USING SALVAGED LUMBER AS A FEEDSTOCK FOR MANUFACTURING STRUCTURAL GLULAM By Amar Bajirao Mali A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Construction Management - Master of Science 2022 ABSTRACT USING SALVAGED LUMBER AS A FEEDSTOCK FOR MANUFACTURING STRUCTURAL GLULAM By Amar Bajirao Mali Every year tons of old wood end up in landfills as there is no lucrative alternative. A glued- laminated timber section made with salvaged lumber could make efficient use of the salvaged material. A 3-point bending test was conducted on a total of 120 specimens to investigate the mechanical properties of glued-laminated timber manufactured using salvaged lumber. The MOE, MOR, and reliability of the salvaged lumber were assessed according to the experimental results. The influence of the position of salvaged lumber on the MOE and MOR of glulam was investigated by one-way ANOVA. The influence of the type of adhesive used for manufacturing glulam was also studied. The results show that that when compared with control samples of glulam, the glulam manufactured with 60% of salvaged lumber had a reduction of 10.5% in MOR, 10.5% in MFL, and 1.9% in MOE as shown in table 4.1. when compared with control samples of glulam the glulam manufactured with 40% of salvaged lumber had a reduction of 4.7% in MOR, 4.5% in MFL, and 1.35% in MOE. These reduction percentages are less than 11% for all mechanical properties. In other words, we can say that even for glulam samples made of 60% of salvaged lumber the reduction percentage for all mechanical properties is going to be less than 11%. The reduction percentage for MOE between two consecutive grades turns out to be 33% approximately so we can safely say in absence of any data about a given salvaged sample we can assume that MOE of that salvaged lumber will be one grade below the actual MOE of that sample before use. Copyright by AMAR BAJIRAO MALI 2022 ACKNOWLEDGEMENTS First and foremost, I would like to thank Dr. George Berghorn, my advisor who provided me extensive support throughout this research. I would essentially not have seen the light of the day without your help and exceptional encouragement at every step along the journey. His unparalleled knowledge and support continue to fascinate me. I would also like to acknowledge the research funding provided by the Environment, Great Lakes, and Energy (EGLE) and the continued support provided by the School of Planning, Design, and Construction towards my master’s education. I thank my research colleague Ahamed for working hard with me throughout this research. This research was made possible by the encouragement and generosity of several individuals, who in one way or another contributed to the acceleration of my efforts through the duration and completion of my work. I would like to thank my other research committee members Dr. Matt Syal and Dr. Mojgan Nejad who deserve special recognition for their contributions towards this research thesis by serving as committee members and by sharing their expertise and valuable inputs. I would also like to thank Mr. Dan Brown for teaching us the use of various equipment in a wood lab without which I would not have been able to complete this research. In addition, I would express gratitude to the forestry department for allowing us to use the wood lab at Michigan State University. I would like to thank Papa Chad for teaching us to perform tests on Instron. Most importantly, I would like to acknowledge my friends, colleagues, and my family members who have stood by me in every decision in life. iv TABLE OF CONTENTS LIST OF TABLES ........................................................................................................................ vii LIST OF FIGURES ...................................................................................................................... vii CHAPTER 1 ................................................................................................................................... 1 INTRODUCTION .......................................................................................................................... 1 1.1 Overview .............................................................................................................................. 1 1.2 Need Statement ..................................................................................................................... 3 1.2.1 Wood Waste Management in the United States ............................................................. 4 1.2.2 Potential Supply of Structural Wood Waste in the US ................................................... 7 1.2.3 Potential Wood Waste Supply in Michigan ................................................................... 7 1.2.4 Advantage of using salvaged lumber during unprecedented times ................................ 8 1.2.5 Use of salvaged lumber in the construction industry ................................................... 10 1.3 Glulam ................................................................................................................................. 10 1.3.1 History of Glulam ......................................................................................................... 