fine sandy or silty soils, elastic silts.

CH Inorganic clays of high plasticity, fat clays.

OH Organic clays of medium to high plasticity.

Pt Peat, muck, peat-bog, etc.

 

 

 

 

A soil is well graded or nonuniform if there is a Wide distribution of grain sizes present,
i.e., if there are some grains of each possible size between the upper and lower gradation
limits. A soil is poorly graded, or uniform, if the sample is mostly of one grain size or is

deficient in certain grain sizes. A beach sand is an example of a unifome graded soil.

The Unified Soil Classification System defines a soil as:

1. Coarse-grained if more than 50 percent is retained on the No. 200 sieve

31

2. F ine-grained if more than 50 percent passes the No. 200 sieve

The coarse-grained soil is either:
1. Gravel if more than half of the coarse fraction is retained on the No. 4 sieve
2. Sand if more than half of the coarse fiaction is between the No.4 and No. 200

sieve Size

The coarse-grained soil is shown in Table 2.7.

Table 2.6 —Coarse-grained Soils (Bowles, 1984)
GW, GP or SW, SP 3 5% passes No. 200 sieve
GW—GM, GP-GM, GW-GC, GP-GC or
SW-SM, SP-SM, SW-SC, SP-SC ‘
GM, GC or SM, SC > 12 percent passes No. 200 sieve

 

 

5 < Percent passing No. 200 sieve .<_ 12

 

 

 

 

 

Classification of coarse-grained soils depends primarily on the grain-Size analysis and
particle size distribution. A major classification change with a small increase or decrease
in the percent passing the No. 4 or NO. 200 sieve is another reason why a verbal
description is included along with the symbols, i.e., very sandy gravel, very gravelly

sand, etc.

Only the sieve analysis and the Atterberg limits are necessary to classify the soil in USC
system. A sieve analysis is performed and a plot of the grain-size distribution curve is
made. When less than 12 percent passes the No. 200 sieve, it is necessary to obtain Cc
and Cu to establish whether the soil is well or poorly graded. When more than 12 percent

of the material passes the No. 200 sieve, the uniformity coefficient Cu and the coefficient

32

of curvature Cc have no significance and only the Atterberg limits are used to classify the

soil.

2.3.4 Soil Selection in the Candidate Project

The main goal in determining the four different soil types to be used in the project was to
obtain a consistent soil so that the effects of different types of soil on LLB
microtunneling system could be determined (Najafi, 1993). Although encountering such a
soil variety would be probably rare in actual practice for a single microtunneling
operation, it was assumed that the results of the microtunneling test could be used for
simulation of impacts of similar types of soils so that the performance of the
microtunneling LLB system could be predicted for different subsurface conditions.
Moreover, the simulation result could add knowledge of different subsurface conditions’
impacts on general microtunneling productivity and cost. Therefore, in order to simulate
soil materials mostly encountered in real situations, samples of sand, clay, silt, and clayey

gravel were selected.

Eleven different soil samples were tested for possible use in the microtunneling project.
These included sands, silts, clays, gravels, and various combination of each. Out of these
11 samples, three most desirable for optimum compaction were selected for backfilling in
14,6-meter (48-foot) lengths in the test trench. Each sample was tested for particle size

distribution and Atterberg limits so that it could be properly classified (N aj afi, 1993).

The soil specimens were prepared for the appropriate tests in accordance with either

ASTM D-2217 (Standard Practice for Wet Preparation of Soil Samples for Particle-size

33

Analysis and Determination of Soil Constants) or ASTM D-421 (Standard Practice for
Dry Preparation of Soil Samples for Particle-Size Analysis and Determination of Soil

Constants).

guide-Size AnglysLsL Each of the samples was subjected to a particle-size analysis in.
accordance with ASTM D-422 (Standard Method for Particle-Size Analysis of Soils). A
representative ample was taken from each of the 11 samples. A sieve analysis was
conducted on the portion retained on the #10 sieve, while the portion passing the #10
sieve was subjected to hydrometer analysis. After the hydrometer analysis was
completed, the specimen was washed over a #200 sieve, and the retained material was

dried overnight and subjected to a sieve analysis.

Atterberg Limits Testip_g._1n order to classify the samples containing clay and silt, it
was also necessary to conduct tests to determine the Atterberg limits of the samples. The
procedures Used for finding these limits were in accordance with ASTM D-4318
(Standard Test Method for Liquid Limit, Plastic Limit, and Plasticity Index of Soils). The
liquid limit of each sample was found by preparing a representative portion of that

sample passing the #40 sieve and testing it in a standard liquid. limit device. The plastic

limit of each sample was found by rolling a portion of the sample into%-inch thick

threads as required by the standard test. The plasticity index was then found by

subtracting theplastic limit from the liquid limit.

34

Each of the 11 samples was subjected to tests to that it could be properly classified.
according to the USC system. Table 2.20 is a list of the results of the classification

procedures conducted on each of the samples.

Table 2.7 — Soil Classifications in the Candidate Project (Najafi, 1993)

 

 

 

 

 

 

 

 

 

 

 

 

Sample Number Group Symbol Group Name

#1 SP Poorly graded sand
#2 SC Clayey sand

#3 SP Poorly graded sand
#4 CL Sandy lean clay

#5 GP Poorly graded gravel
#6 CL Sandy lean clay

#7 SM Silty sand

#8 CL Lean clay

#9 CL Lean clay with sand
#10 SP Poorly graded sand
#11 GC Clayey gravel with sand

 

 

 

 

 

To select the four samples of sand, clay, silt, and gravel, to be used in the project, sample
#7, a. grayish brown, very fine material, was chosen as the silt to be used; a combination
of samples #8 and #9, which were taken from the jobsite at different depths, was chosen

as the best clay sample to used; sample #10, a light brown material, as chosen as the sand

to be used; sample #11, a sample of pit-run} gravel, a mixture of 19- to 25.4- mm (% - to

1- inch) top Size gravel, sand, and clay, was obtained and chosen as the gravel to be used.

2.4 Simulation Candidate Project Description

2.4.1 Project Location and Soil Profile

35

For this study, data was collected on the Louisiana Tech University LLB Microtunneling
Field Test Project, located in Ruston, Louisiana. This project was conducted in order to
evaluate workability of the LLB system in actual field conditions. As a technology
transfer project, details of the test were finalized between the LLB system manufacturer-
Kidoh Construction Company, Iseki Inc., and Trenchless Technology Center at Louisiana
Tech University. A 58.52 meters (192 feet) long test bed was constructed on the
Louisiana Tech University campus. An excavation of 43.89 meters (144 feet) in length
and 2.13 meters (7 feet) wide and 3.05 meters (10 feet) deep was constructed. It was
backfilled with equal sections of clay, silt, sand, and clayey gravel. An additional 14.6-
meter (48-foot) section of the test bed was undisturbed stiff clay. The length of each
section of the test bed was chosen to be the equivalent of Six 2.438-meter (8-foot) pipe
seCtions. The depth of installation was unifome 2 meters (6.6 feet), which is the
minimum requirement for slurry microtunneling method to provide enough pressure to
prevent slurry loss. The ground water level was found to be 1.5 meters (5 feet). Figures

2.14 to 2.16 illustrate the test bed construction.

6 M ‘ 14.6 M I 14.6 M I 14.6 M I 14.6 M '

 

 

 

 

 

me «a an “R ‘flfl
gig“ CLAY SILT SAND CLAYEY
GRAVEL

 

 

Figure 2.14 - Test Bed Plan (Najafi 1993) _

36

 

 

    
 

 

 

 

 

 

 

 

 

Figure 2.15 — Test Bed Cross Section (Najafi 1993)

Figure 2.16 —Test Bed Construction (Najafi 1993)

37

M /fi — Ground Surface
s/
(/
0.5M 0.66M 0.5M 1.2M(4FT)/‘
I // j l:
\ j / 2
0.6 M 2 FT -
/x/ ( ) E
II 0.66 M (2.2 FT) ”
A 0.34M (1.2 FT) II
7 f
/
PVC PIPE “*4 LINE F EXCAVATION 1.5 1101 slo

 

 

 

2.4.2 J acking Forces

The jacking forces in this project varied from a range of 9 tf to 14 if when jacking
through clay, from 10 tf to 20 tf when jacking through silt, from 11 tf to 21 tf when
jacking through sand, from 23 tf to 41 tf when jacking through Clayey gravel. Detailed

jacking force information was obtained for 24 of the PVC pipe drives.

2.4.3 Microtunneling Pipes

The project consists of the installation of 58.5 meters (24 drives) of OD 620 mm PVC
sanitary sewer pipe using Iseki Unclemole (TCC 500) microtunneling machine. PVC is a
suitable product for sewer system construction. Some of the advantages of PVC pipes
include the following: 1) light weight and easy to handle, 2) good impact resistance and
toughness, 3) excellent resistance to a wide range of corrosive environments found in
sewage and soil, 4) good hydraulic flow characteristics, 5) easy to work with, 6)
economical, 7) durable, 8) availability of different joint systems which are extremely
reliable against leakage, 9) excellent abrasive resistance, 10) excellent dimensional
control, and 11) not biologically degradable (Najafi, 1993). The use of PVC sewer pipe
has decreased infiltration and exfiltration and accompanying tree-root problems. The
surface of the pipe is very smooth and resists buildup of deposited materials and other

solids.

Compared to other types of pipe materials available for microtunneling such as reinforced

concrete, steel and glassfiber reinforced plastic mortar pipe (GRP), PVC sewer pipe has

38

,less unit cost (Najafi, 1993). However, in the past, the following factors were the main
obstacles to the utilization of PVC pipe in microtunneling:

1. Axial thrust load limitations,

2. Higher cost of thick-wall PVC pipe to resist the thrust load, and

3. Lack of a suitable joint compatible for microtunneling.

In the LLB system, the above obstacles have been removed with a method of
transmission of the thrust force by the addition of a liner casing and gripper system. This
system transfers the face resistance of the machine to the liner casing inserted in the pipe.
1 Also, the circumferential frictional resistance of the product pipe transfers to the gripper
systems which are installed at certain interVals along the length of the pipe. These gripper
systems expand with air pressure and connect the liner casing with the inner surface of
the pipes to transmit the thrust 'force of the liner casing to the pipes. Therefore, the
maximum thrust force exerted to the product pipes is equal to the circumferential
fiictional resistance of the portion of product pipes between the gripper locations.
Consequently, with utilization of the LLB system, pipes with relatively low compressive

strength can be installed with microtunneling methods.

In addition to reducing the thrust force on the plastic pipe, the gripper system also has the
following Characteristics:
1.- There is minimal possibility of damaging pipes because the contact is made by

pneumatically inflated rubber tubes.

39

2. Conventional microtunneling methods require product pipes of special wall
thicknesses. The LLB system does not have these requirements.

3. The grippers can be installed at desired locations depending on the level of
circumferential resistance of the pipes.

4. Long-distance thrusting with minimal restriction to pipe compressive strength is

possible with LLB system.

Some of the characteristics to consider when selecting a pipe for microtunneling
operations are stiffness, smoothness of the pipe and joint design, joint watertightness, .
dimensional consistency, weight, resiliency and absorbency. After reviewing the
available options of different PVC products for water and sewer construCtion, Vylon
PVC Sewer Pipe manufactured by Lamson Vylon Pipe, Cleveland, Ohio, was selected for
this evaluation program. The Vylon pipe provided suitable characteristics and eliminated
both of the major obstacles other PVC pipes experience when used for microtunneling,

that is, cost and suitable joint.

The Vylon pipe utilizes a new joint system developed by Lamson Vylon Pipe for
microtunneling. The joint provides a smooth outside and inside transition from one pipe
section to another, making the pipe suitable for microtunneling application. This
connection permits the pipe and joint system to mate up with the machine. Additionally,
and air-tight seal is formed at the joint with a multi-fin gasket wrapped around a

fiberglass insert ring. For economy, Vylon utilizes a profile wall. Vylon’s I-Beam design

/

40

reduces the amount of PVC required when compared to the same size solid-wall pipe, yet

maintains smooth surface inside and outside.

The pipe sections selected for use in the project were each 2.438 meters (8 feet) in length
and weighed approximately 29.76 kg/m (20 pounds per foot). The Vylon PVC sewer pipe
is manufactured according to ASTM F-794 for pipe requirements and ASTM D-3212 for
joint requirements. A special adapter was designed and manufactured by Iseki Poly-Tech
for the pipe/microtunneling machine connection. This connection provided the necessary
tolerance for the PVC jacking pipe and LLB propulsion system. This adapter was located
at the tail of the boring machine and provided the necessary tool to transfer face
resistance of the boring machine to the liner casing while the PVC pipe mated up with the

adapter.

2.4.4 Microtunneling Equipment

An Iseki Unclemole machine (TCC 500) was used for this program. The Iseki Unclemole
is a small-bore tunneling machine designed to meet the demand for a wide range of
ground conditions. This machine has an actual outside diameter (OD) of 655 mm (25.787
inches) and can construct a borehole equivalent to 660 mm (25.984 inches) in diameter.
The Unclemole is basically a mechanical earth pressure counter balance (MEPB) shield
that utilizes slurry to counterbalance hydrostatic head and to transport excavated material.
The Unclemole uses a unique built-in cone—shaped crusher to crush cobbles and gravel up
to 30 percent of the outside diameter of the shield into small particles for transportation

as slurry. Figure 2.18 illustrates the mechanism of the cone-shaped crusher.

41

 

Figure 2.17 — Cone-shaped Build-in Crusher (Herrenknecht 2000)

The Unclemole was modified to accommodate the LLB system and Lamson Vylone pipe.

The necessary microtunneling equipments were provided by Iseki Poly-Tech, including

boring machine, jacking equipment and guide rails, charging and discharging slurry

pumps with necessary pipes and hoses, laser transit, desandman, entrance ring, hydraulic

unit and control panel. The desandman is a slurry container which has a Vibratory screen

and hydrocyclone to separate slurry from spoil material. A list of equipment provided by

Iseki Poly-Tech for this evaluation program is provided in Table 2.9.

Table 2.8 —List of Microtunneling Equipment Provided for the Project (Najafi, 1996)

 

 

 

 

 

 

 

 

Net
Description Quantity Weight Size
(kg)
600 mm diameter, 2,390 mm
Tunnel Boring Machine, TCC-500 (LC) 1
length

1,040
Thrust Jacking Equipment, 3-Stage 1 Width 1,300 mm, Length 4,400
Molemeister, M3-150T—30 (I) m

 

42

 

Table 2.8 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Diameter 670 mm, Length 170
Load Meter 1
mm
Air Bleeding Valve, SAP02-000J l 29 x 14 x L53
Check Valve, S6AT-KI-0 l 28 x 24 x L80
Thrust Ring Assembly 1
Operation Board, B05-I, including Power Cables,
1 W1,000xH1,270xL700
Operation Cables and TV Cable 1,040
Power Pack, MP-7.5k-320 A 1
Straub Coupling, Connecting Pipes, Hydraulic
Hose, Power Cables, Operation Cables, Jack 1 set 80
Speed Cable
Diameter 646 mm, Length 630
Adapter Ring 1
mm
Diameter 640 nrrn, Len 950
Special Collar l gth
. mm
Pit By-Pass Unit, TRW-2 1 1,100
Entrance Ring , l
Slurry Pump, SC-28WES, 5.5 kw-4p l
Inventor Pump, SC-28WES 5.5 kw-4p 1
Flexible Hose 8
Distribution Boards, ELCB 200A, MCCB30A x A 2
3-100A and ELCB 200A, MCCB75A x 3 + 50A
Flow Meter, Pipe, Flexible Hose, Elbow Pipe,
1 set 270
Victualic Joint, etc.
Operation Cable, Laser Theodolite (LTL-ZODP), 1 210
Diagonal Eye Piece, Funnel Viscosimeter
PC Bar<D26x2.4m,SlurryPipes ZBxO/0x2m lset 1,100
Air Gripper, K211740 ((1)584 x L 2460) 3 2,550
Casing Pipe ((11595 x L 2460) 1 set 2,800
Spacer, Pipe, Connecting Pipe, etc. 1 set 110
Slurry Disposal Plant, Model: “Desandman” IM-2 1 6,370 465 x 231 x 3060 centimeters.

 

 

 

2.4.5 Other Equipments

The other equipment items utilized for the microtunneling operation were as follows:

43

1. A lO-ton crane for hoisting microtunneling equipment in and out of jacking pit
(the same crane was used to hoist pipe sections and liner casings);

2. An office trailer (to house the control panel);

3. An electric generator to provide required power for operation of the
microtunneling equipment (75 KVA, 200V/60HZ, three phase);

4. An air compressor to provide necessary air pressure to inflate gripper system (the
maximum air pressure needed was 7 kgf/cm2 or 100 psi);

5. An 11.35-cubic meter or 3000-gallon water truck to fill up desandman after slurry
discharge;

6. A 6-Cubic yard dump truck hauling spoils from spoil tank;

7. A welding and cutting equipment to install the steel framing, guide rails, entrance
ring, and miscellaneous welding and cutting works;

8. A backhoe CAT 225 DLC loading spoils from spoil tank to the truck (on part-
tirne basis to excavate drive and receiving pits and slurry pond);

9. A water pump (3 inch—gasoline operated, to pump underground and slurry water

from drive pit).

2.4.6 Labor Crews

The following manpower was necessary for installing the pipe and the evaluation
program. This manpower (except item 8 is for the data collection) is normally required
for a typical microtunneling project:

1. Microtunneling machine operator;

2. Crane operator;

3. Loader operator;

4. Truck drivers (2);

5. Technician;

6. Laborers (2);

7. Supervisor (for desandman operation, setting up laser, checking air gripper
installation and loadings, boring operation including connection and dismantling
of cables and hoses);

8. Data collectors (3).

2.4.7 Project Site Layout

The typical section layout of construction site for slurry type microtunneling has several
components. Two shafts are required for the microtunneling operation: a driving shaft
and a reCeption Shaft. A MTBM is set up on the guide rail of the jacking frame in the
driving shaft. The main jack pushes the machine, and excavation starts. After the machine
is pushed into the ground, the first segment of the pipe is lowered. As main jack pushes

the pipe, the MTBM simultaneously excavates soil (Ueki et al. 1999).

The site layout is a critical factor defining Simulation model, because it reflects the
resource cycle patterns of the project. Project site layout should allow adequate space for
microtunneling operation, ease of material delivery, and keep components of each
resource cycle in spatial adjacent manner to minimize time waste. The resource cycle
components include labor, material and equipment. At the project level, each resource is
usually involved in different cycles. The layout needs to consider multiple involved

resources and facilitate all resource cycles.

45

Adequate working space needs to be provided at the drive shaft to accommodate the
required equipment and materials for the microtunneling operation. The space
requirement is determined by the drive shaft size, which can range from 16 it by 33 ft to
50 ft by 100 ft, depending on pipe diameter and length and equipment dimensions.
Adequate working space typically would range from 20 it to 40 ft wide and from 75 ft to

150 ft long.

Typical microtunneling project layouts are from experience. -A small microtunneling
system can be arranged as Showing in Figure 2.19. Due to the location of the small
projects, which are usually in urban areas, the working space is constrained, epically on
longitude direction when construction is On roadway. The space constraints become a
critical issue when shafts are positioned along high traffic volume roads. In most cases,
only one traffic lane should be closed for microtunneling operation, which is one of

major advantages of microtunneling.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Pipe
.......... 81m $1 separatim adv-awe
.r I L_ { facilities "Wm _,
lPipe&Materials| > r ----------------------------- %
' Swag : a“ T —————— ‘::::::::—_:::
l __________ J 1‘ T New Cm, I.
decaooessfirdeliveryof

Figure 2.18 -Typical Layout for Small Microtunneling System (Abbott 2005)

In larger microtunneling projects, which commonly install large diameter pipelines in
inurbane areas, the space constrain is less an issue because of the location of projects and

larger equipment requirements. Figure 2.20 illustrates a typical larger microtunneling

46

project layout around driving shaft area. The construction site is accessible from two

sides, which reflects more delivery material needs.

Truck Access for Muck
Removal from Slurry
Separation Tanks

 

Slurry Separation Tanks

 

 

Pipe
advance

L1 { ”digitsuntrrq
[—

 

 

 

 

 

Crane > ---—-— ------

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Jacking pit
l' -------- l .
: Pipe & Materials I Control Cabin. and
I S I Shop Facrlrtres
. torage .
| I

<— Truck Access for
Delivering Pipes and
Materials

Figure 2.19 - Typical Layout for Large Microtunneling System (Abbott 2005)

In the project in Ruston, Louisiana, the microtunneling operation was conducted in a test
area on campus. Congestion was not a serious issue in such a test project as in urban area.
In order to generalize the simulation model, the site layout of the candidate project is
slightly modified to reflect common pattern of microtunneling operations. Figure 2.21

shows the site layout of the project.

Equipments’ lay out was next to the 58.52 meters (192 feet) long test bed on the
Louisiana Tech University campus. Driving and receiving shafts were located at both

ends of the test bed.

47

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2.5 Construction Simulation

2.5.1 Computer Simulation Overview

Computer simulation is a valuable management tool that is well suited to the study of
resource—driven processes. It gives the analyst an insight into resource interaction and
assists in identifying which factors in a problem domain are important. Simulation allows
the modeler to experiment with and evaluate different scenarios. Normally, such

experimentation and study would be too costly to be carried out in the real world.

Real world systems are so complex that some these systems are virtually impossible to
model and solve mathematically (Banks and Carson II, 1984). In these instances,
numerical and computer-based simulation can be used to imitate the behavior of the
system over time. A model is defined as a representation of a system for the purpose of
studying the system. Although Mihram and Miharam (1974) and many other
simulationists stated that it is not necessary to consider all the details of a system because
thereby a model is a substitute and a simplification of a system, the model should be
sufficiently detailed to permit valid conclusions to be drawn for the real system. The
Simulation model building process involves many steps. Problem formulation, setting up
of objectives, model design and building, data collection, programming and validation,
and implementation are the major steps. The art of modeling is enhanced by an ability to
abstract the essential features of a problem, to select and modify basic assumptions that

characterize the system, and enrich and elaborate the model until a useful approximation

49

results. However, the model complexity need not exceed that required to accomplish the

purpose for which the model is intended (Banks and Carson II, 1984).

Computer simulation is defined as the process of designing a mathematical-logical model
of a real world system and experimenting with the model on a computer (Pristker 1986).
Early simulation users were required to build a model by writing programming code,
mainly in FORTRAN, and experimenting by directly manipulating the computer
program. This was followed by the invention of simulation specific programming
environments where users write simulation specific code or access a provided function
library. “Modeling” is the term used to describe the process of specifying a given
simulation model. In the next phase of development, a host of systems were introduced
that allowed for alternative model development. This meant that modelers no longer had
to write code directly. Graphical modeling made it possible to define the simulation
model by creating, manipulating and linking a number of available basic building blocks.
This meant that users no longer had to be proficient in programming. A detailed account

of the history of simulation concepts and systems is detailed in Kreutzer (1986).

Computer simulation can be Classified as either deterministic or stochastic depending on
its uncertainty content (Wilson 1984). Since construction operations are subject to a wide
variety of fluctuations, changes, interruptions, and uncertainties, most simulation
applications use probabilistic simulation methods in simulating construction operations.
The input modeling, model. design, and output modeling are critical issues in simulation

modeling for any given situation. AbouRizk (1990) conducted in-depth research on

50

modeling input data for the simulation of construction operations. There are many
problems faced by the model designers and users when creating simulation models.
When a real system is converted into a simulation model, several logical assumptions are
applied. Sometimes these assumptions do not represent the correct nature of the real
system. Uncertainty and unpredictable events in a real system are usually modeled using
statistical distributions to reflect the actual occurrence of those events. A lack of
historical data and its applicability to a statistical distribution may fail to successfully
model such random events. Because of the high uncertainty involved in construction
operations and the unavailability of historical quantitative data, various researchers have
hypothesized the determination of activity durations for most construction operations.
AbouRizk et a1. (1994) divided certain input parameters for “certainty portions” and
“uncertainty portions” based on the uncertainty content of the input parameters:
deterministic analysis to estimate the certainty potion and probability and conceptual

analysis to estimate the uncertainty portion.