10 1.3.2 Types of Configurations in Glulam .............................................................................. 11 1.3.2.1 Unbalanced Beam .................................................................................................... 11 1.3.2.2 Balanced Beam ........................................................................................................ 12 1.4 Research Goal and Objectives............................................................................................. 12 1.5 Scope and limitations of the research .................................................................................. 13 1.6 Chapter Summary................................................................................................................ 14 CHAPTER TWO .......................................................................................................................... 15 LITERATURE REVIEW ............................................................................................................. 15 2.1 Circular Economy ............................................................................................................... 16 2.2 Characteristics of salvaged wood ........................................................................................ 16 2.3 Effects of aging on Mechanical properties of salvaged wood ............................................ 18 2.4 Glue-laminated timber......................................................................................................... 19 2.4.1 Types of Configurations in Glulam .............................................................................. 21 2.4.2 Unbalanced Layup ........................................................................................................ 22 2.4.3 Balanced Layup ............................................................................................................ 22 2.4.4 Arrangement of Lumber in Glulam .............................................................................. 23 2.5 Lumber Grading .................................................................................................................. 24 2.6 Chapter Summary................................................................................................................ 25 CHAPTER 3 ................................................................................................................................. 26 METHODS ................................................................................................................................... 26 3.1 Introduction to Methodology .............................................................................................. 26 3.2 Phase 1: Characterization of salvaged lumber .................................................................... 26 3.3 Phase 2: Manufacturing of GLSL ....................................................................................... 37 3.4 Performance of Glulam ....................................................................................................... 40 3.4.1 Manufacturing standards and process........................................................................... 40 3.5 Phase 3: Mechanical testing of manufactured Glulam panel .............................................. 43 v 3.6 Data Analysis ...................................................................................................................... 43 3.7 Data Quality Measures ........................................................................................................ 43 3.8 Chapter Summary................................................................................................................ 44 CHAPTER 4 ................................................................................................................................. 45 RESULTS ..................................................................................................................................... 45 4.1 Visual Inspection ................................................................................................................. 45 4.2 Modulus of elasticity ........................................................................................................... 51 4.3 Modulus of rupture .............................................................................................................. 55 4.4 Maximum flexural load ....................................................................................................... 59 4.5 Chapter summary ................................................................................................................ 62 CHAPTER 5 ................................................................................................................................. 63 SUMMARY, CONTRIBUTIONS, AND FUTURE RESEARCH............................................... 63 5.2 Future Recommendations.................................................................................................... 66 APPENDICES .............................................................................................................................. 68 APPENDIX A : MFL and MOR values of raw 186 samples ................................................... 69 APPENDIX B : MOE values of raw samples obtained from Metriguard ................................ 76 APPENDIX C : MFL and MOR values of selected 82 samples ............................................... 90 APPENDIX D : Visual grading of 27 samples ......................................................................... 94 APPENDIX E : MOE values of salvaged samples from Metriguard ..................................... 102 APPENDIX F : MFL and MOR values of 30 samples with 60% GLSL…………………….157 APPENDIX G : MFL and MOR values of 30 samples with 60% GLSL ............................... 161 APPENDIX H : MFL and MOR values of 30 control samples .............................................. 164 REFERENCES ........................................................................................................................... 166 vi LIST OF TABLES Table 1.1: Shows the data of the wood generated, composted, combusted with energy recovery, and landfilled by weight (in thousands of U.S. tons) in the year 1960-2017(EPA, 2017). ............ 6 Table 3.1: Showing variables of interest to be measured for salvaged lumber during sampling and lab testing. .............................................................................................................................. 27 Table 3.2: Sample type and total number of samples ................................................................... 38 Table 3.3: List of variables to be measured for newly manufactured Glulam panel. ................... 42 Table 4.1: Table showing criteria for visual characteristics and their reference standards .......... 45 Table 4.2: Lamination Grade Results ........................................................................................... 46 Table 5.1: Showing percent reduction in MOE, MOR, and MFL values of samples ................... 65 Table 6.1: MFL and MOR values of 186 samples ........................................................................ 70 Table 6.2: MOE values of raw sample obtained from Metriguard ............................................... 77 Table 6.3: MFL and MOR samples of selected 82 samples ......................................................... 91 Table 6.4: MOE values of salvaged samples from Metriguard .................................................. 103 Table 6.5: MFL and MOR values of 30 samples with 40% GLSL ............................................ 157 Table 6.6: MFL and MOR values of 40% GLSL ....................................................................... 158 Table 6.7: MFL and MOR values of 30 Control samples........................................................... 165 vii LIST OF FIGURES Figure 1.1: Google N-Gram: Graph showing the frequencies of salvaged wood and virgin wood terms used yearly found in sources printed between 1500 and 2010.................................... 2 Figure 1.2: Wood Cascading of Structural Lumber ........................................................................ 5 Figure 1.3: Wood Waste Management: 1960-2017 ........................................................................ 6 Figure 1.4: Graph showing rise in lumber price in the US. ............................................................ 9 Figure 2.1: Outline of literature review ........................................................................................ 15 Figure 2.2: Glued Laminated Timber (Glulam) ............................................................................ 20 Figure 2.3: Comparison of glulam’s engineering efficiency with Mechanically Graded Lumber (MSR) and visually graded lumber. .............................................................................................. 20 Figure 2.4: Unbalanced layup ....................................................................................................... 22 Figure 2.5: Balanced layup ........................................................................................................... 23 Figure 3.1: Three Phases and all tasks in three phases ................................................................. 28 Figure 3.2: Photograph of Metriguard-340-E and its components ............................................... 30 Figure 3.3: Photograph of Jointer ................................................................................................. 30 Figure 3.4: Photographs showing various equipments used during making samples for instron . 31 Figure 3.5: Photograph of Instron model 4206 used for testing 3-point bending test .................. 32 Figure 3.6: (left) Testing of 16”x1”x1” sample on Instron (right) Blue-hill software interface .. 32 Figure 3.7: Showing 6 sub-samples made from each main sample (sample number 20 in this case) and their nomenclatures for all 68 samples. ........................................................................ 33 Figure 3.8: Showing the Instron sample cut from each sub-sample (20A(a) in this case) with the nomenclature where L is left, M is middle, and R is right............................................................ 34 Figure 3.9: Comparison between values of MOR and MOE of 184 Instron samples .................. 