Construction simulation Can be of great assistance to decision makers in analyzing
various construction operations and alternatives. Simulation of construction operations
allows analysts and construction industry personnel to experiment with different
construction technologies, and estimate their possible consequences and impact on
scheduling and costs. Although simulation has been considered a very powerful tool for
construction, its application to real life construction projects has been minimal

(Ruwanpura 2001). The use Of computer simulation for planning construction projects

51

has been limited to academia and a few large contractors who can afford to employ

dedicated simulation professionals (Haj jar 1999).

2.5.2 Construction Simulation

Possibly due to the uniqueness of constructed facilities and the perceived lack of
repetition, the concept of studying work processes did not receive much attention until
the late 1960s. At this time, work sampling and various graphical techniques related to
bar Charting were considered. It was recognized that although projects are typically
unique, many construction processes are repetitive (e.g. earth hauling, tunneling, road
construction, glass installation on a tall building, etc.) and amenable to closer
investigation. Due to the comparatively short "half life" of construction processes,

sophisticated analytical methods were viewed as being too complex for most situations.

With the emergence of the desktop computer, application of more sophisticated methods
has become more accessible. In particular, simulation of construction processes to
establish anticipated levels of production and solve some of the problems related to the
randomness of construction operations has become a more widely accepted as a tool

available for use in planning and estimating.

Random number techniques to solve stochastic problems encountered in construction
have been used to establish ranges of expected cost (e. g. range estimating), evaluate
project time duration (PERT simulation), and model and evaluate expected production of
1 various construction processes. One of the earliest applications of random number

methods was in a gaming context. AI, Parti, and Bostleman developed a construction

52

bidding game in the late 603 which in Various configurations is still used at several

universities for teaching purposes (Au et a1, 1969).

Following this, the CONSTRUCTO project management game was developed at the
University of Illinois by Halpin to integrate the effects of weather and labor productivity
into the management of projects in a network format (Halpin, 1976). A similar simulation
was developed by Borcherding (1977) of the University of Texas. Recently, the concepts
of the bidding game and the project management format have been integrated into an
educational game (Superbid) by AbouRizk at the University of Alberta, Edmonton

(AbouRizk, 1992)

In order to be accepted in the construction environment, simulation has to be presented in
a very simple and graphical context. Contact with construction professionals indicates
that formats which appear to be too theoretical or analytical tend not to be accepted of
utilized. Therefore, ideally simulation systems should be pictorial of schematic
emphasizing graphical input and graphical output. The early systems designed to study

construction operations utilized simple bar Charting concepts.

With the advent of simulation methods in construction, simple networking concepts were
introduced as a modeling framework for studying construction operations. The earliest of
these methods was the so-called "link node" model adapted by Teicholz (1963). After
that, Halpin (1973) developed the CYCLONE format at the University of Illinois that has

become the basis for a number of construction simulation systems. CYCLONE simplified

53

the simulation modeling process and made it accessible to construction practitioners with

limited Simulation background.

2.5.3 Simulation Modeling

There are many ways of modeling a given problem and these generally fall into two
categories: continuous and discrete-event. Continuous or time-dependant algorithms are
often represented with a system of equations or mathematical models and then solved for
steady state performance using differentiation, integration, or approximation. In discrete
event simulation utilizes “next event processing” of activities based on logical
relationships between process components and availability of resources (AbouRizk,

1998)

Users can typically Change the behavior of a simulation model after it is constructed. This
is the concept of the reusability where the model can be used for a multitude of scenarios.
The degree to which users can change the pre-defined simulation behavior is dependent
on the development strategy utilized. Simulation systems can generally be classified
according to this feature as follows (Ulgen et a1, 1991):

1. Fully documented simulation models,

2. Parameterized simulation models,

3. Special purpose simulation program generators, and

4. General-purpose Simulation program generators.

With fully documented simulation models, users are required to modify the simulation

models by manipulating them at the same level used to originally develop them. This

54

assumes end users are knowledgeable with the way the simulation system works.
Parameterized simulation models allow for model re-use by exposing a set of parameters
that users can modify each time the model is simulated. The values of the parameters can
be used to modify routing strategies, resource values and entity attributes. With special-
purpose program generators (SPSPG), users are able to create models by selecting from a
list of available domain specific constructs and defining their parameter values as well as
their relation to other elements. Examples of such systems include WITNESS and
SIMFACTORY (Mathewson 1989), Ap2Earth (Hajjar et a1. 1998). The advantages of
special purpose simulation program generators are outlined in AbouRizk and Hajjar
(1998). General-purpose simulation program generators (GPSPG) are like SPSPG; only

expert users can add new modeling constructs to the system.

Halpin (1977) popularized the use of simulation in construction research with his
invention of a system called CYCLONE (CYCLiC Operation NEtwork). CYCLONE
allowed-the user to build models using a set of abstract but simple constructs. The system
became the basis for a wide range of construction simulation research efforts with the
objective of enhancing the basic system fimctionality and most construction simulation
work was motivated by the success of CYCLONE (AbouRizk, 1998). This included
MicroCYCLONE (Halpin, 1978), INSIGHT (Paulson et al., 1978), UM-CYCLONE
(Ioannou, 1989), and RESQUE (Chang and Carr 1987). STROBOSCOPE (Martinez and
Ioannou, 1994) was another development based on CYCLONE which allowed for

dynamic simulations based on the definition of entity and resource attributes using

55

programming - like syntax. DISCO (Huang et al., 1994) developed to allow the use of

graphical-based modeling for CYCLONE models.

Simphony is another simulation platform for building general and special purpose
simulation tools, which was developed in the University of Alberta. It is a Microsoft
3 Windows based computer system developed with the objective of proViding a standard,
consistent, and intelligent environment for both the development and utilization of special
purpose simulation (SPS) tools (Hajjar and AbouRizk, 1999). AbouRizk and Hajjar
(1998) also defined SPS as “a computer-based environment built to enable a practitioner
who is knowledgeable in a given domain, but not necessarily in simulation, to model a
project within that domain in a manner where symbolic representations, navigation
schemes within the environment, creation of model specifications, and reporting are
completed in a format native to the domain itself” A detailed introduction can be found

in Hajjar and AbouRizk (1999).

MicroCYCLONE is chosen as the base for this simulation study, due to the accessibility
and ease of use. Specifically, a web based version of MicroCYCLONE, namely,
WebCYCLONE maintained by Purdue University is used to run simulations. The use of
WebCYCLONE requires coding of the model in a format set by MicroCYCLONE and
upload to the website. The interface of WebCYCLONE is shown in Figure 2.22.
MicroCYCLONE is a microcomputer based simulation program designed specially for
modeling and analyzing site level processes which are cyclic in nature. In broader terms,

it can be used to model construction operations which involves the interaction of tasks

56

with their related durations, and the resource unit flow routes through the work tasks are

the basic rationale for the modeling of construction operations.

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‘. Compile I uTJacaRunfj _Runw/and.lnio I Run 1

 

 

 

Figure 2.21 -A glance at WebCYCLONE User Interface

2.5.4 Tunneling and Microtunneling Simulation Tools and Applications

Similarities exist between tunneling and microtunneling construction methods.
Microtlmneling is considered as tunneling with special features (ASCE, 2001). As having
much longer history, researches have been approached on all aspects of tunneling. The
significant amount of previous tunneling simulation projects can nourish the development

of microtimneling simulation, which is rarely found.

57

In general, the term “tunneling” can be used to describe a wide range of underground
excavation operations. Tunnels can be used to serve a variety of functions, including
subways, utility corridors, and sewer lines. Tunnel construction projects are particularly
suitable for simulation due to the many repetitive construction cycles that occur during
construction. Simulating the process of tunnel advancement can guide the engineers,
planners, and constructors to plan and control the project more efficiently. It is generally
accepted that tunneling projects are typically high-risk. Successful project planning can

save both cost and time, resulting in a productive tunnel construction project

(Ruwanpura, 2001 ).

Touran and Asai (1988) predicted the tunnel advance rate in the construction of a several-
mile-long, small-diameter tunnel in soft rock using CYCLONE. Tanaka (1993) presented
a tunnel simulation using CYCLONE for shielded tunnel boring machines. AbouRizk et
a1. (1997) applied tunnel simulation using Visual SLAM to analyze the productivity of
construction activities for a tunnel constructed under a river to validate a productivity
claim. Olufa et al. (unpublished) presented a library-based simulation modeling
development with an implementation in shielded tunnel construction projects in
University of Alberta. They used an object-oriented simulation programming language
called MODSIM to simulate the tunneling projects. Salazar (1987) presented a simulation
model based on the eVent scheduling approach to generate probabilistic descriptions of
the advance rate of tunnel excavation and the corresponding demand for resources. It
used linked lists to dynamically schedule construction activities as the excavation takes

place through difficult ground conditions and provided two case studies comparing two

58

tunneling methods to illustrate the model. Abd Al—Jalil (1998) developed a decision
support system- Decision Aids in Tunneling (DAT) to predict the performance of Tunnel
Boring Machine (TBM) based excavation systems in hard rock geological conditions.
These tunnel simulation models have catered to particular situations and cannot be used

for other types of tunnel or microtunnel construction projects.

Ruwanpura et al. (2000b and 2000c) discussed the independent studies conducted by two
graduate students Hajjar (1997) and Ruwanpura (1998) of the University of Alberta as
part of their course work, to model TBM-based tunnel construction using Visual SLAM
(Pritskar 1994). However, both models were not flexible enough to model for any given
tunnel construction project using a TBM, and were not validated using a constructiOn
project. In both cases, they concluded that simulation could be a very useful tool for
project planning. As an improvement, Ruwanpura (2001) developed a Special purpose
simulation (SPS) template for tunnel construction operation, which included a modeling
technique to predict the soil types in the tunnel path in City of Edmonton, Alberta,
Canada. The prediction of soil types in the tunnel path was realized by using Markov

Chain probabilistic theory on historical geological bore data from City of Edmonton.

Research on microtunneling using simulation is very limited. Nido et al. (1999) simulated
an actual rrricrotunneling project in Montgomery COunty, Ohio, using CYCLONE
methodology. The analysis highlighted the impact of variations in soil compositions on
the productivity of the operation and on the utilization of labor resources. The project

selected for Simulation used centrifugally cast fiberglass mortar pipes, which is

59

significantly more expensive than PVC pipe used in the Louisiana Tech University LLB
Microtunneling Field Test Project. Since the pipe cost constitutes a big portion of
microtunneling cost, the effect on cost reduction by using PVC pipe is one of the goals of
this simulation research. Nido et al. selected an actual microtunneling project with
predominantly variety of clays encountered along the path, based on which simulation
was conducted to analyze the impact of variations in soil compositions on the
productivity. The soil compositions were limited by the actual geological conditions on
the job site; therefore, the simulation could not reveal potential impacts of a wide range
of soil conditions. However, in the Louisiana Tech University LLB Microtunneling Field
Test Project, to simulate soil materials mostly encountered in real situation, samples of
sand, Clay, silt, and gravel were selected artificially. Although encountering such a soil
variety would probably be rare in actual practice for a single microtunneling operation, it
was assumed that the results of the microtunneling test could be used for similar types of
soils so that the performance of the LLB system could be predicted for different
subsurface conditions (Najafi, 1993). This feature of the data collected will enhance the

simulation analysis.

2.6 Summary of Literature Review

The literature review in this Chapter indicates that simulation can be used for study on the
productivity of cyclic microturmeling operation. Backgrounds and elements need for an
Operational simulation on microtunneling have been reviewed. Various aspects of
microtunneling methods in general and the candidate project in specific were descried in
details. The possibility of the application of CYCLONE simulation on microtunneling

was discussed. Also, pipe materials used in microtunneling and soil condition

60

Classifications were documented to develop a broad-based understanding of the method.
The literature review indicates that there is a good possibility to develop a succeszul
CYCLONE model if the microtunneling operation procedures are well understood. In
following chapters, simulation models will be developed based on operation procedure

and duration data analysis.

61

3 CYCLONE METHODOLOGY AND APPLICATION

Previous chapters dealt with the literature review that gave the necessary background for
pursuing this thesis. This chapter presents the methodology used in this research for
microtunneling productivity analysis. The productivity simulation models are built with
CYCLONE (C YCLic Operations NEtwork) techniques. A detailed description of

CYCLONE methodology is presented in this chapter, along with the model development.

3.1 Cyclone Methodology

For the analysis of the microtunneling operation productivity of the candidate project,
Web-Cyclone, a web-based Simulation program that is based on the CYCLONE
methodology, was selected for modeling and simulation of the process. The CYCLONE
(CYCLic Operations NEtwork) methodology is a modeling technique that allows the
graphical representation and simulation of discrete systems that deals with deterministic
or stochastic variables. Construction processes simulation using the CYCLONE
methodology, abstracts the reality into a graphical representation'by dividing the process
into discrete pieces or work task and by representing how these interact. It focuses on
resources and their interactions. The purpose and ideal objective of computer simulation
is to optimize system performance, in the thesis research, is to study to improve and

estimate microtunneling productivity.

Steps involved in CYCLONE simulation are:
0 Defining the system (well defined boundaries)

0 Modeling the system (system of equations, graphical modeling) .

62

0 Input & Output Analysis

0 . Validation/Verification

To define the Network model:
0 Define work task composing a process
0 Establish logical relationship between the work tasks
0 Work task use resources and require time to be completed, this fact is
accounted into the model by supposing that entities flow thorough the
network, are delayed by work tasks, wait for processing, etc. When they are
served (or used) by each work task they continue flowing through the

network.

The basic modeling elements used in the CYCLONE methodology are shown in Table
3.1. The precedence rules of CYCLONE elements are shown in Table 32 Resources can
be in one of two states — active (denoted by a square element) or idle (represented by a
circle element). Resources will move between these two states, as they “traverse” from
one activity to another. A flow unit traverses a CYCLONE network with the following
effects:

0 Waits in QUEUE nodes for processing

0 Initiates (or signal) the processing of a work task

0 Generate other entities where they traverse a QUEUE-GEN node

. Get consolidated with other flow units when they pass a CONSOLIDATE

Function

63

0 Register productions where they pass a function COUNTER

Table 3.1 —CYCLONE Modeling Elements (Division of Construction Engineering and Management
Simulation Homepage, Purdue University, 2005)

 

Name

Symbol

Function

 

Combination (COMBI) Activity

 

 

 

 

This element is always preceded
by Queue Nodes. Before it can
commence, units must be
available at each of the preceding
Queue Nodes. If units are
available, they are combined and
processed through the activity. If
units are available at some but not
all of the preceding Queue Nodes,
theSe units are delayed until the

condition for combination is met.

 

Normal Activity

 

 

 

 

This is an activity similar to the
COMBI. However, units arriving
at this element begin processing

immediately and are not delayed.

 

Queue Node

This element precedes all
COMBI activities and provides a
location at which units are
delayed pending combination.
Delay statistics are measured at

this element.

 

Function Node

It is inserted into the model to
perform special function such as
counting, consolidation, marking,

and statistic collection.

 

It is used to define the number of

 

 

I‘v. .

Accumulator times the system cycles.
Indicates the logical structure of
Arc the model and direction of entity

 

 

flow.

 

64

 

Table 3.2 —CYCLONE Elements Precedence Table (Division of Construction Engineering and
Management Simulation Homepage, Purdue University, 2005)

 

 

 

 

 

 

 

 

 

- Q Q P

 

 

 

 

 

 

 

 

 

 

 

 

Q M N N N N
O

 

 

P N 1 I 1 N

 

 

 

 

 

 

M = required or mandatory
0 I = immaterial
o N = nonfeasible

Active states or work tasks can either be unconstrained (NORMAL modeling element —
represented by a rectangle) or constrained (i.e., certain initial conditions must be
satisfied). The constrained active states are named COMBI (depicted by a hatched
rectangle) modeling elements. “The NORMAL and COMBI work tasks have user-
defined time delay functions that represent the time period during which resource entities
are delayed while processing through these work tasks. The idle state represented by the
QUEUE node, has the potential for storing in a waiting state or queue format the resource
entities held up by system requirements pending the satisfaction of COMBI work task

ingredients or initializing logic” (Halpin et al., 1992). The sequence of work tasks

65

 

undertaken by the resource entities together with their idle states indicates the level of the

use of resource.

Two basic resource flow patterns are commonly used. The slave entity pattern is
produced whenever a resource entity is used by a single active work task, such that the
resource entity cycles between the active state and the idle state. When a resource entity
is Shared between two or more work tasks, the resulting flow pattern is called a butterfly
pattern. In such cases, Once the resource entity is in the idle state, its subsequent active
work state may depend on other factors, such as the availability of other resources, the
priority system adopted for the work tasks in the construction operation, etc. Units can be
generated into the system by defining a GENERATE fimction (abbreviated as GEN)
which is associated with a selected QUEUE node. When a work task is initiated after a
specified number of cycles of the system or system subcomponent, a CONSOLIDATE
function (abbreviated as CON) is defined. The GENERATE function is a discrete event
multiplier, while the CONSOLIDATE function can be considered a discrete event

divider.

3.2 Microtunneling Operation Procedures

The microtunneling procedures for the simulation candidate project are as follows:
1. Excavate and prepare the driving shaft.
2. Set up the control container and any other auxiliary equipment beside the
jacking shaft.

3. Set up the jacking frame and the hydraulic jacks.

66

4. Lower the MTBM (Unclemole) into the driving shaft and set it up on the
guide rails.

5. Set up laser guidance system.

6. Set up the slurry lines and hydraulic hoses on the MTBM as illustrated in

Figure 3.1.

‘ . r“TIT f
» . ~ sf
,. “1
.. _ a? ‘ ‘ '7 ‘1 I
‘QM 7' '
“a. m

3‘
it '
"a“ a.

I,

o... _ ' .i . .-_
._'.'_ "‘» -
Hoses Connected
‘ (I i — A}, ~ :. ‘.

i
I
H
'I
g-

{is
g
. , . . , ‘w‘ x ,-
. ». r_ ‘-.
E Slurry , . ' ‘

Communicatlons

ti
.1 Slurry
_. Charge . .1

J.

ischarge
ms. ._ ; 1. m
..

 

 

Figure 3.1 - Slurry Lines and Hydraulic Hoses (Najafi, 2005)

7. The main jack pushes the MTBM.

8. After the MTBM is pushed into the ground, the slurry lines and hydraulic
hoses are disconnected from the jacked section (or MTBM).

9. The hydraulic jacks are retracted.

10. A new pipe section is brought from the storage and liner casing with two
slurry steel pipes, air hose and cables are placed inside the pipe as shown in
Figure 3.2. Air grippers are installed on certain sections as shown in Figure

3.3.

67

 

1

Figure 3.2 -Inside View of PVC Pipe Showing Liner Casing, Slurry Pipes, Bentonite Hoses and Cables
(Najafi 1993)

 

Figure 3.3 — Air Gripper Used in the Project (Najafi 1993)

11. The pipe section is attached to crane and lowered into the driving shaft as

shown in Figure 3.4.

68

 

Figure 3.4 — Lower Pipe Section into Driving Shaft (Najafi 1993)

12. Connect the slurry lines and hydraulic hoses in the new pipe segment to the
ones in the previously jacked segment (or MTBM).
13. Jack the new pipe section, while removing the spoil, adding lubrication, and

filling water as shown in Figure 3.5.

 

Figure 3.5 — PVC Pipe Joint Being Pushed in (Najafi 1993)

14. Excavate and prepare the receiving shaft.

69

15. Repeat step 8 to 12 as required until the pipeline is installed. The CYCLONE
simulation model will be built based on this cyclic process.
16. Remove the MTBM through the receiving shalt. Figure 3.6 illustrates the

MTBM entering the receiving shaft.

 

Figure 3.6 - MTBM at the receiving shalt (Kerr Construction Inc.)

17. Remove jacking frame and other equipment from the driving shaft.
I 18. Grout the annular space between the exterior pipe surface and the tunnel.
19. In case of sewer applications, install manholes at the shaft locations.

20. Remove shoring, lining, or casing from the shaft and backfill them.

The major procedures in the candidate project are also applied in slurry type
microtunneling in general. Therefore, possibility exists that the simulation model based
on the specific project can be generalized to other slurry type microtunneling projects

with modification.

70

Microtunneling is a complex operation process, which includes multiple types of resource
cycling and interacting in the overall system. Due to the limited supply of resources,
interactions between various resource cycles create the major limitation on productivity
of microtunneling operation. To optimize the productivity, single resource cycles must
be modeled first and integrated with the logic among them to truly reflect the
microtunneling operation. On the both levels of modeling, the CYCLONE model
building procedure need to be followed, which involves four basic steps:

1. Define resources;

'2. Identify work tasks in the process (work tasks with which resources are

involved);
3. Determine the logic of the processing of resources;

4. Build a model of the process.

The next section will follow the four steps to identify flow units and resources in each

resource cycles.

3.3 Flow Unit and Recourses Identification

The resource identification stage is extremely important since it will dictate the degree of
detail of the finished model. In order to portray the resources in the model, important
activity duration information must be measured in the field. The most important
resources were identified as the following: the pipe sections, the jacking system, two
labor crews (called Labor A and Labor B), the lubrication mixture, the water in the spoil
removal system and the spoil that was removed from the borehole (these resources will

be called leading resources thereafter). Other resources were identified, but they were

71

considered as secondary resources, these included construction equipment such as
backhoe, crane, dump trucks, water truck, air grippers for the PVC pipes, and the

ingredients for the lubrication (bentonite and polymer).

The most important resource in the system is the pipe section. A pipe section is defined
as a 8 feet long section of PVC sewer pipe. The pipe sections are brought to the site and
are placed on a storage place showing on Figure 3.1, as they are unloaded from the truck.
When needed, the Labor A rolls one section to the base of the crane where it will be
prepared for installation. This preparation includes the placing of a liner casing with two
slurry steel pipes, air hoses and cables inside the PVC pipe Section. Air grippers need to
be installed on every four sections. Then, the prepared section will be attached to the
crane and lifted, lowered into the shaft and laid on the guardrail. Labor B crew sets up the
pipe for installation. The setup activity includes installing slurry pipes, air hose and
cables, joining the thrust ring with the liner casing and the PVC pipe, and installing laser
guidance. Once the pipe has been set up, the jacking of the section may begin. After the
pipe section has been fully jacked, slurry lines and the hydraulic lines may be dismantled.
At this point, one production cycle is complete. For the models developed in this study,
the production unit was defined as the jacking of one 8 feet long section of PVC sewer
pipe. The installation of each section was deemed to be completed after the slurry and
hydraulic lines have been dismantled from the jacked section. Figure 3.1 illustrates the

resource cycle for pipe section.

72

Air gripper installation as a secondary resource is required on certain pipe sections in the
preparation activity. Due to the material characteristic of PVC pipe used in the project,
air grippers have to be installed on some pipe sections for the air hoses in order to adapt
the PVC pipe to the microtunneling system. The project used air grippers on section
number 4, 9, and 14 in 24 sections installed, which was based on the engineer’s
experience. Assumption is made to model air gripper installation on every 5 sections.
Based on the notes in Appendix B, after installations, approximately 67% of times the air
grippers are ready to use, and 33% of times it needs to be adjusted, which occupies
resources (Labor A, Supervisor) for certain time. Fig. 3.8 illustrates the air gripper

installation on the pipe section that is necessary.

 
    

     
 
 

 

 

  

POSITION
OCCUPIED

/ . .
Bnng section from ‘
storage& prepare

SECTION ON

/ .
Dismantle cables STORAGE

 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

and hoses
/ .
SECTION IN Attach section to
PLACE crane
Jack pipe Lift section to
section position '
fipe section setup SECTION firwer section into SECTION
on guard rail READY shaft READY

 

 

 

 

 

 

Figure 3.7 —Pipe Section Resource Cycle

73

 

 

 

 

 

 

 

 

 

 

 

 
   
   
 

 

 

 

 

 

 

. . /
Egg): 2633153; Assessments
. g . crane
liner casmg
NEED AIR /|nsta|| and check P=0.67 AIR GRIPPER
GRIPPER air gripper QADY
P=0.33
Adjust air
gfipper

 

 

 

Figure 3.8 - Air Adaptor Installation on Pipe Section Resource Cycle

The jacking system is another leading resource; its cycle is shown in Figure 3.9. The
jacking process is the main component of the microtunneling operation. The cycle begins
when jacking flame completely retracted and ready to accept a pipe section, this state is
called jacking system idle. After a pipe section is setup then the jacking system “jacks”
(or pushes) the pipe. After the jacking pipe takes place then the slurry and hydraulic lines
are dismantled and jack flames are retracted once again ready to begin another cycle. The
jacking system consists of: the jacking flame, one worker who is always inSide the shaft
cleaning and observing the jacks, the MTBM and its operator who also controls the jacks,
the spoil separation unit. Production unit was defined as jacking system went through one

cycle flom retracted status to next retracted status.