34 Figure 3.10: Phase 1-This phase consists of two sub phases that is phase 1a for literature review and phase 1b: Characterization of salvaged lumber. .................................................................... 35 vii Figure 3.11: Phase 1c- Sample collection and testing .................................................................. 36 Figure 3.12: Five layered Glulam panels with various percentages of salvaged wood in different positions. ....................................................................................................................................... 38 Figure 3.13: Phase 2 Manufacturing, testing, and analyzing the results with future recommendations. ......................................................................................................................... 39 Figure 3.14: Process flow diagram for glulam manufacturing ..................................................... 40 Figure 3.15: Layup requirements for structural glued laminated timber (Southern Pine Fir) ...... 42 Figure 4.1: Comparison between values of MOR and MOE of 184 Instron samples .................. 47 Figure 4.2: Box plot showing the difference between MOE values obtained from Metriguard 340-E and Instron .......................................................................................................................... 48 Figure 4.3: Bar graph showing number of samples with the difference between average MOE values obtained from Metriguard 340-E and Instron .................................................................... 48 Figure 4.4: Pie chart showing the distribution of grades for 68 samples of salvaged lumber based on MOE values from Metriguard .................................................................................................. 49 Figure 4.5: Screenshot from SPSS software showing Tukey test selection with 0.05 significance level ............................................................................................................................................... 50 Figure 4.6: Descriptive statistics and Test of homogeneity of variance for MOE values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. .................... 51 Figure 4.7: Tests of equality of means and Post Hoc test for MOE values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. ................................... 52 Figure 4.8: Scheffe test for MOE values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. .......................................................................................... 53 Figure 4.9: Graph of Mean of MOE values on y-axis vs Percentage salvage lumber on the x-axis for 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. .. 54 Figure 4.10: Descriptive statistics and Test of homogeneity of variance for MOR values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. ................ 55 Figure 4.11: Tests of equality of means and Post Hoc test for MOR values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. ................................... 56 Figure 4.12: Scheffe test for MOR values of 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples ........................................................................................... 57 viii Figure 4.13: Graph of Mean of MOR values on y-axis vs Percentage salvage lumber on the x- axis for 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples ....................................................................................................................................................... 58 Figure 4.14: Descriptive statistics and Test of homogeneity of variance for MOR values of 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples. ................ 59 Figure 4.15: Tests of equality of means and Post Hoc test for MOR values of 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples. ................................... 60 Figure 4.16: Scheffe test for Maximum Flexural Load values of 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples ................................................. 61 Figure 4.17: Graph of Mean of MFL values on y-axis vs Percentage salvage lumber on the x-axis for 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples ... 61 ix CHAPTER 1 INTRODUCTION 1.1 Overview The past few years have seen exponential growth in sustainable building practices. Until recently, relatively less importance was given to the reuse of salvaged lumber for structural applications. Reusing salvaged lumber helps in reducing greenhouse gas emissions, reducing carbon footprint, minimizing pollution, and conserving natural resources (Bergman et al., 2013; Rose et al., 2018). Building deconstruction is an accepted method to extract the maximum amount of good conditioned salvaged material from old buildings and old structures (Tatiya et al., 2017). The use of salvaged wood is not a new concept, but it has seen a surge in popularity especially with sustainable and green building construction. Figure 1.1 shows the frequencies of salvaged wood and virgin wood terms used yearly found in sources printed between 1500 and 2010. There is an increase in the use of the word salvaged wood after the year 2010. Salvaged wood is the wood that is carefully extracted from the old structure during its demolition or deconstruction. This salvaged wood is then cut or re-shaped for its reuse. The emerging concept of Story wood has huge potential to add value to the salvaged wood in the coming years. Additionally, these Story wood can be used to score points in LEED and WELL certification by contributing to the innovation, materials, and mind categories (Delta Institute, 2018). Another major benefit of reusing this salvaged lumber is that the material can be dimensionally stable, as it has been air-dried for many years. Despite having several advantages of reusing salvaged lumber, its widespread use is hampered because of fewer consistent markets for large volumes of wood waste. 1 Figure 1.1: Google N-Gram: Graph showing the frequencies of salvaged wood and virgin wood terms used yearly found in sources printed between 1500 and 2010. Source: Figure N-Gram Despite beneficial features, the reuse of salvaged lumber faces barriers as well. One of the main barriers for reusing the salvaged wood is that if the wood is exposed to unfavorable conditions such as direct sunlight, UV radiations, or humid climate the wood undergoes chemical and physical degradation (William et al., 1984) Due to temperature fluctuations and humidity wood is subjected to mechanical stresses (Borgin et al., 1975). Elevated temperature for a longer duration may also result in loss of weight, the strength of wood, and decrease of MOR (Forest Product Laboratory, 1999). Also, if the wood is subjected to loading for a long period, then wood is likely to carry a lesser percentage of load when compared to the load-carrying capacity of the same wood subjected to no-load previously. For example, a wood subjected to bending stress for 10 years may be capable of carrying only 60% or less load than the same wood which is not subjected to any bending stress in past (Forest Product Laboratory, 1999). Therefore, effects on strength of wood due to the loading 2 history of the wood must be considered when salvaged wood is to be reused. However, Barret and Foschi (1978) presented a model to predict the effects of duration of loading on wood, which suggested that a wood member placed under a constantly high-stress level over a period then the wood is likely to sustain damage due to the DOL effect as the rate of degradation is expected to slow down over a period. Other barriers to increased wood reuse include the lack of recycling centers for wood waste and the lack of a cost-effective system for re-grading salvaged lumber (Howe et al., 2013). Lack of a dedicated process for handling hazardous wood (such as wood painted with lead-based paints) contributes to the list of barriers as well. Another barrier is the difficulty in estimating the exact volume of post-consumer wood waste. Essential steps are required to be taken to remove the barriers to expanding markets for reusing wood waste as reusing wood waste is necessary to overcome several problems as well. 1.2 Need Statement Every year, 146 million tons of solid waste is disposed of in landfills across the United States (EPA., 2018). This waste mainly comes from residences, industries, and construction sites. One of the major sources of waste wood is demolished structures. In USA there are almost 226,778 abandoned houses that are potential candidates to be demolished (US CENSUS BUREAU, 2020). This large amount of wood from these abandoned houses are most likely to end up in landfill if any lucrative alternative is not provided. Land filling of wood from houses will not only end the life cycle of a renewable material but will also use up the limited landfill areas available in the US. Wood is one of the oldest construction materials and is a renewable resource (Issa, 2005). Despite being renewable, it is still the second-largest contributor to construction and demolition (C&D) debris after concrete. Wood waste contributes 20 to 30 percent of the total C&D waste and 10 3 percent of all landfilled material annually (Leblanc, 2018). Problems associated with landfilling, waste incineration, and economic strain due to an increase in the cost of waste disposal are of growing concern. Growing awareness about environmental issues related to landfilling of wood waste and burning of wood as a biofuel has pushed researchers to contemplate on reuse and recycling of wood. As per the Steel Recycling Institute (SRI), the rate of steel recycling is 98% and the rate of concrete recycling is 82% which is notably higher than the recycling rate of wood which is only 16.7%. (EPA, 2017; CMRA, year). These statistics make it evident that despite having both renewable ability and abundant availability of wood, its recycling percentage is very low. Hence, it is vital to elucidate that the reuse of wood should be our priority rather than the increasing consumption of virgin wood exponentially. To address the issues of wood waste management, research must lead to the creation of new markets for waste wood material in US. 1.2.1 Wood Waste Management in the United States The United States is currently the largest producer of wood products in the world. A total of 143 million tons of wood products are produced in the US each year (Howe et al., 2013). Forest products