74

 
 
 

 

 

fipe section setup Jack pipe

   

Jacking

 

 

 

 

 

  

 

 

 

system idle on guard rail section
/.
DIsmantIe cables , SECTION
and hoses READY

 

 

 

Figure 3.9 -Jacking System Resource Cycle

The “Labor A” resource is defined as a one-worker crew. This worker is assigned to
various activities as shown in Figure 3.10. This worker does not directly interact with the
jacking system cycle since he does not perform any jacking related activity. This worker
is involved in the mixing of the lubrication, attachingthe pipe section to the crane and

preparing the section for installation.

 

 

 

 

 

 

 

 

 

 

 

 

 

Bring section from /Attach section to
storage & install crane
liner casing
LABOR A - - -
IDLE MIX lubrIcatIon
/lnstall and Check / , , ,
air gripper Adjust aIr ngpper

 

 

 

 

 

 

Figure 3.10 —Labor A Resource Cycle

The next resource is called “Labor B”. Labor B is defined as a two-worker crew with one

labor and one technician, who are involved mainly in jacking related activities like setting

75

up the pipe in the shaft, dismantling the slurry and hydraulic lines and lowering the
section into the shaft. This crew is also involved in the task of discharging and refilling

the desandman (Figure 3.11). The crew members have to work together.

 

 

{ower section into ape section setup
shaft on guard rail

  
  

 

 

 

 

 

 

 

 

Discharge and Dismantle cables
refill desandman and hoses

 

 

 

 

 

 

Figure 3.11 —Labor B Resource Cycle

The lubrication cycle (Figure 3.12), starts with the lubrication in its storage tank. This
resource is used to set up the pipe in the jacking flame. It is also required through the
entire jacking process until the slurry lines and hydraulic lines are dismantled. After five
cycles, the lubrication is consumed and more is needed, so the ingredients (polymer
liquid, bentonite powder and water) must be mixed in the mixing tank and then stored.

The flow unit is defined as one lubricatiOn mix process is finished and ready for use.

76-

 

The slurry (water based) in the system is a very important resource, as shown in Figure

3.13. Slurry is needed in all phases of the jacking process, flom the setting up of the pipe,

 

/

 

Pipe section setup
on guard rail

 

 

 

 

 

/

Mix lubrication

 

 

 

Figure 3.12 —Lubrication Resource Cycle

 

JaCk pipe
section

 

 

 

through the jacking itself until the slurry and hydraulic lines are dismantled. Slurry can be

recirculated through the system only a certain number of times, which is a function of the

composition of the soil being ,exCavated. The flow unit is one time of discharging the

desandman and refilling water for use.

WATER
READY

During the pipe jacking process spoil is removed through the slurry return lines in the

 

4

 

 

 

 

 

 

refill desandman

 

 

 

 

 

 

ipe section setup Jack pipe
on guard rail section
/Discharge and

 
  
     

READY TO
DISCHARGE

Figure 3.13 —Water Resource Cycle

  

     
 

SECTION IN
PLACE

 

 

/Dismantle cables
and hoses

 

 

 

form of a slurry suspension (Figure 2.7). It is then separated flom the water and dumped

77

into the storage tank before it is loaded into dump trucks for hauling to disposal sites, as

depicted in Figure 3.14. Flow unit is the spoil tank is emptied once.

   

 

 

SPOIL TANK flpe section setup Jack pipe
NOT FULL on guard rail section

 

 

 

 

 

 

 

   
   

 

/
Empty spoil tank

SPOIL TANK
FULL

 

 

 

I Figure 3.14 —Spoil Cycle

After leading resource cycles have been defined, secondary resources need to be
identified. One of them is the supervision provided by Kidoh staff flom Osaka, who is
responsible for Checking air gripper installation, pipe section setup on guardrail including
laser setup and connection of cables and hoses, desandman operation, and dismantling
cables and hoses. Figure 3.15 shows the resource cycle of supervision. One supervisor is
asSumed and he must be available at the beginning of each activity which need to be

supervised. The supervisor can only present at one activity a time.

78

 

 

/lnstall and Check
air gripper

 

 

 

 

Discharge and
refill desandman

 
 

 

 

 

/

 

 

Adjust air gripper

 

 

  
 

 

Pipe section setup

on guard rail

 

 

 

 

/Dismantle cables .
and hoses

 

 

Figure 3.15 — Supervisor Resource Cycle

The crane cycle is another secondary resource cycle, as shown in Figure 3.16, the crane

returns when pipe section is setup on guardrail, and ready to be attached next pipe

section. Flow unit is defined as a cycle that flom attaching pipe to crane idle'completes.

 

 

. CRANE IDLE
/

 

 

 

 

 

Lift section to
position

 

 

 

L SECTION
READY

Figure 3.16 - Crane Resource Cycle

 

-I Crane returns _‘

 

 

 

 

/

Lower section into
shaft

 

 

-\

\

\

 

SECTION /

READY

 

Pipe section setup

 

on guard rail

 

There are other secondary resources not forming independent cycles, such as backhoe,

crane, dump trucks, water truck, and the ingredients for the lubrication. Those secondary

resources will be included in next section of integrating independent resource cycles into

one microtunneling simulation model.

79

3.4 Integration of Independent Resource Cycles

The second step in building the model is the integration of the independent resource
cycles. When all the flow unit cycles have been identified, they can be integrated at the
COMBIS for development of the comprehensive process model. Those COMBIS that
appear in different resource cycles will be joints on the comprehensive process model
connecting the independent resource cycles. Such a model structure reflects logic nature
behind the operation process. For instance, COMBI Pipe Section Setup on Guard Rail
appears in eight independent resource cycles. Resources including pipe section, labor B,
supervisor, water, lubrication, spoil tank, jacking system, cables, hoses, and laser must be

ready before pipe section can be setup on guard rail.

Basically we need the following information in order to simulate the actual process:

1. When can a work task be scheduled to start?
2. What resources are necessary for its processing?

_3. Time consumed by processing the resource

Item 1 and 2 are discussed in this section, which explains the structure and logic of the
model. Time consumed by processing the resource will be studied in chapter 4, Statistical

Analysis of Observed Duration Data.

Figures 3.17 and 3.18 present the complete prototype CYCLONE model for
microtunneling operation without consideration of soil impacts. The purpose of this

prototype model is for validation of the modeling structure and logics. Alter building and

80

validating this prototype model, enhancements of different soil composition impacts will

be included in next section.

The complete description of the prototype simulation model elements is shown in Table

3.3 to 3.6.

Figure 3.17 —Combination Elements in Prototype Model

COMBI elements

Element number (Priority) Description

1 Discharge and refill desandman

 

 

 

lMix lubrication

 

Disrrrantle cables and hoses

 

Empty spoil tank (desandman)

 

Setup pipe sectiOn on guard rail

 

Lower section into Shaft

 

Adjust air gripper

 

Install and check air gripper

 

2
3
4
5
6
7
8
9

Attach section to crane

 

 

Bring section flom storage and install liner casing

 

In order to prioritize activities sharing the same resource, thorough analysis has been
conducted to follow the microtunneling practice. In CYCLONE modeling, lower
ntunbered COMBI elements receive priority (Halpin et al. 1998). For example, resource
Labor A is responsible for five activities in priority of: Mix lubrication, Adjust air
gripper, Install and check air gripper, Attach section to crane, and Bring section from
storage and install liner casing. Slurry is ranked first because it is the most important
among five, without lubrication the operation could be jeopardized and fail. Other four

activities are prioritized following a general rule: later positioned activity in the cycle

81

takes higher priority. The logic of the rule is that there is only one situation later and
earlier positioned activities fight for the resource: later activity deals with previous pipe
section while the early activity deals with next pipe section. For instance, Bring section
from storage and install liner casing must happen before Attach section to crane, but
they share resource Labor A, which means normally two activities won’t occupy Labor A
simultaneously. However, the only possibility comes when Labor A is to attach pipe
section to crane, the next section need to be brought and prepared. Obviously, Labor A
should attach section to crane first in order to keep the whole operation running and come
back to bring more sections and prepare. Thus, if any two of these activities need Labor
A at the same time, higher numbered activity has to wait for lower numbered activity

finish and release Labor A to idle status.

82

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2.2301 ”:90

     

=.

/|\

84

Figure 3.18 — Queue Elements in Prototype Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

QUEUE elements
Element number Description Generate

11 Section on storage N/A
12 lPosition available N/A
13 Labor A idle N/A
14 Supervisor idle N/A
15 Air gripper ready 5

l6 Crane idle N/A
17 Crane control N/A
18 Labor B idle N/A
19 Truck idle N/A
20 lBackhoe idle N/A
21 Lubrication ready N/A
22 Bentonite ready N/A
23 Jacking system idle N/A
24 Water ready 4

25 Need air gripper N/A
26 Air gripper need adjust N/A
27 Spoil tank not full 4

28 Position occupied N/A
29 Section ready N/A
30 Section ready N/A
31 Spoil tank full 4

32 Need slurry N/A
33 Desandman ready to be discharged N/A
34 Section in place N/A
35 Cables, hoses, and laser ready N/A

 

85

 

Figure 3.19 —Function Elements in Prototype Model

FUNCTION elements

Element number Description

 

 

36 CON 5
37 CON 4
38 CON 4
39 CON 4
99 COUNTER

 

 

 

 

 

 

 

Number generated by QUEUE element is multiplying resource units exit after one unit
enters the QUEUE. Consolidate is the number to be consolidated before the entity exits
this node. If combined on one flow route, consolidate and generate can model regularly
happened activities. For example, when Jack pipe section is finished, one unit is released
to fimction node 37 to consolidate 4, which will stay in the function node until four pipe
sections are jacked and lubrication need to be added. Then, the four consolidated units
trigger one time of mixing lubrication. After lubrication ready, the QUEUE node
generates four units available for Pipe section setup on guard rail, which will provide

adequate lubrication for next four pipe sections.

Figure 3.20 — Normal Elements in Prototype Model

    

NORMAL elements

Element number Description

 

 

4O Lift section to position

 

41 Crane returns

 

42 Jack pipe section

 

43 DUMMY

 

86

3.5 Resources Initialization

After building the model, in order to perform the simulation, the resources must be
initialized. This is the third step of the model building process. Table 3.7 provides the
information regarding initialization for all the resources. The resources have been
initialized such that at the beginning of the simulation all the pipe sections are on the
storage, the crane is available, supervisor, crew Labor A and B are flee, air gripper is not
needed for the first four sections, trucks and backhoe are flee, spoil tank, water, and
lubrication are ready for the first four sections, bentonite is ready to make lubrication,
jacking system, cables, hoses, and laser are ready. Hence before the jacking begins, a
section must be brought flom storage and prepared, lowered into the Shaft, and finally set

up on the jacking flame.

87

Figure 3.21 —Resource Initialization

Resource Initialization

 

Description

Quantity

 

Section on storage

30

Pipe section

 

Position available

1

Position

 

Labor A idle

1

Labor

 

Superintendent idle

Supervisor

 

Air gripper ready

Signal

 

Crane idle

Crane

 

Crane control

Signal

 

Labor B idle

Labor

 

Truck idle

Truck

 

Backhoe idle

Backhoe

 

Lubrication ready

Signal

 

Bentonite ready

Bentonite

 

Jacking system idle

Jacking system

 

Water ready

Signal

 

Spoil tank not full

Signal

 

Cables, hoses, and laser ready

 

 

 

 

3.6 Modeling Assumptions

‘ Certain assumptions were made in order to build this prototype model. These
assumptions are as follows: i
o The manner in which the resources have been initialized assumes that at the
beginning of the simulation all pipe sections are on the storage, therefore the
driving shaft is empty.
0 One complete production cycle is finished after one pipe section (8 feet long)
is fully jacked, the slurry and hydraulic lines have been dismantled flom that

section and the jacking flame is fully retracted.

88

Labor A (l-labor crew) and labor B (l labor and 1 technician crew) work
independently.

One tank of mixed lubrication lasts for the duration of the jacking of four pipe
sections (CON 4, node 37).

The spoil tank must be emptied after tunneling for 4 consecutive pipe sections
(CON 4, node 38) averagely in four types of soil conditions.

The water in the system must be Changed after tunneling for 4 consecutiVe
pipe sections (CON 4, node 39) averagely in four types of soil conditions.

The air gripper must be installed on every five pipe sections. It is checked for
and must be adjusted 33% (P = 0.33 between node 43 and 26) of the times it is
checked.

The time required to retract the jacks is included in the slurry and hydraulic
lines dismantling activity (COMBI node 3).

The time required to set up laser is included in the pipe section setting up
activity (COMBI node 5); the time required to take off laser is included in the
slurry and hydraulic lines dismantling activity (COMBI node 3).

Before the setting up of a pipe section in the shaft can take place the following
tasks must be finished (in order of priority): Changing the water in the system
(if necessary), mixing of lubrication (if necessary), slurry and hydraulic must
be dismantled flom the previous section, jacks must be retracted, laser must
taken off, and the Labor B crew must be available.

MTBM breakdown and obstruction that may halt the operation are not

‘ considered.

89

3.7 Model Enhancement with Soil Composition Changes

After the building of a prototype model, duration data for activities was analyzed to find
distributions for the simulation, which is discussed in Chapter 4. The model was coded
with duration distributions and loaded onto WebCYCLONE for simulation. The results
were compared with observed productivity for validation in Chapter 5. The simulation
results were satisfactory, which means the structure and logic of the prototype model was

valid for enhancements with soil composition Changes.

Enhancements to include changes in the operation due to different soil composition are
introduced as shown in Figure 3.19 and 3.20. Three enhancements were included. After
pipe section is setup on guard rail, a dummy activity was introduced to split the flow unit
into four ways according to probability on each route. Four routes represent four types of
soils used in the candidate project. The probability of each route is set equally to 0.25,
because the testing bed was constructed of four segments of different soils with the same
length. By changing the probabilities on each ’ route, various combination of soil
compositions can be simulated to find the correlation between productivity and soil
condition, which will be discussed in Chapter 6. The second enhancement will be

presented in Chapter 4, which is finding the different duration time distribution in four

types of soils.

The other change was on the water resource cycle. Because the slurry pump used in the
candidate project was not compatible of handling Clay soil, the desandman was

discharged more flequent when pipe in Clay soil, which is reflected in the model

90

structure. The desandman need to be discharged every two pipe sections jacked in clay
soil, while every six pipe sections jacked in other three kinds of soils. The average times

of discharging desandman remains six in 24 pipe sections installation.

To match the structure of changed consolidate nodes, QUEUE Water Ready (node 24) is
no longer generate 4 units as in the prototype model. Instead, after dismantling cables and
hoses in any type of soils, one unit flows to QUEUE Water Ready (node 24) and Con 2
or Corr 3. Before certain number is consolidated, the COMBI Discharge and Refill
Desandman (node 1) will not be triggered, so the QUEUE Water Ready (node 24)
provides unit for COMBI (node 5) Pipe Section Setup on Guard Rail for jacking activity.
Once the consolidation reaches the preset number, one unit will be released to trigger
COMBI Discharge and Refill Desandman (node 1). Because of the dual direction of unit
flow between QUEUE (node 24) and COMBI (node 1) and higher priority of COMBI
(node 1), any unit in QUEUE (node 24) Water Ready will flow back to COMBI (node 1)
to discharge and refill desandman and put COMBI (node 5) Pipe Section Setup on wait
until desandman is ready. This structure change models the water resource cycle in

different soils.

91

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92

 

 
   
 

 

 

 

 

  

 

 
   
   
   

 

,’\
l I R Control Crane ‘
(62)
Backhoe \\ ,-\‘
Idle '83;
' I' \
SPOIL TANK SPOIL TANK
NOT FULL ‘g’ i
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‘ z‘x‘ / \‘ x \\ / \‘ [/4 \ll/ \II/ 'l\\(/ \\
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PLACE

   
   
 

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Ilsmantle cables
and hoses

  
  
   

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section

  

SECTION IN
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SECTION IN
PLACE

   

Discharge 8. refill
desandman

  

DISCHARGE

  

 

Figure 3.25 ~ CYCLONE Model Considering Soil Types (Continued)

 

4 STATISTICAL ANALYSIS OF OBSERVED DURATION DATA

In order to conduct simulations in WebCYCLONE with built model, task duration data
obtained flom the candidate project need to be analyzed. Each task element should be
accompanied with a duration set number that defines the duration category of the task and
the population flom which the duration of the task will be sampled. MicroCYCLONE /
WebCYCLONE recognizes two categories of tasks based on duration-stationary tasks
and nonstationary tasks. From data collected during the operation, only duration-
stationary tasks are defined. Figure 4.1 illustrates the time consuming process of the

simulation program and the works presented in Chapter 3 and 4.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Check if work task can be MODEL
processed (logical and <:7 DEVELOPMENT(logics
resource constraints are met) and resource constraints)
No Yes
, , STATISTICAL
Get trme required to ANALYSIS ON
”“655 this “‘5“ DURATION DATA
(finding durations)
Calculate the time taken
to complete this task
Update the resource/
entity allocation

 

 

 

 

 

Advance time

 

 

 

Figure 4.1 - Time Consuming of the WebCYCLONE Simulation Program

94

4.1 Data Collected from the Project

Appendix B shows the duration data collected flom the candidate project. 24 sets of data
are recorded for activities:

0 Durations of COMBI (node 1) Discharge and Refill Desandman,

0 COMBI (node 3) Dismantle Cables and Hoses,

0 COMBI (node 5) Pipe Section Setup on Guard Rail,

0 COMBI (node 7) Adjust Air Gripper,

0 COMBI (node 8) Install and Check Air Gripper,

0 COMBI (node 10) Bring Section flom Storage and Install Liner Casing,

0 And NORMAL (42) Jack Pipe Section.

The distributions of recorded activity durations will be found using goodness-of-fit
testing on CDFS (Cumulative Density Function). Activity duration of jacking pipe section
will be further analyzed to find distributions in four types of soil conditions. All the
analyses are done with R190. R, which is a flee version of S-plus and can be

downloaded flom http://www.r-project.org/.

Non-record activity durations such as crane returning, attaching pipe to crane are not

critical in the project, and are assumed as having same distributions as other recorded

slurry microtunneling project (Nido et al. 1999).

95

4.2 Introduction to Statistical Distributions in WebCYCLONE

The Statistical distributions for the duration time random variables recognized by the
input module of WebCYCLONE program are:

0 Exponential distribution,

0 Triangular distribution,

0 Uniform distribution,

0 Log normal distribution,

0 And Beta distribution.

1. Exponential distribution: “13(6)

The probability density function (PDF) of the exponential distribution “13(6) is

f(x) :16“, x > 0, 6 > 0
I9 , where 9 is the scale parameter.

Both the mean and the standard deviation of “13(9) equal to ‘9 .

The cumulative distribution function (cdf) is the probability that the variable takes a
value less than or equal to x. That is F (x) : Pr(X S x). Therefore, the cdf of exponential
distribution CXp(9) iSF(x) = l—e’x’g, x > O, 6 > 0.

The exponential pdf is always convex, and is stretched to the right as 9 increases in

value. The following in Figure 4.2 are the plots of the probability density fimctions

ofexp(0.5), exp(l) and exp(2)_

96

PDF of exp

 

 

 

 

 

 

Q
P
9=0.5
‘0
6—
'¢
6 \1
6:2

0
d —

I I I I I I I

O 1 2 3 4 5 6

Figure 4.2 -PDFs of Exponential Distribution (Shao, 2003)

2. Triangular distribution: Triangular-(a, 9,13)

The probability density function (pdf) of the Triangular distribution Triangular(a, 6’ b) is

 

 

 

 

 

r 2(x-a) a<x<6
(b-a)(0-a)’ — _
f(x)=<
2(b—x) , (95be
J” " “)(b ‘6') , and its cdfis
[ (x—a)2 03x36?
F(x) =. (b-a)(6-a)
_ (b—x)2 <x<b
. (b—axb—a)’ ’

 

where a represents the lower bound (the least possible value), b represents the upper
bound (the highest possible value), and 9 is the mode (the most common value). The

distribution is called right triangular distribution when 9 = b, and left triangular

97

—1—(a+b+6)

 

 

distribution when 9 = a . The mean of Triangular(a, 6’ b) equals to 3 , and the
Jaz +1)2 +62 -ab—a(9—b6
standard deviation equals to 18

The distribution is skewed to the left when the mode is close to the minimum, and is
skewed to the right when the mode is close to the maximum. It is a simple distribution
that as its name implied, has a triangular shape. Below in Figure 4.3 are the plots of the

pdfs of four triangular distributions with varying parameters.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

PDF of Triangular“), 0, 1) PDF of-Triangular(0,1, 1)
q .r i 0. _
N N
‘9 .. ‘0. -
3? °. ... '3? 0. a
no _ '0. _
O O
2 - 2 .
I I I I I I I I I I I I
00 02 04 06 08 1.0 00 02 O4 06 08 10
x x
PDF of Triangulaflo, 0.25, 1) PDF of Triangular“), 0.75.1)
°. .4 C’.
N N
"’. .4 '9 a
3 ° - g o _
m. - “’- a
O O
O. .4 °
° I I I I I ° I I I I I I
00 02 04 06 08 1.0 00 02 04 06 08 10
x x

Figure 4.3 —PDFs of Triangular Distribution

98

3. Uniform distribution: U(a, b)

U(a, b)

The probability density fimction (pdf) of the uniform distribution

‘ 1
f(x)=——, anSb
is b—a , where a is the location parameter representing the lower

bound (the least possible value), and b " a is the scale parameter with b representing the

' U ( b) —1— (a + b)
upper bound (the highest possible value). The mean of a, equals to 2 , and the

b ._
standard deviation equals to M .

Q

 

 

 

 

 

 

The following in Figure 4.4 is the plot of the probability density function of U(O’ 1) .
PDF of U(O, 1)
:5 ..
$1 ..
8 $3 -
g _
g ._
O O O 2 0.4 0.6 O 8 1 0

Figure 4.4 —PDF of Uniform Distribution

The uniform distribution measures data for which the probability of occurrence is the

same for all possible values of x .

99

2
4. Lognormal distribution lognormal(6,it,0')

A variable X is lognormally distributed if Y = log(X ) is normally distributed, where

“ log ” denotes the natural logarithm. The probability density function (pdf) of the

lognormal distribution log nor mal(6,m,0') is

e-[log((x—0)M))2/(202)]

f(X)= ,—
(x—6)0' 271' , x20; it>0, 0'>O,

 

6

where is the location parameter, A is the scale parameter, and 0' is the shape

parameter. The case where ,u = O and ’1 =1 is called standard lognormal distribution.

. 2 0,2
The mean of lognormal(6,l,o* ) equals t09+3~305 . The standard deviation of

lognormal(6,/1,0’2) equals to 1W6"2 (6"2 -1).

The lognormal distribution is a distribution skewed to the right, and the degree of

skewness increases as 0' increases, for a given (9 , A ). Therefore, lognormal distribution
is used to model continuous random quantities when the distribution is believed to be
skewed, such as certain income and lifetime variables. The following in Figure 4.5 is the

plot of the standard lognormal probability density function for four values of 0' .