are consumed at a rate of 1,800 pounds per person annually in the US (Haynes, 2003). It is forecasted that the consumption of forest products in the U.S will be escalated by 40 percent by 2050; to meet this demand, a 23 percent increase in timber harvest will be required (Haynes, 2003). And as per the World Bank’s forecast, global timber demand is going to quadruple by 2050 (FIM, 2017). Reusing salvaged lumber will be of a great benefit to fulfill the growing demand without overusing the existing forest reserves. The forecasted growth rate of the global reclaimed lumber market is 4.8% which will boost the USD amount from 12.50 billion in 2019 to USD 17.79 Billion in 2027 (Research and data, 2020). Promotion of the concepts like Story wood and reusing 4 salvaged lumber for manufacturing products like CLT and Glulam will help in reducing pressure on forest reserves to fulfill future demands of wood supply. Reusing salvaged lumber will not only reduce the overuse of forest reserves but will also help in reducing the wood waste generation. Typical markets of wood waste in the U.S. include paper products, animal bedding particleboard, landscaping material, pulp, composting material, energy recovery, and reuse (Calrecycle, 2019). In the US approximately 30 percent of wood waste is commonly disposed of by burning wood for energy, 10 percent is ground into mulch, and the remaining 60 percent is disposed of in C&D landfills. (Calrecycle, 2019). Greenhouse gas (GHG) emissions from landfilling of wood waste are comparatively greater than GHG emissions resulting from burning of old wood for energy (Bergman, 2013). Several strategies are required to increase the efficient use of wood utilization. One such strategy which will help in the efficient use of wood utilization is the concept of wood cascading. In general, wood cascading means efficient utilization of wood at every product stage with its use for energy generation as the final stage. (Risse, 2019). Figure 1.2 shows one such example of wood cascading for a circular economy. Figure 1.2: Wood Cascading of Structural Lumber 5 In 2017, the domestic generation of wood in the municipal solid waste (MSW) stream was approximately 18 million tons; this is approximately 6.7 percent of the total MSW generated that year. Out of these 18 million tons, 12.1 million tons of wood ended up in landfills (EPA, 2017). Management 1960 1970 1980 1990 2000 2005 2010 2015 2016 2017 Pathway Generation 3,030 3,720 7,010 12,210 13,570 14,790 15,710 16,300 18,050 17,990 Recycled - - - 130 1,370 1,830 2,280 2,660 2,940 3,000 Composted - - - - - - - - - - Combustion - 10 150 2,080 2,290 2,270 2,310 2,570 2,860 2,850 with Energy Recovery Landfilled 3,030 3,710 6,860 10,000 9,910 10,690 11,120 11,070 12,250 12,140 Table 1.1: Shows the data of the wood generated, composted, combusted with energy recovery, and landfilled by weight (in thousands of U.S. tons) in the year 1960- 2017(EPA, 2017). Source: Center for Forest Products Marketing and Management (Virginia Polytechnic Institute) Figure 1.3: Wood Waste Management: 1960-2017 Sources: https://www.epa.gov/facts-and-figures-about-materials-waste-and-recycling/wood- material-specific-data#WoodTableandGraph 6 1.2.2 Potential Supply of Structural Wood Waste in the US There are 16,672,938 homes in the United States; out of those homes 5,884,047 fall under the “other vacant” category which is the best estimate for abandoned homes in the US (US Census Bureau, 2019). In five years (2013-2018) alone 585,233 homes became vacant (US Census Bureau, 2018). These abandoned houses are required to be deconstructed so that all useless siting salvageable wood can be reused again profitably. It is estimated that total abandoned homes in the US have approximately 28,205,676,000, board feet of salvageable lumber which can be reused. (MSU center for community and economic development, 2016; US Census Bureau, 2016). These abandoned homes are a stockpile of old lumber which can be reused to prevent these old lumbers from losing the potential salvage value. A significant amount of lumber is potentially available for future reuse. Since the 20th century, more than 3 trillion board feet of lumber have been sawn in the United States (Falk et. Al., 2013; Howard 2001). Some states in US are facing issues of abandonment on a greater scale. The state of Michigan is one of such states who are facing problem of abandonment which needs to be addressed as soon as possible. 1.2.3 Potential Wood Waste Supply in Michigan As per the U.S census bureau, Michigan had 671,430 housing units in 2018, with approximately 223,774 of those being abandoned (Census Bureau, 2019). In five years (2013-2018) around 9,347 homes were abandoned in the state of Michigan. (Census Bureau, 2018). The City of Detroit alone has over 78,071 abandoned homes (US Census Bureau, 2019)). Structural abandonment poses several threats to communities, such as economic loss to neighboring non-abandoned properties, increased crime, and unemployment rates, decrease in property value, impact the aesthetics of the surrounding area, pose a negative impact on public health and community. (Mallach, 2018). Due 7 to these negative impacts abandonment of homes has become a major concern for local government. These abandoned homes in Michigan have littered the state. One of the best methods for solving this issue is the deconstruction of these abandoned homes instead of demolition (Mallach, 2018). Deconstruction is defined as the selective dismantlement of each building component without causing loss to their mechanical and physical properties. for recycling and reuse (Carruthers, 2013). Deconstruction has also been defined as “construction in reverse” where all building components are dismantled for reuse or recycling purpose (Carruthers, 2013). Whereas demolition of a building means clearing of building by the most expedient means at the end of their design life leading to loss of salvage value of components. One of the main advantages of deconstruction of these abandoned homes is that the material which is deconstructed can be reused for more sophisticated applications such as in building construction rather than burning as fuel or landfilling. (Wu et al., 2015). The reuse of lumber will lead to the reutilization of its maximum potential of salvage value. One of the ways of reutilizing salvaged wood is using salvaged wood to manufacture products like Cross Laminated Timber (CLT) and Glulam. These products once tested and approved as per the industry standards can be used for desired applications. In this research we will concentrate on manufacturing Glulam products by using salvaged lumber from abandoned houses of Michigan. 1.2.4 Advantage of using salvaged lumber during unprecedented times As shown in figure 1.4 lumber prices in the US have grown from around $400/1000 BF in April 2020 to $1278/1000 BF in April 2021 amid COVID-19 pandemic. The. The high prices are the result of disruptions in the supply chain and huge boost in home improvement projects when the pandemic forced people to stay home. National Association of Home Builders says wood costs are 8 adding $24,000 to the price of a new house. During such unprecedented times, use of salvaged lumber can prove to be very lucrative. The use of salvaged lumber will not only help in maintaining supply and demand during these unpredictable times but will also control the cost of lumber from surging suddenly. Another major advantage of using the salvaged lumber is that the lumber can be obtained from abandoned houses which act as a readymade storage place for wood at all locations. There is no need to put extra effort into storing these salvaged lumbers during normal times. In a nutshell, salvaged lumber can provide a good cushioning effect for surging lumber prices during such unprecedented times at no extra cost. Figure 1.4: Graph showing rise in lumber price in the US. (Source: Trading economics, 2021) 9 1.2.5 Use of salvaged lumber in the construction industry Salvaged lumber can be used in construction in many ways for example old wood can be used in making wall panels, kitchen countertops, floors, and decks. One of the major advantages of using salvaged lumber is that the same wood is reused again which results in reducing our dependency on virgin lumber. Salvaged lumber comes with a desirable and unique look that cannot be found in newly sawn wood thus giving a unique look to the structure. Another, benefit of using salvaged lumber in construction is that salvaged lumber has its own story which appeals for the finished project and in return, this increases the market value of the project due to sentimental value attached to the material used in the project. Also, using reclaimed wood certified by the Forest Stewardship Council can help the construction or remodeling project earn LEED points. Thus, the use of salvaged wood in construction not only benefits the project by increasing its unique appearance and value but also helps protecting the environment. 1.3 Glulam Glulam is manufactured by bonding horizontal layers of dimensional lumber or “lams” using adhesives. The grains of these laminations run parallel to the length direction of the member. Glulam can be used for longer spans as any number of laminations can be joined to produce desired long lengths with the help of adhesives. When compared to the pound by pound, glulam is stronger than steel (APA, 2007). This enables glulam to be used in areas where intermediate supports are restricted and in structures where long spans are desired. 1.3.1 History of Glulam A series of glulam arches erected in 1934 at the US Department of Agriculture Forest Products Laboratory in Madison, Wisconsin is one of the oldest uses of the glulam in the US (Rammer et 10 al., 2013). Degradation of the glue line was one of the major concerns in earlier days when glulam was exposed to the exterior environment. The advent of water-resistant adhesives in 1942 not only solved the concern of glue line degradation but also boosted the development of the glulam industry. The commercial standard CS 253-63 published by the department of commerce in 1963 was the first US manufacturing standard for glulam. Now, ANSI/APA standard A190.1 is the most recent standard used for providing guidelines for the manufacturing of glulam. 