100

PDF of lognonnaKO, 1 , 0.2) PDF of lognorrnaKO, 1, 0.5)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

a)
a o m
In
0 — 8 ~
3 — N _
q 0
0 ° ..
C -‘ l l l l T l C l l l l l
0.5 1.0 1.5 2.0 2.5 3.0 0 2 4 6 8
X X
PDF of lognorrnal(0, 1, 1.5) PDF of Iognormal(0, 1, 6)
a - 8 —
J .—
r 3‘ r 3 ‘
8 — 8 ~
_. .4
O O
o l l l l l l l C d l l l T l l.
0 2 4 6 a 10 12 0 5 10 15 20 25
X X

Figure 4.5 -PDFs of Lognormal Distributions

5. Beta distribution: '6 (a, b, c, d)

The probability density function (pdf) of the beta distribution ,8(a, b’ c’ d) is

x-a
b—a

 

1 .F(c+d) (1_x—a

b—a r(c)r(d) '17—? )c-

f (X) = )‘H(

a_<_x_<_b; a>0, b>0, c>0, d>O,

where c and d are the shape parameters, a and b are the lower and upper bounds,

rm i

respectively of the distribution. Here 5 the gamma function, which is defined as

I‘(x) = It“‘e”dt
° . If x is an integer n = 1, 2, 3, ..., then

F(n)=(n—l)(n—2)(n—3)---1=(n—l)!.

101

The case where a = 0 and b = ,1 is called the standard beta distribution. The uniform

 

distribution U(a,b) is a special case of beta distribution when 0 = d = 1.
c
a + (b — a)
The mean of 16(0’ 1” C’ ‘1) equals to C + d , and its standard deviation equals to

 

 

(b—a)‘/ 2cd
(c+d) (c+d+l).

The shape of the beta distribution is quite variable depending on the values of the

parameters. As illustrated by the plot below, when C <1 and d <1, the distribution is U-

shaped; when the two parameters are equal, the distribution is symmetrical, and a special
case is uniform distribution when; if C < d , then the distribution is skewed to the left; if

C > d , then the distribution is skewed to the right. The beta distribution is often used to
estimate the proportion of defective items in a shipment or model time to complete a task.

Figure 4.6 shows the plot of the beta probability density function for different values.

102

PM

PM

PDF of beta(0, 1, 0.75, 0.75) ' PDF of beta(0, 1, 2, 2)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

‘7. _
8 - 0 ~
._ 5
8 CL (0 j
0'
$2 — q
N
.._ _J o' r
o I I F I I I I I I I I I
0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0
x x
PDF of beta(0, 1, 2, 5) PDF of beta(0, 1, 5, 2)
o o
N _ N T
—I g d
O. .0 0- q _
‘- s-
—I -i
o 0. ..
0' I I I I I o I I I T I
0.0 0.2 0.4 0.6 0.8 0.2 0.4 0.6 0.8 1.0
x x

Figure 4.6 — PDFS of Beta Distributions

4.3 Kolmogorov-Smirnov Goodness-of-Fit Test

To decide the distributions for the duration time random variables, we follow the below

steps. First we assume a pre-specifred distribution based on the statistical properties, for

instance the histogram plot, of the duration data. Then we estimate the distribution
parameters from the data using the Maximum Likelihood Estimation (MLE) method.
Next we test the assumed distribution using Kolmogorov-Simimov test. If the assumed
distribution is rejected, we will choose another distribution, and repeat the above steps

until we find an appropriate distribution.

103

The Kolmogorov-Smirnov test was developed by Kolmogorov and Smirnov in the 19305
to to determine if a sample comes from a given hypothesized distribution. The
Kolmogorov-Smimov test is based on the empirical cumulative distribution function

(ECDF). Given n ordered data points x“) S x“) S. H S x‘") , the ECDF is defined as

 

 

[0, x < x“)
1 <
“r x“) - x < M)
n
F" (x) = < i
n
(I, xm S x

The Kolmogorov-Smirnov test statistic D is defined as the maximum difference between

the empirical distribution function and the theoretical cumulative distribution function

(cdf) of the hypothesized distribution. The hypothesized distribution is rejected when D
is large enough, or equivalently when the p-value is smaller than the significance level a ,

which is commonly chosen as 0.05.

4.4 Distributions Suggested for the Duration Time Random Variables

Table 4.1 summarizes the distributions determined, the correspondent estimations of

parameter, the test statistics D and the p-values of the Kolmogorov—Smimov test.

104

Table 4.1—Distributions, Parameters, Test Statistics, and P-values

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

D-statistic of P-value of
Distribution
Variables Parameters Kolmogorov- Kolmogorov- Comment
Determined
Smirnov test Smirnov test
Lognormal ‘
NOR 42 log normal(6, 2., 0'2) (8, 30.177, 0.0917 0.988 GOOD
0.756)
BETA (Par1)(Par2) Beta(12, 102, OK
NOR 42 0.159 0.579
(Par3) (Par4) 0.854, 1.403) (suggest)
, Triangular(12 OK
NOR 42 Trrangular(a, 6, b) 0.168 0.507
, 31, 92) , (suggest)
BETA (28,
BETA (Parl) (Par2) Good
COMBI 5 (P 3) (P 4) 80, 0.761, 0.1129 0.920 ( )
ar ar su est
1.841) g
. Lognormal
COMBI 5 log normal (6, 11, 0'2) (25, 14.062, 0.1021 0.964 Good
0.783)
Lognormal
COMBI 2
10 log normal(6, 2., a ) (0, 6.838, 0.1615 0.559 Good
' 0.377)
COMBI BETA (Par1)(Par2) Beta (3, 23, Worse than
0.2059 0.261
10 (Par3) (Par4) 1.481, 5.353) Triangular
COMBI , Trian ar 2, OK
Trrangular(a, 19, b) gul ( 0.1891 0.357
10 5, 15) (suggest)
Lognormal
COMB13 log normal(6, 2., 0'2) (5, 5.537, 0.1226 0.880 Good
0.650)
BETA (Par1)(Par2) BETA (7, 33, Good
COMBI 3 0.1304 0.8288
(Par3) (Par4) 0.643, 3.020) (suggest)
, Triangular (3, OK (worse
COMBI 3 Trrangular(a, 6, b) 0.1696 0.5228
7, 27) than beta)

 

 

Figures 4.7 to 4.10 show the CDFS of the determined distributions for NORMAL 42,

COMBI 5, COMBI 10, COMBI 3 respectively.

105

Foo '

F(X)

Normal 42 Jack Pipe Section, Beta(12, 102, 0.854, 1.403)

 

 

 

 

 

,_/_°—°_
.T /'
/
7/
/
,4“—
/
/°_.._
0:0 0:2 0:4 0:6 0:8
Studentized x

Figure 4.7 —CDF of NORMAL 42 Jack Pipe Section

COMBI 5 Pipe Section Install on Guardrail, beta(28, 80, 0.761, 1.841)

1.0

 

1.0

0.6

0.4

0.2

 

0.0

—--------.--

 

 

1 1

0.6 0.8

l l

0.2 0.4
Studentized x

Figure 4.8 —CDF of COMBI 5 Install Pipe Section on Guardrail

106

COMBI 10 Bring Section 8. Install Liner Casing, Triangular(2, 5, 15)

 

 

 

 

 

 

 

 

 

 

 

 

q _ -
«é _
o
"D. -
o
3? /
u":
‘12 _
o
N. _
o
0. _ -
o 1 l l I F l - l
2 4 6 8 10 12 14 16
x
Figure 4.9 — GDP of COMBI 10 Bring Section and Install Liner Casing
COMBI 3 Dismantle Cables 8: Hoses! Retrack Jack Frame, beta(7, 33, 0.643, 3.020)
0
- /
0——°_ /
(0
o “ 72/
co _ /i_
o 2 .._
3
11.
V. -
o
N
o' -
0.
o l l l l l
0.0 0.2 0.4 0.6 0.8

Studentized x
Figure 4.10 -CDF of COMBI 3 Dismantle Cables & Hoses/ Retrack Jack Frame

Activity duration distributions used in the simulation are shown in Table 4.2. It was

discovered that lognormal distribution was not implemented in WebCYCLONE. Thus, I

107

any statistically suggested lognormal distribution was replaced by the second good

distribution in the simulation as shown in Table 4.1.

Table 4.2 —Duration Information

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Activity number Description Probabilistic distribution
1 Discharge and refill desandman TRI (10,12,15)

2 Mix lubrication TRI (25,30,35)

3 Dismantle cables and hoses BETA (7,33,0.643,3.020)
4 Empty spoil tank TRI (20,30,35)

5 Setup pipe section on guard rail BETA (28,80,0.76l,1.84l)
6 Lower section into shafi UNI (1,2)

7 Adjust air gripper UNI (10,15)

8 Install and check air gripper UNI (10, 15)

9 Attach section to crane DET (2)

10 Bring section from storage and install liner casing TRI (2,5,15)

40 Lift section to position DET (1)

41 Crane returns DET (2)

42 Jack pipe section BETA (12, 102, 0.854, 1.403)
43 Dummy DET (0)

 

4.5 Compare the Duration Time of Jacking Pipe Section in Different

Soil Conditions

 

In this section, the differences between the jacking pipe activity durations in four types of
soils are compared. When microtunneling in different types of soils, the major
productivity difference comes from the activity COMBI 42 Jack Pipe Section, which is
the direct interaction between soil composition and microtunneling productivity. If the

differences of durations are significant, then building model with different soils

108

enhancement is a valid approach. In addition, distributions of jacking pipe sections in

different soils need to be found.

Table 4.3 shows the sample means and sample standard deviations for each soil. From
Table 4.3, we see that the mean jacking time in clay is the largest, which is mainly due to
the incompatibility of slurry system and clay soil; the next largest is clayey gravel; silt

and sand takes the shortest times.

Table 4.3 — Sample Means and Standard Deviations of Jacking Durations in Different Soils

 

 

 

 

 

Soils Sample Mean Sample Standard Deviation
Clay 70.67 22.89
Silt ‘ 29.167 8.40
Sand 26.83 . 10.87
Clayey Gravel 57.5 17.56

 

 

 

 

 

To test further whether the differences are significant, we perform the pairwise
comparisons between the pushing times on four different soils using Welch’s two sample
t-test where equal variances are not assumed, and Wilcoxon rank sum test. The t-test is a
popular test used to compare the means of two populations, and it assumes that the two
populations are both normal distributed. The Wilxocon rank sum test is a nonparametric
version of the two sample t-test, and it tests the equality of the medians of two
populations. The Wilxocon rank sum test is very commonly used when the sample size is

very small or when the normality assumption is violated, which is the case of this study.

Table 4.4 and 4.5 summarize the pairwise comparison results from t-test and Wilcoxon

rank tests, respectively. Both t-test and Wilcoxon rank tests give the similar results.

109

There is no statistical significant difference between clay and clayey gravel, neither
between silt and sand. The mean jacking durations between the rest 4 pairs: clay and silt,
clay and sand, clayey gravel and silt, clayey gravel and sand are significantly different.
More specifically, the jacking time in clay and clayey gravel are significantly longer than

those on silt and sand.

Table 4.4 — Pairwise comparison results from two sample t-test

 

 

 

 

 

 

 

 

Pair Test statistic p-value Significant
Clay vs Silt 4.1694 0.005243 Yes
Clay vs Sand 4.2374 0.003676 Yes
Clay vs Clayey gravel 1.118 0.2914 No
Silt vs Sand 0.416 0.6867 No
Silt vs Clayey gravel -3.5656 0.008783 Yes
Sand vs Clayey gravel ~3.6375 0.00616 Yes

 

 

 

 

Table 4.5 — Pairwise comparison results from Wilcoxon rank test

 

 

 

 

 

 

 

 

Pair Test statistic p-value Significant
Clay vs Silt 34 0.01291 Yes
Clay vs Sand 34 0.008658 Yes
Clay vs Clayey gravel 25 0.3095 No
Silt vs Sand 20.5 0.7479 No
Silt vs Clayey gravel 0.5 0.0063 Yes
Sand vs Clayey gravel 0.5 0.006392 Yes

 

 

 

 

found as shown in Table 4.6.

Using the Kolmogorov-Smirnov test, jacking duration distributions in different soils are

Table 4.6 —Jacking Pipe Duration Distributions in Different Soils

 

 

 

 

 

 

 

 

 

Activity Soil Condition Probabilistic distribution
Jack PipeSection Clay BETA (19, 92, 0.781, 0.323)
‘ Jack Pipe Section Silt BETA (17, 51, 0.989, 1.775)
Jack Pipe Section Sand BETA (12, 46, 0.613, 0.793)
Jack Pipe Section Clayey Gravel BETA (26, 88, 1.075, 1.041)

 

 

 

110

5 SIMULATION RESULTS AND DISCUSSION

In chapter 3, the prototype model and soil impacts enhanced model of microtunneling
have been developed. In addition, chapter 4 studied the activity duration data in both
models. Combining previous work, this chapter presents simulation results from two
models subsequently. Firstly, simulations with the prototype model are conducted and the
validation of the prototype model is discussed with simulation results. Afier the
validation, considerations of different soil compositions are added into the model, which
was presented in chapter 3 (section 3.7). Simulations have been conducted again with
enhanced model. Simulation results from enhanced model are validated and conducted
sensitivity analysis to optimize the productivity. Finally in this chapter, different soil

composition impacts on microtunneling productivity are studied.

5.1 Simulation Results with Prototype CYCLONE Model

A total of 30 simulation runs were performed with the prototype CYCLONE
microtunneling model. Appendix C has the coding for prototype model with duration
data distribution discussed in chapter 4. Appendix E presents the full set of data from
simulation results, which) includes productivity information for each cycle, duration
statistics for CYCLONE active elements, idling percentage and waiting time statistics for

CYCLONE passive elements, and elements trace information.
For validation purpose, the productivities generated from the simulations are studied

thoroughly. Other results as resource idling and limitations will be analyzed with soil

enhanced model. Table 5.1 and 5.2 show the productivities obtained from the simulation.

111

.4-..”

Table 5.1 —Simulated Microtunneling Process Productivity Information by Cycle

 

1

 

Mflfl-

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

EiSirn. Time (Accumulative) Cycle No iPer “3:224:11: (min.) Productivity Per Time Unit
1 160.4 41 1 41 160.4 1 0.006234
' 280. 9 1 2 ' 140.45 $444444 0.007120
4 44434347144 44 4 ; 3 112 3666667 1444 0.008899
44 4444434946184 4 :4 4 4444444 49494424444 4,1444 44404041068044" 4
629.7 44444 44 5 123 49444 44444441 0.007940
751.5 44 4144446 125.25 1 0.007984
898.1 {44447444 4444444 441248.434 4444444441 0.007794
967.9 4444 441 8 120.9875 :4 0.008265
1066.1 9 1184555556 14 0.008442
1195.2 4 4 i 4414044 119.52 414444 4 0.008367
1271.2 44; 11 115.5636364 ‘1' 0.008653
1343.9 4' 4E4 12 4 4 111. 9916667 1 0.008929
4 4 444144425442 4 4 4 ‘ 13 10963074649424 4474 4 0.009121 4444
41496.9 441444414444 106.9214286 444! 0.009353
1550.4 44 14544 444444 103.36 {4444 0.009675
44 4 4 1607.3 4 444 444164 4 10045625 1444 0.009955
1706.7 44 4 Q 4147444 4444 100.3941176 1 0.009961
18025 4 444 4418 44 1001388889 1 0.009986
4444149346404 44 414441494 4 101.8947368 4441' 0.009814
2031.1 4 20 .3 101.555 1 0.009847
2199.3 21 1. 104.7285714 4) 0.009549
{4 2374.4 4 442244 107.9272727 '1' 0.009265
(4 2501.4 44;} 23 4 108.7565217 14 44 4 0.009195
1 2629.1 4 4 42444 4 109.5458333 1 0.009129
14 2715.54 4 4 4144442344 4144 108.62 414 0.009206
1' 2818.7 1 26 ‘ 108.4115385 1 0.009224
2908.8 ; 247 4444‘ 107.7333333 1 0.009282
1 3013.0 4 444 4, 44428 1 107.6071429 1 0.009293
1' 444 3170.4 4; 29 109.3241379 0.009147
1 ‘4 30 107.8466667 4444 ‘ 0.009272

 

 

.- m ...,...“ .-m~. -_~ _

 

Table 5.2 —Overall Simulated Microtunneling Process Productivity Information

 

 

 

 

 

 

[Total Sim. Time Unit C cle No Productivity Productivity
(in minute) , y (per pipe section) (per time unit)
3 3235.4 ’ 30 144107 867 0 009272409316360385 '

112

 

Figure 5.1 shows the change of productivities in thirty cycles. A pattern can be easily
observed on the plot. The duration time decreasing steeply on the initial four pipe
sections reflects the preparation work has to be done at the beginning stage of the project.
Moreover, it can be explained as following productivity learning curve (Abdelhamid
2004), which predicts productivity will increase as units being constructed, and the
increase rate is slowing down to zero eventually. There always is a limit of productivity
increase through learning. Abnormal pattern appears after pipe section number four that
cycle duration climbs suddenly. This abrupt change can only be explained as resource
limitation. Rearranging resource might release this bottleneck. With the soil-enhanced
model, resources will be studied to find the sensitive ones (bottlenecks) and different

alternative resource allocations will be simulated to optimize the operation.

The rest parts of the plot in Figure 5.1 show the same pattern, afier a short platform of
pipe section 6, productivities increase from pipe 7 to 16, following exactly the learning
curve. Then another platform starts from section 16 to 20, which could reflect the bottom
of productivity improving. Duration jumps from section 20 to 24, not as sharp as the
previous but still indicates some resource arrangements need to be adjusted. A platform

from section 25 to 30 finishes the curve.

Overall, the productivity simulation results are in reasonable patterns. The validation of

the prototype model with these results will be discussed in next section.

113

170
165
160
155
150
3 145
‘5 140
.E 135
c 130
4; 125
E 120
fi 115
110
105
100
95
SI)

 

 

 

 

 

 

12 3 4 5 6 7 8 9101112131415161718192021222324252627282930
Smlation0/cles

Figure 5.1 -Simulation Cycle Durations with Prototype Model

5.2 Validation of the Prototype Simulation Model

In Appendix B, the actual production measured in the field was recorded as follows:

Table 5.3 -Actual Cycle Time Measured in the Field

 

 

 

 

 

Average cycle time for installation of an 8-ft section of PVC pipe in:
Clay 169 min.

Silt 97 min.

Sand 91 min.

Clayey Gravel 130 min.

 

 

 

 

For a soil composition of 25% clay, 25% silt, 25% sand, and 25% clayey gravel, the
average duration for installing one 8 feet pipe section is 121.75 minutes. Consulting with
expert, it was found that the production rates of the project for jacking pipe were within
acceptable range of a microtunneling project for the specified type of soil (Najafi 1993).

However, the average rate of production for the candidate project was 8.5 meter (28 feet)

114

per day, while the reported rates for typical microtunneling projects are about 12 to 15
meters (36 to 45 feet) per day (Kramer et a1. 1992). The main reason for overall-
production being lower than a standard microtunneling project is due to the experimental
nature of the candidate project (Najafi 1993). The averaged simulated productivity from
30 cycles is 13% higher than the productivity observed in the field, which is clearly in a
reasonable range of typical microtunneling project. Therefore, the logic and structure of

the prototype model and accuracy of input data have been validated.

Afier verifying the simulation results with actual data the model can be enhanced with
soil compositions and used for experimentation. Using a soil composition of equal
portions of clay, silt, sand, and clayey gravel, the simulations are conducted to identify
the resource bottlenecks. Alternative resource arrangements are simulated to find the
optimized productivity of the operation. The enhanced model is also modified for testing
the impacts of different soil compositions on productivity, which is discussed in Section

5.5.

5.3 Simulation Results with Enhanced Model Considering Soil

Composition Changes

A total of 30 simulation runs were performed with the soil enhanced CYCLONE
microtunneling model. Appendix D has the coding for soil enhanced model with
duration data distribution discussed in chapter 4. Appendix F presents the full set of data
from simulation results, which includes productivity information for each cycle, duration

statistics for CYCLONE active elements, idling percentage and waiting time statistics for

115

CYCLONE passive elements, and elements trace information. Table 5.4 and 5.5 show the

productivities obtained from the simulation.

 

Sim. Time (Accumulative)

Duration 44

1Cy4cle No ’Per Pipe Section (min. )

Table 5.4 -Simulated Microtunneling Process Productivity Information by Cycle

Productivity Per Time Unit

 

155.7

 

1
1 .

303.5
441 6

 

550.5

 

702.9
4831.644 4

 

934.6

5
—. ._._.., . .2-. -.._. . .,
. .
1 . :
1 3 1

 

1042.2

 

444141444642 44 444
1246.1

44441345. 6

1403.1--...-,_. ....

 

1482.3

 

1
1
1
1
1
1
1
I

1616.2

44444441464941.3444

 

1762 8

 

4 1887.1 .
441980. 04 4 4

 

2129.9

 

2230. 7

2372 3

 

2546.8

 

 

2679.9

2822442 4

1;
1

l
l

1

134N1—

l

l
l
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l

155. 739

 

4 151.7681
147.2104 '4

 

137.6084

0.006421
0 006589

' 44400046793444

 

0.007267

 

140.5877

14386001 4

0.007113
0.0072154 4 4

 

Wo oo.’\150~4u~34>1

133.5113

0.007490

 

130.2762

12744344561

 

0.007676

4 040074854244444 '

 

1

~
~

~
1::

 

124.6106

 

122.3242 4
44116.9414844 __ .

 

114.0251

 

115.4468

4411247542344

 

110.1686

 

111.0001

' 4140944998494 4

0.008025

44440004817454 4

0.008553 4

0.008770
0.008662

WM“ -W~-~ .am... ..._ - -_. --m.

._.- -.«-..............J... __2 ....__.__... ... ..., w ...,".-. .--, m.

40. 04088694 '4 "

 

0.009077

 

112.0951

 

111.5325

114249468844 4

0.008921

 

0.008966

0008852

 

1 15.7675

 

1 16.5094

44411745917444

0.008638

-,_.-. -._... _‘——-~v—

0. 00845483444

440. 0085044

 

2926.7

 

3063.1

44434175484444

1 17.0686

 

117.8134

117 464194

 

3304.1

 

3456.5

4 ' 4434544144344

118.008

 

119.1895

44141840498444 4

0.008542

 

0.008488

40.008502 4 4 ’

 

0.008474

44404004484390
4 0.0084714 4'

 

116

 

 

Table 5.5 —Overall Simulated Microtunneling Process Productivity Information

 

 

 

 

1Total Sim. Time Unit 14C cle No 4 Productivity 1 Productivity
(in minute) 1 y ' (per pipe section) 1 (per time unit) 1
1 3541.3 41 30 1 1 18.043 10.008471404967265655

 

The averaged duration time of 118.043 minutes is longer than simulation result from the
prototype model of 107.867 minutes by 9.4% due to the modified model structure and
input jacking duration data. However, it is closer to the average of actual measured
durations in the field, 121.45 minutes. Only 3% difference exists between the soil
enhanced simulation results and actual measured data, which indicates an improved
accuracy of modeling.

Figures 5.2 to 5.16 show the trace information for QUEUE elements, where resource
units wait until the successive activity starts. The trace information for all QUEUE

elements is recorded in Appendix F.

35

 

28

2. “a

M 4E

7 E

. 47%

3323.5

 

 

Figure 5.2 —Trace Chart for QUEUE-1 1 Section on Storage

117

 

4||||11|ll llll

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3458.5

Figure 5.3 -Tracc Chart for QUEUE-12 Position Available

 

3458.5
Figure 5.4 -Trace Chart for QUEUE-13 Labor A Idle

 

 

 

 

 

Figure 5.5 -Trace Chart for QUEUE-14 Supervisor Idle

118

10

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 5.6 --Trace Chart for QUEUE-15 Air Gripper Ready

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 5.7 ——Trace Chart for QUEUE-16 Crane Idle

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 5.8 —Trace Chart for QUEUE-17 Control Crane

119

3491.2

3541.3

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3541.3
Figure 5.9 —Trace Chart for QUEUE-18 Labor B Idle

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3319.1
Figure 5.10 -Trace Chart for QUEUE-19 Truck Idle

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3319.1

120

Figure 5.11 -Trace Chart for QUEUE-20 Backhoe Idle

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ll

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

, 3321.5
Figure 5.12 —Trace Chart for QUEUE-22 Bentonite Ready
' 4 ' 4 ‘ 4 f ' 3541.3
Figure 5.13 -Trace Chart for QUEUE-23 Jacking System Idle
3355.5

121

Figure 5.14 -Trace Chart for QUEUE-25 Need Air Gripper

 

 

 

 

 

 

 

 

 

 

 

2747.9
Figure 5.15 —Trace Chart for QUEUE-26 Air Gripper Need Adjust

 

 

 

 

 

 

 

 

 

 

 

ll llHlllllHHl l1 |JJ|

Figure 5.16 —Trace Chart for QUEUE-28 Position Occupied

 

 

3456.5

As shown in Figure 5.2, thirty pipe sections were brought fi'om storage and prepared with
different durations. The overall pattern is linear with reasonable variations. From Figure
5.3 and 5 .16, we can see there is less waiting time in QUEUE 12 than QUEUE 28, which
could be explained as attaching section to crane takes long time to put next pipe section
on wait. While on the contrary, the only position on the crane is filled immediately when
it is emptied. The limitation resources of attaching section to crane activity are cranes and
Labor A, which need sensitivity analysis. From Figure 5.4, 5 .5 and 5.9, we found Labor

A, Supervisor and Labor B are idling very frequently, which is proved in Appendix F,

122

where Labor A has 80.87% idling time, Labor B and supervisor has 50.43% and 47.81%
idling time, respectively. Apparently, they are not bottleneck resources compared with
crane in Figure 5.8 with 3.93% idle time. However, in sensitivity analysis of next section,

when crane number is added, it may trigger labor shortage.

For air gripper installation, in Figure 5.14, when the pipe section need air gripper, only in
5.1% of the time it need to wait; in Figure 5.15, when air gripper need adjust, 100% of
the time adjustment is in time; in Figure 5.6, air gripper is in 97.6% of the time ready
when pipe section need to be attached to crane. Conclusion can be drawn that air gripper

installation is efficient and create no delays for the operation.

Truck, backhoe, and bentonite are three resources that follow the same pattern, because
of the assumption made in model development. Every four times of jacking pipe sections
activate the truck, backhoe, and bentonite preparation once. These three resources are
idling for 88.17% of the time in microtunneling operation, which have no effect on

delaying the productivity.

In Figure 5.13, the jacking system is regarded busy. Only in 8.93% of the time, it is
idling. This may indicate that jacking system is one of the limiting factors. Jacking
system is the resource with one of the highest utilization rate. By changing the
Microtunnel Boring Machine cutting head design to more appropriate, production can be 4

increased. This change can be reflected in the model by changing the jacking pipe section

123

activity duration. The optimization of MTBM with the soil conditions will increase the

productivity.

5.4 Sensitivity Analysis

In this section, the numbers of crane and labor crews will be analyzed as discussed in the
previous section. Different combinations are simulated to find the optimization plan. As
Shown in Table 5.6 and 5.7, all combinations of one to two Cranes, one to three Labor A
crews, one to three Labor B crews, and one to three Supervisors have been simulated.
Due to the space limitation on the site, no more than two cranes have been simulated. The
highest productivity appears with one Labor A crew, three Labor B crews, two
Supervisors, and two cranes. The second highest plan is to have three Labor A crews and
three Labor B crews, one Supervisor, and two cranes. The third highest plan is to have
three Labor A crews, two Supervisors, one crane and one Labor B crew. The productivity
of the second and third plans are both very close to the first plan. The fourth highest plan
is to add two Supervisors to the original. This indicates the supervisor is one of the
bottleneck resources, who is responsible for too many activities. The maximum
productivity plans do not consider cost factor. Therefore, it can not be concluded that

which one is the optimized.

By adding one Labor A crew, one Labor B crew, one Supervisor, or one Crane to the
system, production improves. Coincidently, the productivity improvements due to adding
one Labor A crew or one Labor B crew are the same. When adding both to two or three,
the productivity slightly decreases. Labor A and B crews reach the limitation of

improving productivity when used without adding other resources. When jointly used

124

with one new crane, the Labor A and B crews contribute more to productivity

improvement.

The productivity improvements due to adding one supervisor or one crane are the same,

which are higher than adding One labor crew. Both of them are bottlenecks of the original

operation. Consideration of cost factor should be taken to judge which plan is more

feasible.

Figure 5.17 —Sensitivity Analysis Results

 

Resource Information

 

11 or # of 1
LABOR' SUPERVISOR'
at LABOR at SUPERVISOR

A IDLE IDLE

.2.-.3 M01
1

# of
CRANE'
131 CRANE

 

 

 

# of CRANE
CONTROL
SIGNAL at
CONTROL

CRANE

Productivity Information

 

#of

 

1LABOR'1
at LABOR;

B IDLE

1 (Section/ min) Installation

 

 

 

1 Productivity Duration Per
Per Unit Time Pipe Section

Time

(min)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1

 

l
l
1

1

0.0101

4440200947444 4

44103 0928

 

 

 

0.0092

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14 1 1 1 1 1 1 1 0.0091 109.8901
1 41 41 144441 4144 4441 4f; 0.0093 107.5269
1 1444 1 1 2-1-2.2. 14 2 000940 14141411114
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125

111.1111

 

117.6471

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Figure 5.187 (cont’d)

 

 

 

_~.-. “0

Productivity Information

..-.2.--.--.--.2.-22222._ 2. 4414 2 2

Time Duration

1 44 Resource Information

2 .# ofC E44 #of
CONTROL

# f #of
1 ° SUPERVIS

# of

 

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L ABOR' at 1 Productivity

LABOR B ' Per Unlt TIme

(Section! min)
1

Per Pipe Section
Installation
(min)

44441031263244 4

 

1
1
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1
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1
’.--2
1
1
1
1
1

 

112.3596
44116. 2791

 

4 108.6957

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

126

 

 

444443444444 4 444 44442444441444444442444444414444442444444E 0.0093 ,44 107.5269

;4 3 2 1 2 1 3 4 0.0100 1 ' 100

2-3.-- -4 442 - 4144 1 1 - 1.. .2- 1 40.040949444441444 414014 0414041444444
1 3 1 2 1 14444 1 1 42444 44 4 0.0092 14 108.6957

1 3 ; 2 . 1 1 1 1 3 0.0091 1444 109.8901

4 34 4 41 24 2 44144 4 44424444 11' 40.400874 4.4 414141492425 4
3 1 2 2 1 2 1444442 0.0092 1 108.6957
14444434444414 442 2 1 2 1 3 0.0091 1 109.8901

14 W313 2 4414 2-1-22-212 11 0.0095 105.2632

1 3 414 3 1 1 1 1 2 4 0.0093 1 107.5269

; 3 414 3 1 4444144 41444444441444 3 0.0095 44444441052632

144 3 13- 2 2.-.! - 25-2- .-2.12-----.1. - - 40140093 1414671.45424594444444
1444 3 1 3 2 1 1 2 441 2 4 4 44014109474444 1444 144034.404494248444 444
1 3 1444 3 2 1444444244444414444444344444 4 4 40404049424441 44104869457444

 

5.5 Impacts of Different Soil Conditions

Afier analyzing the resource limitations, productivity changes in the operation due to
different soil composition are introduced as shown in Figure 5.19. The soil compositions
have been modified from 25% of each soil type to variety of combinations. Simulation
runs with the soil enhanced model generate corresponding productivities. A linear
regression is conducted to find the correlations between microtunneling productivity in

the candidate project and soil compositions. All the analyses are done with R190. R is a

free version of S-plus and can be downloaded from http://www.r-project.org/.

Figure 5.19 —Productivity in Different Soil Compositions

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Percentage of Percentage of Percentage of Percentage 0f Productivity Time Duration
Clayey Gravel in Sand in the Silt in the (3:23: Per Unit Time Per Pipe Section
the Operation Operation Operation (X4 = 100-Xl- (l/Y) Installation (Y)
(X1) (X2) (X3) X2-X3) (Section! nun) (min)

10 10 10 70 0.00819 122.1

10 10 20 60 0.008266 120.98
10 10 30 50 0.008554 116.9
10 10 40 40 0.008586 116.4733
10 10 50 30 0.008849 113.0033
10 10 60 20 0.009123 109.6133
10 20 10 60 0.008242 121.3333
10 30 10 50 0.008595 116.3533
10 40 10 40 0.0086 1 16.28
10 50 10 30 0.008809 113.5233
10 60 10 20 0.009028 1 10.7633
10 20 10 60 0.008242 121.3333
10 20 20 50 0.008531 117.22
10 20 30 40 0.008505 117.58
10 20 40 30 0.00873 114.5533
10 20 50 20 0.008969 11 1.5
10 20 60 10 0.009766 102.3933

 

127

 

Figure 5.19 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

10 30 20 40 0.008615 1 16.08
10 40 20 30 0.008858 112.8933
10 50 20 20 0.009066 110.3
10 30 30 30 0.008767 1 14.06
10 30 40 20 0.00896 1 1 1.6067
10 30 50 10 0.009692 103.18
10 40 3o 20 0.009139 109.4167
20 10 10 60 0.00817 122.4
30 10 10 50 0.007969 125.4933
40 10 10 40 0.007856 127.29
50 10 10 30 0.007793 128.3267
60 10 10 20 0.007888 126.78
20 10 10 60 0.00817 122.4
20 10 20 50 0.008454 118.2867
20 10 30 40 0.008428 1 18.65
20 10 40 30 0.008628 1 15.8967
20 10 50 20 0.008884 1 12.5667
20 10 60 10 0.009637 103.77
30 10 20 40 0.007986 125.22
40 10 20 30 0.008055 124.15
50 10 20 20 0.007993 125.1033
30 10 30 30 0.008117 123.2
30 10 40 20 0.008282 120.7467
30 10 50 10 0.008903 1 12.32
40 10 30 20 0.008287 120.6733
20 20 10 50 0.008457 1 18.24
20 30 10 40 0.008399 1 19.0667
20 40 10 30 0.008629 1 15.8933
20 50 10 20 0.008865 1 12.8067
20 60 10 10 0.009349 106.96
30 20 10 40 0.008051 124.2033
40 20 10 30 0.008098 123.4933
50 20 10 20 0.007951 125.77
60 20 10 10 0.008342 1 19.8767

 

 

 

 

 

 

128

 

Figure 5.19 (cont’d)

 

 

 

 

 

 

30 30 10 30 0.008182 122.2133
30 40 10 20 0.008349 119.77
30 50 10 10 0.008826 113.3033
40 30 10 20 0.008262 121.0433
50 30 10 10 0.008484 117.8733
25 25 25 25 _ 0.008475 118

 

 

 

 

 

 

 

 

- Linear regression of Y vs X1, X2, X3 and X4
The estimated coefficients are shown in Figure 5.20, where the estimated value are the
coefficients, and Pr(>|t|) is the p-value. All the p-values are significant small, which
means the data plots follow linear patterns on different dimensions. Such patterns are also

shown in Figure 5. 21.

Figure 5.20 —Confmements Estimation

 

 

 

 

 

Estimate Std. Error t value Pr(>|t|) Significance
(Intercept) 129.32946 1.30947 98.765 < 2e-16 ***
X1 0.06841 0.02386 2.867 0.00593 **
X2 -0.28765 0.02386 -12.054 < 2e-16 ***
X3 -0.30163 0.02238 -13.480 < 2e-16 ***

 

 

 

 

 

 

 

 

The residual standard error is 2.202 on 53 degrees of freedom. Multiple R-Squared is
0.8774; adjusted R-squared is 0.8704. F-statistic is 126.4 on 3 and 53 degree of freedom,

where p-value < 2.2e-16.

In Figure 5.17, X1, X2, X3, and X4 are plotted with Y separately. Clear linear patterns

can be found on the plots. The application of linear regression on the data is appropriate.

129

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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$1“ 0 g e e 2!“ e
-8 8 9 o .5 8 8 o
90 o 9 808
> 103 o >_ In 8 o a
F— :— O O
a-g a 8 e O O O 9
.. 10 o o
o 0
£08 0 $70 0' o
l l l T T l I .l I I I l
10 20 30 40 50 60 10 20 30 40.50 60
X1 )Q
o
o
3—3 8 gi~ 8 3 °
_ 0 o O -o 8 . 8
§08 0 o g 8
>- 1‘3 9 9 >- 53.. °
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‘- 8 o o g ‘- 8 a B
-0 go o o .1
l0 0 m 0
O- o-
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l l l l T l I l I l [j
10 20 30 40 50 60 10 20 3040 5060 70
)0 X4

Figure 5.21 —Data Plots on X and Y

The regression results are as following:
Y=a0+ a1X1+ a2X2+ a3X3+ a4X4
=a0+ a1X1+ a2X2+ a3X3+ a4(1-X1-X2-X3)
=aO+a4 +(a1-a4)X1 + (a2-a4)X2 + (a3-a4) X3, where the estimated coefficients:
a0 + a4 = 129.32946
a1 — a4 = 0.06841
a2 — a4 = -0.28765

a3 — a4 = -0.30163

130

All three are significant, and this means that al, a2, and a3 are all different from a4. More
specifically, a1 is significantly larger than a4, and a2, a3 are significantly smaller than a4.
Because X4 can be expressed as 100-X1-X2-X3, a1, a2, a3, and a4 do not have unique

values. However, the differences between them do have unique values.

131

6 SUMMARY AND CONCLUSIONS

6.1 Overall Summary

In previous chapters, in order to analyze microtunneling technology an actual project was
reviewed with other background information. The data collected at the Louisiana Tech
University LLB Microtunneling Field Test Project in Ruston, Louisiana has been
analyzed for modeling inputs. CYCLONE models have been built to reflect the
microtunneling operation with soil impacts. Through WebCYCLONE simulations, the
productivity of microtunneling operation has been analyzed and the limiting factors have
been evaluated. Recommendations are given to optimize the productivity. In addition,
the correlations between different soil compositions and microtunneling productivity

have been studied. The following research objectives have been completed:

1. Portrayed the process of microtunneling operation in Chapter 2,

2. Identified resources and develop the model for simulation in Chapter 3,

3. Analyzed the production cycle data and find statistical distributions in Chapter 4,

4. Input the distribution data in the model and run simulation with WebCYCLONE,
and presented the results in Appendix C and D.

5. Validated the simulated productivity results with actual observations at the project
in Section 5.1 and 5.2

6. Performed sensitivity analysis and discussed the optimization of productivity in

Section 5.3 and 5.4,

132

7. Enhanced CYCLONE model with consideration of soil compositions in Section
3.7,

8. Ran simulation with variety of soil compositions to obtain corresponding
productivity and presented the results in Appendix E and F,

9. Researched the correlation between soil composition and microtunneling

productivity in Section 5.5.

6.2 Conclusions based on the Simulation

1. CYCLONE models accurately represent the microtunneling process

From the validation of simulation results, It is clear that the averaged simulated
productivity is in a reasonable range of the productivity observed from the field. This
indicates that the model developments are successful. Such models can be used as a base

for future microtunneling productivity research.

2. Kolmogorov-Smirnov Goodness-of-Fit Test

The Kolmogorov-Smimov Goodness-of-Fit Test generates valid distributions based on a
relatively small set of duration data, which supported the success of the simulation. In
construction simulation, data collected from the field is normally fewer than data
collected from labs. Facing shortage of data, researchers have to perform well statistical
analysis to obtain modeling input as accurate as possible. The accuracy of input duration

data is critical to the validation of simulation results.

133

3. Soil Compositions Affecting Microtunneling Productivity

Based on the successfulness of CYCLONE model building and the Kolrnogorov-Smirnov
Goodness-of-Fit Test, the goal of studying correlations between soil compositions and
microtunneling productivity become achievable. The proportions of four types of soil
show strong linear correlations with productivity. Stemmed from such result, the
coefficients of proportion of each type of soil and microtunneling productivity has been
estimated. Through multi-linear regression, an experimental formula was developed to
reflect the soil composition effects on microtunneling productivity: Y =129.32946 +
0.06841*X1 - 0.28765*X2 - 0.30163*X3, where Y is time duration in minutes of each 8-
foot pipe section installation with microtunneling; X1 is percentage of clayey gravel in
the soil composition; X2 is percentage of sand in the soil composition; X3 is percentage
of silt in the soil composition. In the full-scale test in Louisiana Tech University, the
proportion of clay (X4) can be expressed as 100% minus other three proportions,
therefore only three coefficients have certain values, thus X4 does not exist in the
expression. The result is for general knowledge of microtunneling productivity. Since it is
highly associated with the candidate project’s conditions, it can not be used directly to
predict another microtunneling project without considering operations and soil

composition. Modifications have to be made to reflect any project condition variations.
The durations of jacking pipe sections in four different soils have been studied.iThe

conclusion is that clay and clayey gravel tend to have similar property, while the sand and

silt don’t have significant difference. The clay and gravel differ mainly on soil property

134

and friction. Possible explanation of close productivities in clay and gravel is that jacking
pipe speed in clay soil was impacted by other factors than soil property, for example, the
slurry pump incompatible with clay as recorded in Appendix B. Changing of slurry pump

could reflect shorter jacking time in clay in the model.

The limited times of simulation inevitably brought in skewness to the research. In the
simulations with the soil enhanced model, the portion of four different types of soil was
set to 25% each. Due to the random nature of the modeling structure, only two pipe
section went though silt, and eleven went through gravel, which skewed the simulation
results. However, if large number of simulations performed, the pipe sections in each
type of soil will be approximately 25%. The skewness is from the limit number of

simulations, instead of model structures.

4. Resource Limitations

Resource limitations have been studied through sensitivity analysis in WebCYCLONE.
The Jacking System is the resource with the highest utilization rate, in 92.17% of the
construction duration, it is kept busy. By changing the MTBM cutting head design more
appropriate to the soil conditions, productivity can be increased. This change will be
reflected in the model by decreasing J acking Pipe Section activity durations, instead of

adding more resource.

The supervisor was found another bottleneck of the Operation. That might come fi'om the

candidate project’s scientific experimental nature. The supervisor in the project takes a »

135

serious of responsibilities, which should be shared by peers. Introducing of another
supervisor will increase the productivity. In equipment, crane is the most significant
resource limitation. However, from a practical perspective, adding one crane would be
infeasible due to site limitation. In labor crews, crew B’s activities are mostly related to
jacking system, which keeps crew B occupied. If the MTBM cutting head design can be
improved to decrease J acking Pipe Section activity durations, adding Crew B will
become unnecessary. Crew A works with supervisor on most activities. Productivity can
be improved by adding Labor A with supervisor. The idling time of above bottle neck
resources are about 50% except Jacking System, conclusion can be drawn that the
microtunneling project in Louisiana Tech University was planned properly. There is no

need to adjust resource usage but improve the MTBM cutting head design.

6.3 Limitations of this Research

Major limitation of this study was introduced by the data collected. The data amount of
the scientific experimental project in Louisiana Tech University was relatively limited,
which is due to the high cost of microtunneling operation. Twenty-four pipe sections
were installed in the project within four different types of soil. Consequently, twenty-four
sets of data were collected, which are merely enough for distribution studies.
Furthermore, the data set was divided by four; only six sets of data are available for
installing pipe in each type of soil. Although the simulation results met the research
objective, the chance of confidentiality can not be eliminated. The limitation of data

could undermine the significance of this research.

136

Although cost factor is not considered in this research due to data limitation, cost must be
analyzed when adding any resources to microtunneling operations to achieve

optimization.

6.4 Recommendations and Areas of Future Research

Every project manger strives to achieve three goals on any project — to complete the
project on time with the highest possible quality at the lowest possible cost. Simulation is
a powerful tool for microtunneling project managers. It provides an appealing approach
to analyze and improve repetitive processes in microtunneling. The repetitive nature and
the complexity of microtunneling operations make it an ideal candidate for simulation
analysis. Simulation allows experimentation with costly microtunneling operations before
they are actually performed in the field. By experimenting with multiple scenarios,
equipment, labor force and materials, the operation may be streamlined to the project
manager’s needs. By using simulation the requirements of the operation and the
relationships between their resources can be studied in detail, thus enabling managers to
make more informed decisions at different stages of the project. Through better planning

and scheduling, the overall performance of a microtunneling project can be improved.

Simulation modeling may be done at different levels of detail based on the project
- manager’s needs. This allows the use of the same model for different operations since the
basic work tasks are similar. Microtunneling operations share many similarities with

respect to the pipe jacking process, the slurry removal process, the cleaning and recycle

137

of slurry, etc. Thus, a “template” model of a “standar ” microtunneling operation can be

modified with ease to incorporate variations in specific projects.

Since microtunneling operations are highly repetitive, small improvements in one cycle
could lead to considerable cost and/or time reductions in the full process. A database
containing activity durations and productivities on different soil conditions can be
interacted with simulation models to continuously improve model results, hence making
it an automated viable decision making tool for cost estimating and project planning

purposes.

When data is collected and such a database'built, graphic interface can be developed for
microtunneling operation simulation. Each piece of key components in microtunneling as
labor, equipment, and materials will be graphically represented on screen. A user
interactive simulation program with graphical appearance and menu or click-and-drop
commands can be developed. When microtunneling project managers choose different
operation options from the menu, the coding module in the system is triggered to
translate options into codes and integrate data from. the database. Such information tells
the system what and how resources are altered and the corresponding duration
distributions. It is sent to the simulation engine for simulating. The results will be
returned to an animation generator to project altered activity duration into animation on
the graphic user interface. Any changes made to the simulation model, resources, and
duration input will be reflected into animation simultaneously. Such software can be

loaded on the computer in microtunneling control unit, thus simplify the simulation use

138

for microtunneling project managers. Simulation tool will be popularized on
microtunneling project management. Microtunneling productivity optimization will be
achieved widely, fiirthermore lower the associated cost and improve microtunneling

competitiveness.

139

APPENDICES

140

APPENDIX A

Microtunneling Glossary1

Adapter Ring: In microtunneling, a fabricated ring usually made from steel, that serves
to mate the microtunneling machine to the first pipe section. This ring is intended to
create a waterproof seal between the machine and the spigot of the first joint.

Auger MTBM: A type of microtunnel-boring machine that uses auger flights to remove
the spoil through a separate casing placed through the product pipeline.

gag: A principal module that is part of a shield machine as in microtunneling or tunnel-
boring machines (TBMs). Trailing cans may be used, depending on the installation
dimensions required and the presence of an articulated joint to facilitate steering. May
also be referred to as a trailing tube.

Cased Bore: A bore in which a pipe, usually a steel sleeve, is inserted simultaneously
with the boring operation.

QsLng: A pipe to support a bore. Usually not a product pipe.

Control Console: An electronic unit inside a container located on the ground surface that
controls the operation of the microtunneling machine. The machine operator drives the
runnel from the control console. Electronic information is transmitted to the control
console fi'om the heading of the machine. This information includes head position,
steering angle, jacking force, progression rates, machine face torque, slurry and feed line
pressures, and laser position. Some control consoles are equipped with a computer that

tracks the data for a real-time analysis of the tunnel drive.

 

' ASCE (2001): Standard Construction Guidelines for Microtunneling

141

Crossing: Pipeline installation in which the primary purpose is to provide one or more
passages beneath a surface obstruction.

Compression Ring: A ring fitted between the end-bearing area of the'bell and spigot to
help distribute applied loads more uniformly. The compression ring is attached to the
trailing end of each pipe and is compressed between the pipe sections during jacking. The
compression rings compensate for slight misalignment, pipe ends that are not perfectly
square, gradual steering corrections, and other pipe irregularities. Also referred to as
packers.

Cutterhead: Any rotating tool or system of tools on a common support that excavates at
the face of a bore.

Driveshaft: See Jacking Shaft.

Entrance Seal: See Launch Seal

’ Ent_ry Ring: See Launch Seal

EPB Machine: Earth pressure balance type of microtunneling or tunneling machine in
which mechanical pressure is applied to the material at the face and controlled to provide
the correct counter-balance to earth pressures in order to prevent heave or subsidence.
The term is usually not applied to systems in which the primary counterbalance of earth
pressures is supplied by pressurized slurry.

Exit Seal: Same as launch seal except for retrieval of the machine at the reception shaft.
Used in high groundwater to prevent the loss of ground.

Exit Shaft: See Reception Shaft.

Grouting: The process of filling voids or modifying/improving ground conditions.

Grouting materials may be cementitious, chemical, or other mixtures. In microtunneling,

142

grouting may be used to fill voids around the pipe or shaft or to improve ground
conditions.

Interiack Pipes: Pipes specially designed for use with an intermediate jacking station.
Intermediate Jacking Station: A fabricated steel cylinder fitted with hydraulic jacks
that is incorporated into a pipeline between two pipe segments. Its function is to
distribute the jacking load over the pipe string on long drives.

Jacking Frame: A structural component that houses the hydraulic cylinders used to
propel the microtunneling machine and pipeline. The jacking frame serves to distribute
the thrust load to the pipeline and the reaction load to the shafi wall or thrust wall.

J acking Pipes: Pipes designed to be installed using pipe jacking techniques.

J acking Shaft: Excavation fiom which trenchless technology equipment is launched for
the installation or renovation of a pipeline, conduit, or cable. May incorporate a thrust
wall to spread reaction loads to the ground.

Jacking Shield: A fabricated steel cylinder fi'om within which the excavation is carried
out either by hand or by machine. Incorporated within the shield are facilities to allow it
to be adjusted to control line and grade.

Launch Seal: A mechanical seal, usually composed of a rubber flange that mounted to
the wall of the drive shaft. The flange seal is distened by the MTBM as it passes through,
creating a seal to prevent water or lubrication inflow into the shaft during tunneling
operation.

Lubrication: A fluid, normally bentonite, used to reduce jacking loads on the jacking
pipe.

Muck: Spoil or removal of same.

143

Obstruction: Any, object or feature that lies completely or partially within the cross-
section of the microtunnel and prevents continued forward progress.

Overcut: The annular space between the excavated hole and the outside diameter of the
jacking pipe.

PM: See Compression Ring.

mt Time Metppg: A multistage method of accurately installing a product pipe to line
and grade by use of a guided pilot tube followed by upsizing to install the product pipe.
Product Pipe: Pipe used for conveyance of water, gas, sewage, and other products and
services.

Push Ring Adapter: Mechanical structure mounted on the thrust ring to prevent the
thrust ring from coming in contact with the pipe collar and causing damage to the collar.
Receiving Shaft: See Reception Shaft.

Reception Shaft: Excavation into which the microtunneling equipment is driven and
recovered.

film: A fluid, normally water, used in a closed loop system for the removal of spoil
and for the balance of groundwater pressure during microtunneling.

Slurp! Chamber: Located behind the cutting head of a slurry microtunneling machine, a
chamber in which excavated material is mixed with slurry for transport to the surface.
Slurp! Line: A series of hoses or pipes that transport tunnel muck and slurry from the
face of a slurry microtunneling machine to the ground surface for separation.

Slurry Separation: A process in which excavated material is separated from the

circulation slurry.

144

m: Mechanical structure used to transfer the jacking load from the jacking thrust
ring to the pipe and used to accommodate lengths of pipe that are longer than the stroke
length of the jacks.

SM]; Earth, rock, and other materials removed during installation.

Thrust Ring: A fabricated ring that is mounted on the face of the jacking frame. It is
intended to transfer the jacking load from the jacking frame to the thrust-bearing area of
the pipe section being jacked.

Trenchless Technology: Techniques for utility or other line installation, replacement,
renovation, inspection, leak location and detection, with minimum excavation fiom the
ground surface.

Tunneling: A construction method of excavating an opening beneath the ground without
continuous disturbance of the ground surface and of large enough diameter to allow
individuals access and erection of a ground support system at the location of material
excavation.

Uncased Bore: Any bore without a lining or pipe inserted, i.e., self-supporting, whether
temporary or permanent.

water Jets: Internal cleaning mechanism of the cutterhead in which hi gh-pressure water

is sprayed from nozzles to help remove cohesive soils.

145

APPENDIX B

Duration Data Collected from the Louisiana Tech University Microtunneling

Project (Najafi, 1993)

A

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Durations for jacking pipe sections
. Start Finish urationl
Pipe No. Date Time Time (min) Notes
Boring 1100 1130 From 130 to 3'45 pm reconnect adapters
machine 6/16/ 1992 ' ° 30 ' . '. . ’
AM AM electnc lrnes and extens1ons.
adapters
Boring . _ . .
machine 6/17/1992 3:45 PM 4: 10 PM 25 Fm“ 3'45 t° 4'10 pm “3mm“ “mg f“
the machrne -
adapters
1 6/17/1992 8:50 AM 9:43 AM 53 Boring within clay section
2 6/17/1992 1:35 PM 3:07 PM 92 Boring within clay section
3 6/18/1992 8:18 AM 9:46 AM 88 Boring within clay section
4(with gripper) 6/18/1992 1:07 PM 2:32 PM 85 Boring within clay section
Boring within clay section (average duration
5 6/18/1992 3:40 PM 4:52 PM 72 = 74 rrrinutes and average speed = 1.3
inch/minutes)
6 6/19/1992 8: 12 AM 8:46 AM 34 Boring machine began entering inside silt.
. 10:23
7 6/19/1992 9.56 AM AM 27
11:20 12:01
8 6/19/1992 AM AM 41
From 2:43 to 2:51 pm machine was stopped
because slurry back pressure was high and
flow volume was low. From 2:53 to 3:53 pm
9(with gripper) 6/19/1992 2:40 PM 4:34 PM 114 wood pieces in the silt clogged the slurry
pump inside pit. Same problem happened
from 3:57 to 4:00 and from 4:17 to 4:21 and
from 4:26 to 4:28 pm.
10 6/20/1992 8:14 AM 8:39 AM 25
. 10:06
11 6/20/1992 9.39 AM AM 27
10:35 10:53 . . . .
12 6/20/1992 AM AM 18 Bonng wrtlun sand sectron
13 6/22/1992 8:50 AM 9:40 AM 50 9:05 to 9:25 jacking was stopped for crack
sealant to dry up.
14(w1th 6/22/1992 11:09 11:45 36
gripper) AM AM
15 6/22/1992 2:08 AM 2:20 AM 12
16 6/22/1992 3:30 AM 3:53 AM 23
17 6/22/1992 4:50 PM 5:09 PM 19 B°mg ”Chmiggt‘i‘gjd Clayey gravel

 

 

146

 

 

 

 

 

 

 

 

8:26 to 8:35 jacking pressure obstruction
8:40 to 9:08 slurry line obstruction. 9:11 to
18 6/23/1992 8:20 AM 9:57 AM 97 9:30 slurry line obstruction. Note: 28 liters
of lubricant (bentonite) used to push this
section
1 1:12 1 1:54 . .
19 6/23/1992 AM AM 42 85 lrters of lubrrcant was used.
20 6/23/1992 1:53 PM 2:34 PM 41 93 liters of lubricant was used.
21 6/23/1992 3:33 PM 5:29 PM 116 4:05 t° 4‘43 9‘“ it“ Slurry Pm“? “‘s‘d" the
prt clogged.
22 6/24/1992 8:09 AM 9:25 AM 76 Slurry pump inside the pit clogged
10:15 . 10:24 to 10:41 amthe slurry pump inside
23 6/24/1992 AM 1 1.15 60 the pit clogged
At 1:53 pm boring machine entered the clay
zone. Total jacking force 39 ton. Jacking
24 6/24/1992 1:16 PM 2:21 PM 65 force on the plastic pipe 2 tons. Maximum
jacking load on plastic pipe occurred at pipe
No.12 and at a load of 3.5 tons.

 

 

 

 

 

 

147

 

 

Durations for installation of the pipe section on the guard rail (including installation of cables and
hoses and settin up the laser)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

. Start Finish Duration
Prpe No. Date Time Time (min) Notes
1 6/17/1992 8:50 AM 9:43 AM 53
2 6/17/1992 10:00 AM 12:15 AM 135 me 10“” ‘° ”5.0 “.1”.wa“‘“g ‘° 3““
the prpe jomt.
At 3:25 pm the desandman was
3 6/18/1992 3:25 PM 4:25 PM 60 discharged. Grinding the joint from 3:28
to 3:31 pm
Fitting the pipe joints together from 11:10
. . . _ to 11:38 am Gripper installation inside
4(w1th gripper) 6/18/1992 10.22 AM 11.47 AM 85 plastic pipe from 9:00 to 9:15 am,
checking gripper from 9: 16 to 9:30 am
. . Laser installation from 3:32 to 3:38 pm.
5 6/18/1992 2'49 PM 33.8 PM 49 Desandman was discharged at 3:30 pm
6 6/18/1992 5:05 PM 5:47 PM 42 Laser was not 1nstalled. Desandman was
drscharged.
7 6/19/1992 9:04 AM 9:55 AM 51 Laser installation from 9:46 to 9:55 am
8 6/19/1992 10:36AM 11:20AM 44
9 6/19/1992 1:37 PM 2:40 PM 63
10 6/19/1992 4:52 AM 5:27 AM 35
11 6/20/1992 9:00 AM 9:37 AM 37
12 6/20/1992 10:25 AM 11:30 AM 65 5 minutes for pipe measurements.
13 6/20/1992 12:06 PM 12:42 PM 36 A 3m". 9”“ was mm" When the 1”?"
jomts were fitted together.
141““ 6/22/1992 10:05 AM 11:09 AM 64
gripper) .
15 6/22/1992 12:04 PM 12:32 PM 28
16 6/22/1992 2:54 PM 3:30 PM 36
17 6/22/1992 4:08 PM 4:50 PM 42
18 6/22/1992 5:22 PM 5:55 PM 33 Laser to be set up in the morning.
i _ . Slurry pump was disassembled and
19 6/23/1992 10.16 AM 10.55 AM 39 checked for obstructions
20 6/23/1992 12:10 PM 12:42 PM 32
21 6/23/1992 2:46 PM 3:32 PM 56
22 6/23/1992 5:38 PM 6:07 PM 29 Laser to be set up in the morning.
23 6/24/1992 9:40 AM 10:15 AM 35
24 6/24/1992 11:27 AM 12:00 AM 33

 

 

 

 

 

 

 

148

 

Durations for installation of the casings and grippers inside the plastic pipe (including time necessary

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

to install two slurry pipes, two Jullback rods and check the air grippers)
Pipe No. Date 3.2:: 22:23: D333?“ Notes
1 6/16/1992 4:47 PM 4:57 PM 10
2 6/17/1992 9:44 AM 9:57 AM 13
3 6/17/1992 2:02 PM 2:12 PM 10
Gripper installation inside plastic pipe
4(with gripper) 6/18/1992 9:00 AM 9:30 AM 30 from 9:00 to 9:15 am, checking gripper
from 9:16 to 9:30 am.
5 6/18/1992 2:15 PM 2:25 PM 10
6 6/18/1992 4:47 PM 4:52 PM 5
7 6/19/1992 8:52 AM 8:58 AM 6
8 6/19/1992 10:07AM 10:14AM 7
9(with gripper) 6/19/1992 11:50 AM 12:05 PM 15 From 11:55 to 12:05 checking gripper
10 6/19/1992 4:00 PM 4:08 PM 8
11 6/20/1992 8:35 AM 8:40 AM 5
12 6/20/1992 9:42 AM 9:50 AM 8
13 6/20/1992 10:40 AM 10:47 AM 7
glfigretrl; 6/22/1992 9:35 AM 9:50 AM 15 10 minutes for checking the gripper
15 6/22/1992 11:40 AM 11:45 AM 5
16 6/22/1992 2:31 PM 2:38 PM 7
17 6/22/1992 3:48 PM 3:55 PM . 7
18 6/22/1992 5:07 PM 5:19 PM 12
19 6/23/1992 9:20 AM 9:26 AM 6
20 6/23/1992 11:52 AM 11:58 AM 6 g
21 6/23/1992 5:00 PM 5:06 PM 6 Wrong pipe loaded with casing
22 6/23/1992 3:53 PM 3:56 PM 3
23 6/24/1992 8:03 AM 8:08 AM 5
24 6/24/1992 10:52 AM 10:57 AM 5

 

149

 

 

Durations for retraction of Jacks (including dismantling of cables and hoses)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Pipe No. Date in: F123: 0:32;)“ Notes
1 6/17/1992 9:44 AM 9:55 AM 11
2 6/17/1992 3:10 PM 3:25PM 15
3 6/18/1992 9:47 AM 10:14 AM 27
4(with gripper) 6/18/1992 2:35 PM 2:47 PM 12
5 6/18/1992 4:56 PM 5:04 PM 8
6 6/19/1992 8:47 AM 9:00 AM 13
7 6/19/1992 10:24 AM 10:33 AM 9
8 6/19/1992 1:18PM 1:35PM 17
9(with gripper) 6/19/1992 4:37 PM 4:51 PM 14
10 6/20/1992 8:44 AM 8:57 AM 13
11 6/20/1992 10:15 AM 10:22 AM 7
12 6/20/1992 11:53 AM 12:04 PM 11 Taking off laser fi'om 10:53 to 10:55 am.
13 6/22/1992 9:40 AM 9:55 AM 15
14(with
gripper) ‘ 6/22/1992 11:50 AM 12:03 AM 13
15 6/22/1992 2:29 PM 2:45 PM 16
16 6/22/1992 3:58 PM 4:06 PM 8
17 6/22/1992 5:09 PM 5:17 PM 8
18 6/23/1992 10:02AM 10:12AM 10
19 6/23/1992 12:00PM 12:10PM 10
20 6/23/1992 2:35 PM 2:42 PM 7
21 6/23/1992 5:30 PM 5:37 PM 7
22 6/24/1992 9:27 AM 9:35 AM 8
23 6/24/1992 11:17AM 11:25AM
24 N/A N/A N/A ' N/A

 

 

 

 

 

 

150

 

 

Summary of Production Rates

 

 

 

 

 

 

 

transit

Type of Work Time Required
Opening the crates and installation of 3 da
all rrucrotunnelrng equ1pment
Checkrng the. nucrotunnelrng _ ‘ 1 day
equ1pment
Average hoisting time 2 min.
Average time for installation of 8 8 min.
casing inside PVC pipe '
Average time for installation of PVC
pipe (with casing) on the guide rails 4 .
. . . . 3 mm.
(mcludrng connectron of slurry prpes,
hoses and cables)
Average trme for sett1ng up of laser 10 min.

 

Average time for pushing the pipe

 

 

 

 

Clay 33 mm. (1.3 ir1./min.)

Silt 101.6 mrn/min. (4.0 in./rnin.)

Sand . 134.6 mm/min. (5.3 in./min.)
Clayey Gravel 43.2 mm/min. (1.7 in./min.)

 

Average time for retraction of jacks
(including dismantling of cables and
hoses)

11.6min.

 

Average cycle time for installation of an 8-ft section of PVC pipe in:

 

 

 

 

Clay 169 min.

Silt 97 min.

Sand 91 min.
Clayey Gravel 130 min.

 

Average time for pulling back of one
liner casing and dismantling of all

20 min. (10 min. to retract the

 

 

 

 

slurry pipes, hoses and cables for jacks)
each PVC pipe section
Drsmantlmg, washing and crating of 2 days
equ1pment
Loading equipment 1 day

 

 

151

APPENDIX C

Coding of the Prototype CYCLONE Microtunneling Simulation Model:

Input Model

Line 1: NAME MICROTUNNELING PROCESS LENGTH 10000 CYCLES 30

Line 2: NETWORK INPUT

Line 3: 1 COM 'DISCHARGE & REFILL DESANDMAN' SET 1 PRE 33 18 14 FOL 18
14 24

Line 4: 2 COM 'MIX LUBRICATION' SET 2 PRE 13 22 32 FOL 13 21 22

Line 5: 3 COM 'DISMANTLE CABLES & HOSES' SET 3 PRE 34 14 18 FOL 17 23 14
18 39 99 i I
Line 6: 4 COM 'EMPTY SPOIL TANK' SET 4 PRE 31 19 20 FOL 27 19 20

Line 7: 5 COM 'PIPE SECTION INSTALL ON GUARD RAIL' SET 5 PRE 30 18 14 35
24 23 2127 FOL 41 1814 42

Line 8: 6 COM 'LOWER SECTION INTO SHAFT ' SET 6 PRE 29 18 FOL 30 18

Line 9: 7 COM 'ADIUST AIR GRIPPER' SET 7 PRE 13 2614 FOL 13 1415

Line 10: 8 COM 'INSTALL & CHECK AIR GRIPPER' SET 8 PRE 13 25 14 FOL 13 14
43 '

Line 11: 9 COM ’ATTACH SECTION TO CRANE' SET 9 PRE 28 13 17 16 15 FOL 40
13 12

Line 12: 10 COM 'BRING SECTION & INSTALL CASING' SET 10 PRE 11 13 12
FOL 36 13 28

Line 13: 11 QUE 'SECTION ON STORAGE'

152

Line 14:

Line 15:

Line 16:

Line 17:

Line 18:

Line 19:

Line 20:

Line 21:

Line 22:

Line 23:

Line 24:

Line 25:

Line 26:

Line 27:

Line 28:

Line 29:

Line 30:

Line 31:

Line 32:

Line 33:

Line 34:

Line 35:

Line 36:

12 QUE POSITION AVAILABLE'
13 QUE 'LABOR A IDLE'

14 QUE SUPERVISOR IDLE'

15 QUE 'AIR GRIPPER READY' GEN 5
16 QUE 'CRANE IDLE'

17 QUE 'CONTROL CRANE'

18 QUE 'LABOR B IDLE'

19 QUE 'TRUCK IDLE'

20 QUE 'BACKHOE IDLE'

21 QUE 'LUBRICATION READY' GEN 4
22 QUE 'BENTONITE READY' ~

23 QUE 'JACKING SYSTEM IDLE'

24 QUE 'WATER READY' GEN 4

25 QUE 'NEED AIR GRIPPER'

26 QUE 'GRIPPER NEED ADJUST'

27 QUE 'SPOIL TANK NOT FULL' GEN 4
28 QUE 'POSITION OCCUPIED'

29 QUE 'SECTION READY'

30 QUE 'SECTION READY'

31 QUE 'SPOIL TANK FULL'

32 QUE 'NEED LUBRICATION'

33 QUE 'DESANDMAN READY TO DISCHARGE'

34 QUE 'SECTION IN PLACE'

153

Line 37:
Line 38:
Line 39:
Line 40:
Line 41:
Line 42:
Line 43:
Line 44:
Line 45:
Line 46:
Line 47:
Line 48:
Line 49:
Line 50:
Line 51:
Line 52:
Line 53:
Line 54:
Line 55:
Line 56:
Line 57:
Line 58:

Line 59:

35 QUE 'CABLE HOSE LASER READY'

36 FUN CON 5 FOL 25

37 FUN CON 4 FOL 32

38 FUN CON 4 FOL 31

39 FUN CON 4 FOL 33

40 NOR 'LIFT SECTION TO POSITION SET 40 FOL 29
41 NOR 'CRANE RETURNS SET 41 FOL 16

42 NOR 'JACK PIPE SECTION SET 42 FOL 34 37 38
43 NOR 'DUMMY' SET 43 FOL 26 15 PROBABILITY .33 .67
99 FUN COU FOL 35 QUA 1

DURATION INPUT

SETITR1101215

SET 2 TRI 25 30 35

SET 3 BET 7 33 0.643 3.02

SET 4 TRI 20 30 35

SET 5 BETA 28 80 0.761 1.841

SET 6 UNI 1 2

SET 7 UNI 10 15

SET 8 UNI 10 15

SET 9 DET 2

SET 10 TRI 2 5 15

SET 40 DET 1

SET 41 DET 2

154

Line 60

Line 61

Line 62

Line 63

Line 64

Line 65

Line 66

Line 67

Line 68

Line 69

Line 70

Line 71

Line 72

Line 73

Line 74

Line 75

Line 76

Line 77

Line 78

: SET 42 BETA 12 102 0.854 1.403

: SET 43 DET 0

: RESOURCE INPUT

: 30 'PIPE SECTION' AT 11

: 1 'POSITION' AT 12

: 1 'LABOR' AT 13

: 1 'SUPERVISOR' AT 14

: l 'GRIPPER READY SIGNAL' AT 15

: 1 'CRANE' AT 16

: 1 'CRANE CONTROL SIGNAL' AT 17

: 1 'LABOR' AT 18

: 1 'TRUCK' AT 19

: 1 'BACKHOE' AT 20

: 1 'LUBRICATION READY SIGNAL' AT 21
: 1 'BENTONITE READY SIGNAL' AT 22

: 1 'JACKING SYSTEM' AT 23

: 1 'WATER READY SIGNAL' AT 24

: l 'SPOIL TANK NOT FULL SIGNAL' AT 27

: l 'CABLE HOSE LASER READY SIGNAL' AT 35

155

APPENDIX D

Coding of the CYCLONE Microtunneling Simulation Model with Soil
Condition Enhancement:

Input Model

Line 1: NAME MICROTUNNELING PROCESS IN DIFFERENT SOILS LENGTH
10000 CYCLES 30

Line 2: NETWORK INPUT

Line 3: 1 COM 'DISCHARGE & REFILL DESANDMAN' SET 1 PRE 33 18 14 24 FOL
18 14 24

Line 4: 2 COM 'MIX LUBRICATION' SET 2 PRE 13 22 32 FOL 13 21 22

Line 5: 3 COM 'DISMANTLE CABLES & HOSES 1' SET 3 PRE 34 14 18 FOL 17 23
14 18 51 24 99

Line 6: 44, COM 'DISMANTLE CABLES & HOSES 2' SET 13 PRE 47 14 18 FOL 17
231418 5124 99

Line 7: 45 COM 'DISMANT LE CABLES & HOSES 3' SET 23 PRE 48 14 18 FOL 17 ,
231418 5124 99

Line 8: 46 COM 'DISMANTLE CABLES & HOSES 4' SET 33 PRE 49 14 18 FOL 17
231418 50 24 99

Line 9: 4 COM 'EMPTY SPOIL TANK' SET 4 PRE 31 19 20 FOL 27 19 20

Line 10: 5 COM 'PIPE SECTION INSTALL ON GUARD RAIL' SET 5 PRE 30 18 14
35 24 232127 FOL 41 1814 52

Line 11: 6 COM 'LOWER SECTION INTO SHAFT' SET 6 PRE 29 18 FOL 30 18

Line 12:7 COM 'ADJUST AIR GRIPPER' SET 7 PRE 13 26 14 FOL 13 1415

156

Line 13: 8 COM 'WSTALL & CHECK AIR GRIPPER' SET 8 PRE 13 25 14 FOL l3 14

43

Line 14: 9 COM 'ATTACH SECTION TO CRANE' SET 9 PRE 28 13 17 16 15 FOL 40

1312

Line 15:

10 COM 'BRING SECTION & INSTALL CASING' SET 10 PRE ll 13 12

FOL 36 13 28

Line 16

Line 17:

Line 18:

Line 19:

Line 20:

Line 21:

Line 22:

Line 23:

Line 24:

Line 25:

Line 26:

Line 27:

Line 28:

Line 29:

Line 30:

Line 31:

Line 32:

11 QUE 'SECTION ON STORAGE'
12 QUE POSITION AVAILABLE

13 QUE 'LABOR A IDLE'

14 QUE SUPERVISOR IDLE'

15 QUE 'AIR GRIPPER READY' GEN 5
16 QUE 'CRANE IDLE'

17 QUE 'CONTROL CRANE'

18 QUE 'LABOR B IDLE'

19 QUE 'TRUCK IDLE'

20 QUE 'BACKHOE IDLE'

21 QUE 'LUBRICATION READY' GEN 4
22 QUE 'BENTONITE READY'

23 QUE 'JACKING SYSTEM IDLE'

24 QUE 'WATER READY'

25 QUE 'NEED AIR GRIPPER'

26 QUE 'GRIPPER NEED ADIUST'

27 QUE 'SPOIL TANK NOT FULL' GEN 4

157

Line 33:

Line 34:

Line 35:

Line 36:

Line 37 :

Line 38:

Line 39:

Line 40:

Line 41:

Line 42

Line 43:
Line 44:
Line 45:
Line 46:
Line 47:
Line 48:
Line 49:
Line 50:
Line 51:
Line 52:
Line 53:
Line 54:

Line 55:

28 QUE POSITION OCCUPIED

29 QUE 'SECTION READY'

30 QUE 'SECTION READY'

31 QUE 'SPOIL TANK FULL'

32 QUE 'NEED LUBRICATION'

33 QUE 'DESANDMAN READY TO DISCHARGE'
34 QUE 'SECTION IN PLACE 1'

47 QUE 'SECTION IN PLACE 2'

48 QUE 'SECTION IN PLACE 3'

: 49 QUE 'SECTION IN PLACE 4'

35 QUE 'CABLE HOSE LASER READY'

36 FUN CON 5 FOL 25

37 FUN CON 4 FOL 32

38 FUN CON 4 FOL 31

50 FUN CON 2 FOL 33

51 FUN CON 3 FOL 50

40 NOR 'LIFT SECTION TO POSITION‘ SET 40 FOL 29
41 NOR 'CRANE RETURNS' SET 41 FOL 16

42 NOR 'JACK PIPE SECTION 1' SET 42 FOL 34 37 38
57 NOR 'JACK PIPE SECTION 2' SET 57 FOL 47 37 38
58 NOR 'JACK PIPE SECTION 3' SET 58 FOL 48 37 38
59 NOR 'JACK PIPE SECTION 4' SET 59 FOL 49 37 38

43 NOR 'DUMMY' SET 43 FOL 26 15 PROBABILITY .33 .67

158

Line 56:
Line 57:
Line 58:
Line 59:
Line 60:
Line 61:
Line 62:
Line 63:
Line 64:
Line 65:
Line 66:
Line67:
Line 68:
Line 69:
Line 70:
Line 71:
Line 72:
Line 73:
Line 74:
Line 75:
Line 76:
Line 77:

Line 78:

52 NOR DUMMY 1' SET 44 FOL 53 54 55 56 PROBABILITY .25 .25 .25 .25
53 NOR 'DUMMY SOIL TYPE CLAYEY GRAVEL' SET 45 FOL 42
54 NOR 'DUMMY SOIL TYPE SAND' SET 46 FOL 57
55 NOR DUMMY SOIL TYPE SILT' SET 47 FOL 58
56 NOR 'DUMMY SOIL TYPE CLAY' SET 48 FOL 59
99 FUN COU FOL 35 QUA 1

DURATION INPUT

SET 1 TRI 10 12 15

SET 2 TRI 25 30 35

SET 3 BET 7 33 0.643 3.02

SET 4 TRI 20 30 35

SET 5 BETA 28 80 0.761 1.841

SET 6 UNI 1 2

SET 7 UNI 10 15

SET 8 UNI 10 15

SET 9 DET 2

SET 10 TRI 2 5 15

SET 13 BET 7 33 0.643 3.02

SET 23 BET 7 33 0.643 3.02

SET 33 BET 7 33 0.643 3.02

SET 40 DET 1

SET 41 DET 2

SET 42 BETA 26 88 1.075 1.041

159

Line 79:

Line 80:

Line 81:

Line 82:

Line 83:

Line 84:

Line 85:

Line 86:

Line 87:

Line 88

Line 89:

Line 90

Line 91

Line 92

Line 93

Line 94

Line 95

Line 96

Line 97

Line 98

Line 99

SET 43 DET 0

SET 44 DET 0

SET 45 DET 0

SET 46 DET 0

SET 47 DET 0

SET 48 DET 0

SET 57 BETA 12 46 0.613 0.793

SET 58 BETA 17 510.989 1.775

SET 59 BETA 19 92 0.781 0.323

: RESOURCE INPUT

30 PIPE SECTION' AT 11

: 1 'POSITION' AT 12

: 1 'LABOR' AT 13

: 1 'SUPERVISOR' AT 14

: 1 'GRIPPER READY SIGNAL' AT 15
: 1 'CRANE' AT 16

: 1 CRANE CONTROL SIGNAL' AT 17
: 1 'LABOR' AT 18

: 1 'TRUCK' AT 19

: 1 'BACKHOE' AT 20

: 1 'LUBRICATION READY SIGNAL' AT 21

Line 100: 1 'BENTONITE READY SIGNAL' AT 22

Line 10

l: l 'JACKING SYSTEM' AT 23

160

Line 102: 1 'WATER READY SIGNAL' AT 24
Line 103: l 'SPOIL TANK NOT FULL SIGNAL' AT 27

Line 104: 1 'CABLE HOSE LASER READY SIGNAL' AT 35

161

APPENDIX E

Simulation Results with Prototype CYCLONE Microtunneling model:

Simulation Run Times: 30

 

1 MICROTUNNELING PROCESS
1' " WWPRODUCTIVITY INFORMATION
Sim. Time 1C§616WN6 Productrvrty Per Time Unrt
160.4 1 1 0. 006234
" 0.007120 1
W" "0.008899T”
0.010080 1
0.007940
0.007984 .,
0.007794
0.008265
0008442 ' 7'
0. 008367
WWWO 00865TWWW'
” 0. 008929
13 0.009121

'14 0.009353 '

 

 

 

1
l
l

 

mi '
w: 1
'x)
~

1
|
1
1

 

 

\1 01 11:14:. wSN'

I
1
l

-.._.__...... _.. ~.,‘-._... .

 

\ooo

 

O

 

n—oiu—t
N.—

l
1

 

 

 

 

 

 

15504 *' 1‘5 WT0009675WW'
16 WW 0.009955

"17067“ W "1T" §W 0. 009961
_ w a... ._.. -.., .... ..-....,........... i

l
‘ 18 0009986
1 19 0.009814
1 20 0.009847 2
1 21 ” W“70.0'09'5'49Wm"W'
1 22 0.009265
W. 1"”23 " 0.009195
l
1
l
l
l
l

 

 

 

 

 

2.4 1 0.00912T _ ,_
25 0.009206
26 0.009224

W27' “0009282? "
28 0. 009293

-_........—.. -___._.—.... ...a -.W ....—..___m ..._~.. ...,-...—

 

 

 

 

 

29 0009147
30 0.009272 '

 

162

 

 

 

 

1W "WWW'WWWW'WWWWW MICROTUNNELING PROCESS W W
1 PRODUCTIVITY INFORMATION :
1 Total Sim. Time Unit 1 Cycle NO. QW Productivity (per time unit)

3235.4 1

30

0.0092724093 16360385

 

W CYCLONE ACTIVE ELEMENTS STATISTICS INFORMATION

 

 

 

WW Activity NT Name 1 Access Average Maximum Minimum
‘ Type ' 1Counts Duration Duration Duration
' ' DISCHARGE& 1
COMBI 1 REFILL 7 12.3 14.2 10.8
DESANDMAN
”COMBI 12 1M1XLUBRICATIONW1W 7 299W 1 33.5 126.8 ' W
WWW~ DISMANTLE r7
COMBI 1 3 1 CABLES &HOSES 1 30 11.6 29.1 7.1
.WWWWW‘W 1 1“ WW W WWW WWWWWWWWW
; . EMPTY SPOIL -
1 1 1 g
COMBI 14W 1 TANK 7 28.1 33.2 23.1
PIPE SECTION W
COMBI 5 INSTALL ON 30 41.9 77.8 28.4
GUARD RAIL 1
WWW LOWER SECTION 1" “W
COMBI 6 1 INTO SHAFT 1 30 1.4 2.0 1.0
E'W WW ADJUST AIR 1 '
COMBI 7 GRIPPER 4 13.2 14.8 1 11.1
WW INSTALL & CHECK WEWWW W
COMBI 8 AIR GRIPPER 6 1 12.5 14.8 1 10.3
ATTACH SECTION 1 1
COMBI 9 To CRANE 30 1 2.0 2.0 1 2.0
W BRING SECTION& 1
COMBI 10 INSTALL CASING 30 1 6.6 12.6 2.3
{WWW—WW LIFT SECTION TO W1 .1 W
NORMAL 40 POSITION 30 1 1.0 1.0 1 1.0
NORMAL 41 1 CRANERETURNS 1W 30 ”230' 120W 2.0
JACK PIPE 1 ‘

1
1NORMAL W131 SECTION 1 30 44.3 1 100.7 1 13.3
NORMAL W151 DUMMY 1 6 0.0 1 0.0 1 0.0 ._

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

163

 

r. ....
l

 

 

 

 

 

 

 

WWWWWWWWWWW Average Max. Times 1y Total Average UnitSW1
Type .No. Name Units Idle not I d1e Sim Wt at '1
Idle Units empty Time Time end
WWW SEWEfiONWWON W 1 WW" WWW
QUEUE111 STORAGE 14.6 130 3036.3 93.85 3235.4 737.2 0
r 3,. -. . -133 .... 3-... 1333.3- 3 3.4 ...--.. ..-. ..._. .. . - --H..-..._-~~._ W... .. . lW
' POSITION 1 1 101 a
QUEUE 12 AVAILABLE 1 0.0 1 1 0.0 10.00 3235.4 0.0 1 »
WW WWWWW LABORA " 1 'WWW WW‘
QUEUE 13 IDLE 1 0.8 1 1 2577717967 3235.4. 33.0 1
'7 I“ 1 1
QUEUE 14 SUPERVISOR: 0.4 1 1 11416.8 43.79 3235.4 18.2 ' 1
IDLE 1
...-333.3 _3- 1.. 1
1 GEN 15 “1113;111:5131 3.4 1 6 131704 97.99 3235.4 334.2 1 5
1QUEUE1161CRANEIDLE1 0.5 f 1 11..75551542613235.41566 1
WW” CONTROL ‘1 1 1
1QUEUE11 1 CRANE 1 0.0 1 .1157.0 4.85 3235.4 5.1 1 1
1. 1-33.3 3.3-3.1 3.3 1.333
LABORB 1 1
1QUEUE1181 IDLE 1 0.5 1 11502.3 46.43 3235.4 15.3 1 1
1QUEUE119 TRUCK IDLEWEW 0.9 1 1 128352187631323324135414WWEW‘1WW
1QUEUE 20 BACKHOE 1 0.9 1 1 2835.2187.63 3235.4 354.4 1 1
IDLE 1 - 1 1
1.-..3..._3._..3..-- ~~~—-—-’“"--; ------———r-—------~ ‘- ‘1 1—'-“~--~~-~--° ‘——'“
1 GEN 121 WLUBgEgg'ON 1.6 4 2466.117622132354 160.6 1 2
1 1
1 3 BENTONITE -113_3_---_3_ 1
1QUEUE 22 READY 1 0.9 1 2825.1187.3213235.4 353.1 1 1
“r" r"— 1 ' r
JACKING 1 : 1 1
1
QUEUE 23 SYSTEM IDLE1 0.1 1 1289.5 18.95 13235.4 9.3 1
1 WATER 1 1 1 1
GEN .12: READY 1:3” :1-“ 2532.2178.2713235.41 168.5 2
NEED AIR
QUEUE 25 GRIPPER 0.1 1 203.616.29 3235.4 33.9 0
33313GRI3PPER 3-3-3-333..-
QUEUE 26 NEED ADJUST 0.0 1 0.0 W10.00 3235.4 0.0 1 0 .
g.— .
SPOILTANK 1
1 GEN 27 NOT FULL 1.7 4 2478517661 3235.4 162.1 2 .
WWW 1W POSITION WW" 1 W WWW" 1WWWW1
QUEUE128 OCCUPIED 0.9 1 2914.9 90.09 3235.4 97.2 1 0
3.3333... ______ SECTION - _ 3 3-
QUEUE 29 READY 0.0 1 0.0 0.00 3235.4 0.0 0
1'“ ,__.._,__ "_"_' :'
SECTION 1 1
QUEUE 30 READY 0.0 1 1 1 0.0 0.00 3235.4 0.0 0
..____._F___
QUEUE 31 31301113ng 0.0 1 1 1 0.0 0.00 3235.4 0.0 o
WOWIWJWEWIWIEWW 32 NEED 1.---.(1-;---1—.__l~-1.403416-$g23541 00 W o
1 LUBRICATION ' 1 ' ° 1 ° '

 

 

 

 

 

1 CYCLONE PASSIVE ELEMENTS STATISTICS INFORMATION

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

164

 

sQUEUE§ 33

l 1'
I 1
‘1 I

. __-_-L.,___f-._--..

EQUEUE 34 I

§_,....-___.. E
{QUEUE L 35

.'
I-
I 1
' l

 

-~ _- .-.

’ - ~~.v- ...-....-.“ "...—‘nafi '—~-. -....p— .- a - —-—

 

{DESANDMAN ‘ { ;
READYTO 5 0.0 g 1 0.0 10001323541 0.0 '
DISCHARGE g i g i
Sfié'l‘mileN E ” I Tm“;
PLACE i 0.0 { 1 11.7 !O.36 E32354i 04
CABLE HOSE " 1“ " g 1 1:.
LASER g 0.1 1 1 289.5 g8.95 3235.4! i
READY I 3 1 l

 

 

 

f M ' TRXCEINFORMATION" ” " ”

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sim Activity
Time No. Type Name
1 NWWW’ " --.,..--_____ BRING
SECTION&
4.9 10 COMBI INSTALL
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6.9 9 COMBI SECTION TO
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. 7.9 40 NORMAL To POSITION;
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9.1 6 COMBI SECTION INTOE
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19.5 10 COMBI INSTALL

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N FIRE SEETTONFE .
67.3 5 COMBI INSTALL ON
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69.3 41 NORMAL RETURNS
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143.4 42 NORMAL SECTION .
E ..- ' DISMAN'EEE
160.4 3 COMBI CABLES& '
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{166.4f 99""l""COUNTE" R“ "NM”:"W"
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162.4 9 COMBI SECTION TO
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163.4 40 NORMAL To POSITION;
' E "— LOWER :
165.4 6 COMBI SECTION INTO?
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172 7! [ COMBI { BRING .

 

165

212.0

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268.7

280.9

 

 

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99 l

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INSTALL
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282.9

9

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283.9

285.7

337.1

 

 

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40

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41

3

 

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I 337.13r

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339.1

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340.1

341.7

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345.4

 

 

10

 

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166

 

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I 371.7 5 I COMBI INSTALL ON E
E GUARD RAIL
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I 373.7 41 E NORMAL E RETURNS
W WW I " INSTALL&
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I 382.7I 43 I NORMAL I DUMMY
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I 389.4E 42 E NORMAL E SECTION
I 389.4 I 37 KEONSOLIDATEI -

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I 396.8I 39 ICONSOLIDATEI -

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408.3 1 COMBI REFILL E
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415.1 4 COMBI TANK ..
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417.7 2 COMBI LUBRICATIONI
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419.7 9 COMBI SECTION TO 5
I CRANE
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420.7 40 NORMAL To PosmONE
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422.1 6 COMBI SECTION INTOE
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423.3 10 COMBI INSTALL 1
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I -_ W WWW PIPE SECTION I
499.9 5 COMBI INSTALL ON I
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501.9 41 NORMAL RETURNS

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600.6 42 NORMAL SECTION

I629.7I 3 I COMBI IDISMANTLE

 

167

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

168

I WIW WEWW"W W. CABLES&
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631.7 9 COMBI SECTION TO
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632.73 40 NORMAL ITOPOSITION‘;
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636.9 10 COMBI INSTALL
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678.3 5 COMBI INSTALL ON
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680.3 41 NORMAL RETURNS
W "IW' I“ WW WIXCEPIWPEW
742.0E 42 NORMAL SECTION .
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751.5E 3 COMBI CABLES&
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IW751'.5I 99 I COUNTER I -
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754.5 40 NORMAL To POSITION
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810.5 41 NORMAL RETURNS
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886.9 42 NORMAL SECUON
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903.4 10 COMBI SFNCSTTIEEL‘Y‘
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935.0 5 COMBI INSTALL ON
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937.0 41 NORMAL RETURNS
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959.7 42 NORMAL SECTION

IW9 9.7 IW37W ICONSOLIDATEI - W

I 959.7I 38 'ICONSOIWIDATEI ’ 4

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I 967.9I 39 ICONSOLIDATEI -

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995.3 9 COMBI SECTION TO
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996.3 40 NORMAL To POSITION
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1056.5 1

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1070.8

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1120.9

 

 

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[1122.9 |

41

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111ml

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1195.2

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BRING
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1203.8 10 COMBI INSTALL
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‘ --. __-_,__.____.--____._._ PEESECI'ION
1234.4 5 COMBI INSTALL ON
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1236.4 41 NORMAL RETURNS
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1261.8 42 NORMAL SECHON
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1271.2 3 COMBI CAELES& E
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1273.2 9 COMBI SECTION TO
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1274.2 40 NORMAL TOPOSITION:
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1309.1 5 COMBI INSTALL ON g
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1311.1 41 NORMAL RETURNS
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1335.6 42 NORMAL SECHON
11335.6( 37 [CONSOLIDATE }“ - '
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171

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1 " ATTACH
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1379.0 10 COMBI INSTALL
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1401.7 5 COMBI INSTALL ON ;
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1403.7 41 NORMAL RETURNS
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1417.9 42 NORMAL SECTION
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11425.2 3 COMBI CABLES&
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11425.21 99 1 COUNTER 1 -
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1427.2 9 COMBI SECTION TO
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1428.2 40 NORMAL To POSITION;
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1430.0 6 COMBI SECTION INTO?
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1437.1 10 COMBI INSTALL
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11437.11 ”36' [CONSOLIDATE 1 - 1
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1460.3 5 COMBI INSTALL ON
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1462.3 41 NORMAL RETURNS
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1474.5 8 COMBI CHECK AIR ;
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11474314? ‘1' NORMAL 1 DUMMY
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; 1 1 . GRIPPER ;
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i1496.9{ 99 i COUNTER { -
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1583.8 5 COMBI INSTALL ON %
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1585.8 41 NORMAL RETURNS
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1600.0 42 NORMAL SECTION
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173

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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1607.3 3 COMBI CABLES&
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1607.3l 39 CONSOLIDATEI -

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1667.4 5 COMBI INSTALL ON

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1699.3 42 NORMAL SECTION

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1706.7 3 COMBI CABLES&

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1709.7 40 NORMAL To POSITION
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1805.5 40 NORMAL To POSITION
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1921.6 42 NORMAL SECTION
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1936.0 3 COMBI CABLES &
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CRANE
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1939.0 40 NORMAL To POSFHON
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175

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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1948.8 10 COMBI INSTALL
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1979.8 5 COMBI INSTALL ON E
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1981.8 41 NORMAL RETURNS
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2111.0 5 COMBI INSTALL ON E
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2113.0 41 NORMAL RETURNS .
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176

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5199.3"? 99 {W COUNTER : -
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2202.3 40 NORMAL TOPOSITION
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2270.5 5 COMBI INSTALL ON
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2272.5 41 NORMAL RETURNS
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2359.0 42 NORMAL SECTION
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2430.7 41 NORMAL RETURNS
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2486.2 42 NORMAL SECTION
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177

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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2557.4 5 COMBI INSTALL ON
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178

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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2661 2 E 10 COMB1 INSTALL
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2706.9 42 NORMAL SECTION
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2715.5 3 COMBI CABLES &
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E27185 40 NORMAL To POSITION
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2721.6 10 COMBI INSTALL
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2754.9 5 COMBI INSTALL ON
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2756.9 41 NORMAL RETURNS
JACK PIPE
2810.7 42 NORMAL SECTION
" ' ' DISMANTLE "
2818.7 3 COMBI CABLES &
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E2818.7E 99 E COUNTER E -
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2820.7 9 COMBI SECTION TO
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2821.7 40 NORMAL To POSITION E
E ' LOWER E
2822.8 6 COMBI SECTION INTO;
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2826.5 10 COMBI SECTION &

 

 

 

179

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

180

" W "WWW”WW WWW
CASING 1
' W 'W W W _ PIPE SECTION
2854.2 5 COMBI INSTALL ON
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._. W NE .....
2856.2 41 NORMAL RECITURNMS
W - JACK PIPE
2883.2 42 NORMAL SECTION ¥
W DISMANTLE
2908.8 3 COMBI CABLES &
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I2908.8I 99‘ I COUNTER I -
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g2910.8 9 COMBI SECTION TO
I CRANE
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2911.8 40 NORMAL To POSITION
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2913.1 6 COMBI SECTION INTO
SHAFT
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SECTION&
2921.0 10 COMBI INSTALL
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2985.6 5 COMBI INSTALL ON
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W CRANE '
2987.6 41 NORMAL RETURNS
W W W JACK PIPE
3005.7 42 NORMAL SECTION
I3005.7I 37 ICONSOLIDATEI - :
I.3005 7I 38 ICONSOLIDATE I -
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I30130I 39 ICONSOLIDATEI WW
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”WW" W3 SECTION TO
3 3 CRANE ’
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3037.3 40 3 NORMAL To POSITION
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3039.1 6 3 COMBI SECTION INTO 'f
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3041.5 10 COMBI INSTALL
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33041.5 3 36 ECONSOLIDATE -
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33068.3 5 COMBI INSTALL ON
3 , GUARD RAIL
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E3070.3 41 NORMAL RETURNS
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3078.7 8 COMBI CHECKAIR ;
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33078.73 "43 3" "NORMAL 3 DUMMY _
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3163.3 42 NORMAL SECTION .1
DISMANTLE
3170.4 3 COMBI CABLES& '
HOSES
23170.43 99 3 COUNTER 3 -
-. .... XfiXCfi ,.
3172.4 9 COMBI SECTION TO
CRANE ;

 

 

--——————-

LIFI‘ SECTION

 

 

 

 

3173.4 40 NORMAL TomsmoM
LOWER f
3174.7 6 COMBI SECTION INTO§
SHAFT
" PIPE SECTION;
3203.1 5 COMBI INSTALL ON
* GUARD RAIL
3205.1 41 NORMAL RECITURN‘AS
3218.7 42 NORMAL JACK PIPE

SECTION

DISMANTLE
3235.4 3 COMBI CABLES& '
HOSES

 

 

 

 

 

33235? [WPEIWCWOUNTERW ' 3' WW i

181

Simulation Results with CYCLONE Microtunneling Model with Soil Factor

Enhancement:

Simulation Run Times: 30

I

APPENDIX F

 

 

.fiIWCROTWI-JNNW fiftfié PROCESS INISIFFERENT S6113"

 

PRODUCTIVITY INFORMATION

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

l
i W Sim Time ; Cycle No. [ Productivity Per Time [Init
;' 155.7 1 ; 0.006421
{ 303.5 2 0.006589
[ 441.6 3 0.006793
i 550.5 4 {7 0.007267
{ 702.9 5 1 , 0.0071 13
{WEEK'S—WW W "BWWWWWW 0.007215 W """""""
{ 934.6 1 7 W ~i 0.007490
[ 1042.2 8 1"” 0.007676
["Wifi—{STWW "if—WT WW 0.007852
{ 1246.1 10 1 0.008025 _
1' 1345.6 _ 11 1' 0.008175
{ 1403.1 W WHEWWWKWW ‘ 0.058553 " W
[ 1482.3 13 . 0.008770 W W ' _
{ 1616.2 14 W37 0.008662 W
3" 1691.3 15 1 0.008869
[ 1762.8 16 i 0.009077
1 1887.1 17 { 0.009009
1‘ 1980.0 18 { 0.009091
1 2129.9 19 6 0.008921
i 2230.7 20 f 0.008966
{ 2372.3 W 21 {r' 0.008852
[ 2546.8 22 g 0.008638
{ 2679.9 23 0.008583
1 2822.2 24 1‘" W 0.008504
[ 2926.7 25 3 0.008542
2 3063.1 26 f 0.008488
' 1‘ 3175.8 27" i 0.008502 ’
§ 3304.1 28 '1’ 0.008474
{ 3456.5 5 29 3' 0.008390
{ 3541.3 30 i 0.008471 W '

 

182

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

m_'

 

EW MICROTUNNELING PROCESS IN DIFFERENT SOILS
E PRODUCTIVITY INFORMATION E
E Total Sim. Time Unit Cycle No. Pmdmm’“? (per ”me i
E E umt)
E 3541.3 30 E 0008471404967265655
E MICROTUNNELING PROCESS IN DIFFERENT SOILS
E CYCLONE ACTIVE ELEMENTS STATISTICS INFORMATION f
ActiWVity Access AVWcWranWe Maximum E MmImumW
No Name
Type Counts Duration Duration E Duration
WWW DISCHARGE & E
COMBI 1 REFILL 7 12.3 14.2 E 10.8
DESANDMAN
WW WWWW MIX 1W WWWW
COMBI 2 LUBRICATION 7 29.9 E 33.5 26.8
W WW DISMANTLEWWWWW
COMBI 3 CABLES & 11 12.3 29.1 ‘ 7.2
HOSESI
WWWWWWWWWWWW WWW EMPTY SPOIL W W
COMBI 4 TANK 7 28.1 33.2 E 23.1
EWWW PIPE SECTION f E
COMBI 5 INSTALL ON 30 41.9 77.8 28.4 E
GUARD RAIL E E
‘ E LOWER W W 'W WW W W WWW;
COMBI 6 SECTION INTO 30 1.4 2.0 1.0
SHAFT E E E
.._._._._ ADIUST AIR ..... ... E ... _ - ,
COMBI 7 GRIPPER 4 13.2 14.8 . E 11.1 E
W INSTALL & . W E E
COMBI 8 CHECK AIR 6 12.5 14.8 10.3
GRIPPER = E
ATTACH E' E ;
COMBI 9 SECTION To 3o . 2.0 2.0 § 2.0 ?
CRANE ! ___i- g
WW BRING SECTION W W W E W W W W
COMBI 10 & INSTALL 30 6.6 E 12.6 2.3
CASING . E E
LIFT SECTION E E i
NORMAL 40 To POSITION 30 E E 1.0
EWWWEWWWW CRANE W " W
NORMAL 41 RETURNS 30 2.0 OEW 2.0 . 2.0
WWW JACK PIPE E E
NORMAL 42 SECTION] 11 56.4 E 83 3 E 28.6
ENORMAL E43 E DUMMY 6 E 0.0 E o.W0WWW WWonoWWWW

 

 

183

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

EWWWWWWWWWWWEWWWW DISMANTLE E f
ECOMBI E44 CABLES& E 8 E 12.7 29.1 7.2
E E HOSES2 E E
E W E W E DISMANTLE E E
E COMBI 45 CABLES& E 2 14.6 17.0 12.2
E 3 HOSES3 E
E WWWWW E DISMANTLE E
E COMBI ‘46 CABLES& E 9 12.3 29.1 7.2
E E HOSES4 E E ‘1
EWNWOWRMALEW 52E DUMMYl E 30 I 0.0 E 0.0 0.0
WWWWWW WWWW DUMMY SOIL '
NORMAL 53 TYPE CLAYEY 11 0.0 0.0 0.0
GRAVEL
EWWW DUMMY SOIL WWWWWW'EW W WE
NORMAL E 54 TYPE SAND 8 0.0 0.0 0.0
E DUMMY SOIL
NORMAL 55 TYPE SILT 2 0.0 0.0 0.0
5 WWW DUMMY SOIL ‘ WWWWE
{NORMAL 56 TYPE CLAY 9 0.0 0.0 . 0.0
E WWWWWWWWWWW W W JACK PIPE WWWWWW W - 1W W
ENORMAL 57 SECTIONz 8 31.4 46.0 12.4
1 E JACK PIPEW . .
ENORMAL E 58 SECTION 3 2 36.1 39.3 2 32.9
E EWWW JACK PIPE
ENORMAL E 59 SECHON 4 9 71.9 92.0 24.1

 

 

 

MICROTUNNEITING PROCESS 1N DIFFERENfidifig‘“ - ..

 

CYCLONE PASSIVE ELEMENTS STATISTICS INFORMATION

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

W W WWWW Average Max. Times (V Total Average Units?
Type No. Name Units Idle not I dWlWe Sim Wt at
Idle Units empty Time Time end
--.. SEWCTWIWOWNWWONW WW... .___..-___.. W... _. ._
QUEUE 11 STORAGE! 14.4 30 3323.5 93.85 3541.3 799.5 0
E...
POSITION E
QUEUE 12 AVAILABLE 0.0 1 0.0 0.00 3541.3E 0.0 1
WWW”... r..- __ “E---“
QUEUE 13 “$23". 0.8 1 2863.7 80.87 3541.3 367 1
... --.... “HEW“..- ...,-"W -_ ._ -..- __ E
OUEUE 14 SUPSWWRVISOR 0.5 1 1693.2 47.81 3541.3 21.7 E 1
IDLE E
W W AIRGRIPPER "" E
GEN 15 READY 3.5 6 3456.5 97.60 3541.3 372.3 1 5
EWWUWWWEUWEWEW1W6WECRANEIDLE E 0.6 E 1 E1996.8E56..38E35413E 64.4 W WW1WWWW
EQUEUEEWE (33113113? E 0.0 E 1 E1391 E3.93E3541.3EWWW 45 E 1

 

184

 

 

 

 

 

 

 

 

 

 

EWWWWWWWWWWE LABORB WWWE WWWWEWWWWWWE ‘W E
EQUEUEE 1WW8WE IDLE 0.5 E 1 E17788E5023W E35413E 182 E 1
EUBUBE19 TRUCKIDLE EWW 0.9 E 1W E3122.3E88.1.7E35413E 390.3 a 1
QUEUE 20 “Egg” E 0.9 ‘ 1 3122.3 88.17 3541.3E390.3 1
E . E
W [WW F r i
1 LUBRICATION E
GBN E21 READY E 1.6 4 2657.2 75.03 3541.3.! 167.5 2
EWWWWWWWWWEWWW W EWW—WWW WWWWWW‘WW-WEW WWW—l
QUEUEEZZ BESETESETE 0.9 1 3112.3 87 88 E35413 389.0 1
--._.__..._...__.._.r---.... JACKING .. N--- .. .wm EWW . _E- -.
QUEUE 23 SYSTEM IDLE 0.1 1 316.4 8.93 3541.3E 10.2 E 1
‘w I'm “‘T"”"" r “ “"7
QUBUB 24 $155 0.1 E 1 230.4 6.51 3541.3E 6.1 E 1
WWWWWWWW NEED AIR E W E - E
QUEUE 25 GRIPPER 0.1 E 1 180.6 5.10 3541.3E 30.1 E 0
---... .. E“ GRIPPER .. ._ ... E
QUEUEE26 NEED ADJUST 0.0 E 1 0.0 0.00 3541.3E 0.0 E 0
WWW E SPOIL TANK W E E
GEN E27 NOTFULL 1.6 4 2669.6 75.38 3541.3E 168.9 E 2
E“ I
POSITION E
QUBUBE E 28 OCCUPIED 0.9 1 3201.0 90.39 3541.3E 106.7 0
WWWWEWWWW SECTION WWWWW E E
OUBUBE29 READY 0.0 1 35.3 1.00 E35413E 1.2 0
WE SECTION“- E _- ._._ .___,-._--_.-_ - E __ . ._ .. .--.--
QUEUEE 30 0.0 1 9.5 0.27 3541.3E 0.3 0
‘ E-—~—~ RBADY E E
QUEUE 31 SP 01:53?“ E0 1 0.0 0.00 3541.3 0.0 0
W WWWWWWW NBBD E . W E
QUEUE 32 LUBRICATIONE 0.0 1 0.0 0.00 3541.3 0.0 E 0
E .... DESANDMAN _ -..... ....... EWW . .
QUEUE 33 READY To 0.0 1 0.0 0.00 3541.3; 0.0 0
. DISCHARGE E
E‘-"“ r
SBCTIONIN E E
QUBUB 34 0.0 1 0.0 0.00 35413 0.0 0
...—~— PLACB1 V E E
CABLB HOSE
QUBUB 35 LASBR 0.1 1 316.4 8.93 3541.3 10.2 1
RBADY
WWW SBCTIONIN
QUBUB 47 PLACB2 0.0 1 0.0 0.00 3541.3 0.0 0
QUBUB 48 Siflggf 0.0 1 0.0 0.00 3541.3 0.0 0
QUBUB 49 Siflggm 0.0 1 0.0 0.00 3541.3 0.0 I 0

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

185

' MICROTUNNELING PROCESS IN ' " '

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

i
I

l

)

DIFFERENT SOILS
; TRACE INFORMATION
Sim” Activity "
Time NO. Type Name
. m , BRING .
SECTION&
4.9 10 COMBI INSTALL
CASING
ATTACH ;
6.9 9 COMBI SECTION TO '
CRANE
' LIFT SECTION
7.9 40 NORMAL To POSITION
LOWER
9.1 6 COMBI SECTION INTO
i SHAFT
‘ BRING
' SECTION&
19.5 10 COMBI INSTALL
CASING
* ”.-..-.” ”WW W PIPE SECTION
67.3 5 COMBI INSTALL ON
GUARD RAIL
[67.3 I 52 I NORMAL [ DUMMYI
W-..“ ... -.D SOIL
67.3 53 NORMAL TYPE CLAYEY
GRAVEL
69.3 41 NORMAL RECITURNMS
JACK PIPE
138.7 42 NORMAL SECTION]
DISMANTLE
155.7 3 COMBI CABLES&
HOSESI
{155.7f 99 I COUNTER [ -
ATTACH .
157.7 9 COMBI SECTION TO
CRANE j
LIFT SECTION
158.7 40 NORMAL To PosmON r
LOWER
160.7 6 COMBI SECTION INTO§
SHAFT '
-----.m. - . -. BRING
SECTION&
168.0 10 COMBI INSTALL
CASING

 

 

 

 

 

186

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I I I PIPE SECTION;
32073 I 5 I COMBI INSTALL ON
I I I GUARD RAIL
52207.3" I" 52 I NORMAL I DUMMYI
' DUMMY SOIL
207.3 56 NORMAL TYPE CLAY
I" W CRANE
209.3 41 NORMAL RETURNS
I JACK PIPE
1286.5 59 NORMAL SECTION 4
I * DISMANTLE
I 303.5 46 COMBI CABLES &
I HOSES4
I303.5 I 99 'I COUNTER I -
I ' ATTACH
I 305.5 9 COMBI SECTION TO
, CRANE
I“ W F LIFT SECTION
I 306.5 40 NORMAL To POSITION
I LOWER 1
308.3 6 COMBI SECTION INTO
E ’ SHAFT
BRING
SECTION&
313.0 10 COMBI INSTALL
CASING .
PIPE SECTION ,
337.4 5 COMBI INSTALL ON
.. GUARD RAIL
I3374 I 52 I NORMAL DUMMYl
I ...- DUMMY SOIL
337.4 56 NORMAL
I TYPE CLAY
{L
i CRANE
339.4 41 NORMAL RETURNS
JACK PIPE
429.4 59 NORMAL SECTION 4
W " WW DISMANTLE
441.6 46 COMBI CABLES &
HOSES4 I
I441.6I 50 ICONSOLIDATEI -
I4416 I 99 I COUNTER I -
...,--.me -.. L ATTACH -
443.6 9 COMBI SECTION TO _
~ CRANE
" LIFI‘ SECTION :
“4'6 4O Nom'mL TO POSITION
I449.9 I 10 I COMBI I BRING I

 

187

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

188

 

IW I I WI SECTION &
I I I CASING
{4499 I 36 rCONSOLIDATE; - ;
D1SCHARGE&;
453.1 1 COMBI REFILL ;
DESANDMAN
7 LOWER ;
454.6 6 COMBI .SECTION INTOI
I SHAFT
7 ‘7 INSTALL& I
464.2 8 COMBI I CHECK AIR
I GRIPPER
I464.2 I 43 I7 NORMAL I DUMMY 2
I I PIPE SECTION I
I494.2 5 COMBI INSTALL ON I
. I GUARD RAIL I
I494.2 I 52 I NORMAL I DUMMYI
I DUMMY SOIL
494.2 i 55 NORMAL TYPE SILT
496.2 I 41 NORMAL 51m“ ‘NES
I 7 JACK PIPE
533.4 58 NORMAL SECHON3 .
B33147 37 ICONSOLIDATEI -
I533. 4 I ICONSOLIDATEI -
I I DISMANTLE
I550.5 45 COMBI I CABLES& ‘
I . I HOSES 3
5505 I 99 I COUNTER I -
I--- - . ...,...“ -- ---..._._..
559.2 4 COMBI EMITIANKWOIL 2
MIX 5
561.7 2 COMBI LUBRICATION
ATTACH
563.7 9 COMBI SECTION TO
CRANE I
"7777 LIFT SECTION
564.7 40 NORMAL To PosmON I
LOWER ,
566.2 6 COMBI SECTION INTO
SHAFT '
BRING
567.3 10 COMBI SfinggEL‘g‘
CASING I
I644.0 I 5 I COMBI IPIPE SECTION

.. WWW- ...—”.....-

 

..- I. . ....--
l

I INSTALL ON

 

I

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

. I .
I I IGUARD RAIL
I 644.0 I 52 ' I NORMAL I DUMMYI :
DUMMY SOIL
644.0 54 NORMAL “TESIHE -.
7 W CRANE
646.0 41 NORMAL RE“ I“ Is
" JACK PIPE
685.9 57 NORMAL SECTION 2
.m I , WW... "DEM‘AWNTLE
702.9 44 COMBI CABLES& ‘
HOSES 2
I 702.9 I 51 ICONSOLIDATEIW .
I 702.9 I 99 I COUNTER I -
IWW" """ - ATTACH
I 704.9 9 COMBI SECTION TO
1 CRANE
I " LIFT SECTION .
705.9 40 NORMAL To POSITION
‘ LOWER
I 707.0 6 COMBI SECTION INTO
SHAFT
'77 7' 7 ' BRING
SECTION&
710.1 10 COMBI INSTALL
CASING
‘ PIPE SECTION
751.5 5 COMBI INSTALL ON
GUARD RAIL
751.5 I 52 I NORMAL DUMMYI
DUMMY SOIL
751.5 53 NORMAL TYPE CLAYEY .
GRAVEL ' ‘
CRANE
753.5 41 NORMAL RETURNS
-.." --.. . JACK PIPE
i819.4 42 NORMAL SECTION 1
7 DISMANTLE
831.6 3 COMBI CABLES& .
. HOSESl
I 831.6 I 99 I COUNTER -
..-._.___..._ I. _. ._ ATTACH I
833.6 9 COMBI SECTION TO
CRANE I
LIFT SECTION?
834.6 40 NORMAL To POSITION I

I835.8I 6 I COMBI I LOWER

189

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

" ' " " M" W MHFSEETION INTO
SHAFT ‘
i " " ’ “ BRING
1 SECTION&
837.7 10 COMBI INSTALL
; CASING
' ”PDESECTION g
$888.6 5 COMBI INSTALL ON
§ GUARD RAIL
{—888.6T ' 52 [ NORMAL [ DUMMYl .
r““"*"r‘"'“’“‘"’* ""“ 3
i, DUMMY SOIL
% 888.6 54 NORMAL TYPE SAND 1
§._....._..-.._. ...- _ W... . ...WW..___._-.-. r‘mMC—‘m‘Efl-vé
3 890.6 41 NORMAL RETURNS
"WWW” ___-“ ...- JACK PIPE .
i922.3 57 NORMAL SECHONZ.
l’ T DISMANTLE ;
934.6 44 COMBI CABLES & ‘
i HOSES 2 %
5934.6 { '99 ’ T COUNTERM'I' W
' ' " mm ' """ATTACI‘IW
936.6 9 COMBI SECTION T0
CRANE i
LIFT SECTION
937.6 40 NORMAL To POSITION i
LOWER
938.7 6 COMBI SECTION INTO ?
SHAFT
’ 1‘ BRING
SECTION &
939.9 10 COMBI INSTALL
CASING
‘ ‘ PPIPESECEENH
971.5 5 COMBI INSTALL ON
GUARD RAIL
1971.5 [ 52 { NORMAL l DUMMYI '
DUMMY SOIL
971.5 53 NORMAL TYPE CLAYEY
GRAVEL
CRANE
973.5 41 NORMAL RETURNS
JACK PIPE
1035.0 42 NORMAL SECTION]
[1035.0 F37 |CONSOLIDATE I -
|1035.o[ 38 [CONSOLIDATE{ -
WW- -- W ‘DISMA B
1042.2 3 COMBI CABLES&
I HOSESI

 

_ .. . . ..-” ... ....

190

 

E10212T2'EW 51 ECONSOLIDATEE -
E10422 E '99 E COUN‘ TER i -
E10422§ W50 ECONSOLIDATEE -

7W“- W" DISCHARGE &
E1056.4E 1 COMBI REFILL ;
3 ‘1 DESANDMAN E
" EMPTY SPOIL

TANK
£10685 2 COMBI LUBRICATION
i ATTACH
g1070.5 9 COMBI SECTION TO
1 CRANE

 

 

l
1
.1 ...... .— {WW—h .

31068.2E 4 COMBI

 

 

~.. _ .— . ~.4-._..._-_

 

-..1

 

 

1' LIFT SECTION";
E10715 40 NORMAL ToposmON

: LOWER 3
E10726 6 COMBI SECTION INTO '
E SHAFT

7 BRING
E10786 10 COMBI SECTION‘g‘

 

 

1 INSTALL

i CASING
1078.6E 36 ECONSOLIDATEE -
_ ' PIPE SECTION
INSTALL ON E
GUARDRAIL

E
:

 

 

 

 

 

 

COMBI

 

11106.6 5

1r
...“ . 1.. -—-——.--.—~- A
i
i

 

. I
E11066] 52 E NORMAL E DUMMYl .
" WE DUMMY SOILié
1106.6 1 53 NORMAL TYPE CLAYEY E
E GRAVEL

CRANE
RETURNS

INSTALL&
1121.3 8 COMBI CHECKAIR

GRIPPER
E11213E43 [WNORMAL E DUMMY

W ADJUST AIR
GRIPPER

 

 

 

1108.6 41 NORMAL

 

 

 

 

 

 

 

 

1 132.4 7 COMBI

 

"W" W JACK PIPE
1138.8 42 NORMAL SECHON 1

 

DISMANTLE
1146.2 3 COMBI CABLES &
HOSES I

.. ...- - . ... ...—........-..-.-.A....-......-.....-...."......" ........,... ......fl...._..._......... . -... .... .... ......4....._...... .. -... uh .......... ...-..“

 

 

 

 

 

ATTACH
COMBI . SECTION TO
' E CRANE =

. .... .... .. . .. , ._ "...,. ___,__.. . ...,. . .-. -..—-....—....--——..~.—-. .. ....-._. ...,. --..— .- -- --. V... ...-W-..- M....._ ... ....-l

E1146.2E 99 E COUNTER

. ...-...1

 

1
,1148.2{ 9

 

191

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

WWWW' W WWWWWWWWW W'LIFT SECTIONWE
E11492 40 E NORMAL To POSITION
W W ‘ LOWER
E1150.8 6 E COMBI SECTION INTO
i SHAFT
W' E ' WWWW BRING
SECTION&
E11518 10 COMBI INSTALL
E CASING
W W W PIPE SECTIONE
{1201.0 5 COMBI INSTALL ON
E E ' GUARD RAIL
EW2WW10EW 52 E NORMAL F DUMMYI
E ' DUMMY SOIL
E12010 55 NORMAL TYPE SILT
EWWWWW W W CRANE
E12030 41 NORMAL RETURNS
‘WWWWW WW W WW JACK PIPE
E12339 58 NORMAL SECTION 3
E ” W DISMANTLE
E1246.l 45 COMBI CABLES&
E E HOSES3
E1246.1E 99 E COUNTER E - E
W W WWW WW ATTACH f
1248.1 9 COMBI SECTION TO
LIFT SECI‘IONE
1249.1 40 NORMAL To PosmON E
W LOWER
1250.2 6 COMBI SECTION INTO
1 SHAFT ‘
' W‘ W ' W W BRING ' E
SECTION&
1254.7 10 COMBI INSTALL
CASING
PIPE SECTIONW
1285.3 5 COMBI INSTALL ON
GUARD RAIL
E1285.3E 52 E NORMAL E DUMMYI
W DUMMY SOIL
1285.3 53 NORMAL TYPE CLAYEY
GRAVEL ‘
E ..W... ___mmflmu
CRANE
1287.3 41 NORMAL RETURNS
JACK PIPE
1316.5 42 NORMAL SECHONE
WWWW DISMANTLE
1345.6 3 COMBI CABLES &

 

 

 

 

 

192

 

 

 

 

 

 

 

 

 

 

 

 

 

NORMALWWWW EWWIWJWUMMY 1

 

 

' E W E" _ WE WWWW EWWWWIWiOWSWESWWIWWWWW
E1345.6E 5W1 ”ECONSOLIDATEE -
EW1W345.6E 99 E COUNTER E -
WW ATTACH
1347.6 9 COMBI SECTION TO
CRANE '
'WWWWWW WLIFT SECTIOWNWE
1348.6 40 NORMAL To POSITION:
WWWWWW E WWWLWOWWWERWWWWE
1350.1 6 COMBI aSECI‘ION INTOE
E SHAFT “
WW W BRING
SECTION&
1353.8 10 COMBI INSTALL .
CASING E
r PIPE SECTIONE
1383.5 5 COMBI INSTALL ON
GUARD RAIL

“m” ___-....-.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

DUMMY SOIL
1383.5 54 NORMAL TYPE SAND .
CRANE
1385.5 41 NORMAL RETURNS
............ --....“ JACK PIPE
1395.9 57 NORMAL SECHONZ
11395-9E 37 ECONSOLIDATEE -
E13959E 38 ECONSOLIDATEE -
E ' DISMANTLE
1403.1 44 COMBI CABLES&
E HOSE82 ‘
E1403:1E 99'WE' ””COWUNTERW E W -
EMPTY SPOIL
1427.3 4 COMBI TANK 1
MIX 1
1427.9 2 COMBI LUBRICATIONE
ATTACH 2
1429.9 9 COMBI SECTION TO
CRANE E
LIFT SECTIONE
1430.9 40 NORMAL ToposmON s
LOWER .
1432.3 6 COMBI SECTION IN'I‘OE
SHAFT E
BRING .
SECTION&
1439.3 10 COMBI INSTALL
CASING

 

 

 

193

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

194

i

i;
1

 

1 1 1 1 PIPE SECTION
114619 5 1 COMBI INSTALL ON
1 1 GUARD RAIL
1146191 52 1 NORMAL F DUMMY 1 1
DUMMY SOIL
1461.9 54 NORMAL TYPE SAND
CRANE
1463.9. 41 NORMAL RETURNS
.._____-____._.1____
JACK PIPE
1474.9 57 NORMAL SECTION 2 1
-- w DISMANTEEWE
1482.3 44 COMBI CABLES &
HOSES 2
11482. 31 99 ”'1'_COUNTER 1 -
1 ATTACH 1
1484.3 9 COMBI SECTION TO
CRANE 1
1..- --.,-.. W L 1
LIFT SECTION
1485.3 40 NORMAL To POSITION
- 1 . .‘ __ -... -- .- ”LOWER
I1487. 1 6 COMBI SECTION INTO
1 , SHAFT '
1 1 1 BRING
SECTION &
11494. 2 1o COMBI 1 INSTALL
1 1 CASING
H494. 2 13 36 1CONSOLIDATE 1 -
1 1 1 M .....- PIPE SECTION 1
11517.4 .. COMBI INSTALL ON f
1 151 GUARD RAIL
11517.41 52 1 NORMAL 1 DUMMYI 1
DUMMY SOIL
1517.4 56 NORMAL TYPE CLAY .
CRANE
1519.4 41 NORMAL , RETURNS
’ ' ‘ INSTALT: & '
1531.5 8 COMBI CHECK AIR
GRIPPER
11531.51 43 1 NORMAL 1 DUMMY
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1546.3 7 COMBI GRIPPER
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1609.0 59 NORMAL SECHON 4
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11616.21 50 1CONSOLIDATE1 -

 

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11618.2

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1629.6

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1683.8

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11753.3 1”. 37 1CONSOLIDATE1 -
11753.3W1' 38 1CONSOLIDATE1 -
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I31175. 8I 99 I COUNTER I -
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3324.5 40 NORMAL To POSITION
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I3355. 5 5 COMBI INSTALL ON
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I3355.5 I M 52 ” I NORMAL I DUMMY i
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I3456.5 I 99’ I COUNTER I -
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3459.5 40 . NORMAL To POSITION
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3460.7 6 COMBI SECTION INTO
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3489.2 5 COMBI INSTALL ON
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204

 

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205

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