1.3.2 Types of Configurations in Glulam Glulam is manufactured by bonding dimensional lumber together using adhesives. Maximum tension and compression occur at the top and bottom of the glulam, therefore strongest lams are used at the top and bottom of the beams. Comparatively lower structural quality lams can be used in inner sections of the beams. Generally, glulam beams are manufactured in two configurations, unbalanced and balanced beams (APA, 2017). 1.3.2.1 Unbalanced Beam An unbalanced beam has higher bending stress on the tension side of the beam than the compression side of the beam (APA, 2008). This unbalance in the bending stress allows us to use lumber more efficiently. Comparatively good quality of lumber is used on the tension side of the beam to counter greater bending stress in the tension zone. Because of these unbalanced stresses in the beam, it becomes very vital to be careful while installation of these beams. 11 1.3.2.2 Balanced Beam In these beams, the bending stress is distributed uniformly from the horizontal centerline. Balanced beams can be used as a cantilever or continuous beams where the top or the bottom of the beam is highly stressed in tension due to service load. Balanced beams are less cost-efficient than unbalanced beam. 1.4 Research Goal and Objectives The goal of this study is to characterize the suitability for salvaged lumber to be used as a feedstock for glulam and determine the physical and mechanical properties of such manufactured products against industry reference standards, such as ANSI/APA. This research aims to find the answer to the following question: “Does the percentage of salvage lumber significantly influence the MOR, MOE, and Maximum flexural strength of glulam?” There are three main objectives of this research: • To characterize the residual mechanical and physical properties of salvaged lumber of deconstructed homes of Michigan. • To manufacture glulam panels (GSL-Glu-laminated Salvaged Lumber) using a mixture of salvaged lumber and virgin lumber; and • To analyze mechanical properties of Glulam panels manufactured with varying proportions of salvaged lumber. a) To test manufactured samples on Instron and to tabulate MOR, MOE and MFL. b) To compare 60% and 40% salvaged lumber glulam panels with the control samples. c) To find out reduction in MOR, MOE, and MFL percentages when compared to control samples and demonstrate potential for salvaged lumber as a feedstock for glulam 12 1.5 Scope and limitations of the research The scope of this research is to characterize the suitability for salvaged lumber to be used as a feedstock for glulam and determine the physical and mechanical properties of such manufactured products against industry reference standards, such as ANSI/APA. Following are the limitations of this research: • Limited availability of salvaged lumber is one of the main limitations of this research. To overcome this limitation each of 68 full length samples was divided into 6 sub samples to increase the sample size. • Access to the lab was hampered due to Covid-19 pandemic. The research lab was inaccessible for 3 months due to surge in Covid-19 cases in Michigan. • Any movement in cable connecting the blue box and the load cell of Metriguard 340-E changed the MOE reading of the sample, thus hampering the accuracy of the MOE values and grade of the samples. To overcome this limitation, several tested samples were tested again to cross check the MOE value and grade of the sample. • All samples were not graded on Metriguard 340-E because they failed to clear the minimum requirement of length and thickness of the samples. • Frequency was induced to the samples by manual tamping which creates room for human error. • The MOE values obtained from Instron, and MOE values obtained from Metriguard 340- E had a mean difference of 0.54 Mpsi. 13 1.6 Chapter Summary This chapter presents the overview of history and rising popularity of the reuse of salvaged lumber due to exponential growth in sustainable building practices. There is great need of reusing salvaged lumber because of limited landfill areas and surplus wood waste supply in the US. Composite members like glulam can be manufacture as per industry standards to meet the growing demands of lumber and to reuse the surplus supply of waste wood in the US. Three main objectives of this research are (i) To characterize the residual mechanical and physical properties of salvaged lumber of deconstructed homes of Michigan. (ii) To manufacture glulam panels (GSL-Glu-laminated Salvaged Lumber) using a mixture of salvaged lumber and virgin lumber; and (iii) To analyze mechanical properties of Glulam panels manufactured with varying proportions of salvaged lumber with ANSI/APA standards (ANSI A190.1-2017). 14 CHAPTER TWO LITERATURE REVIEW Figure 2.1: Outline of literature review 15 2.1 Circular Economy CE is a new model of economic development that tries to 'replace the "end of life" concept by maximizing recycling and reuse of goods and materials to reduce waste generation to the maximum possible extent (Franco-García, 2019). This concept is based on 3 Rs principles Which are reduction, reuse, and recycling. The main objective of CE is to redefine the complete chain of manufacturing, consuming, distributing, and recovery of energy from materials according to the cradle-to-cradle system (Ghisellini, 2018) This system relies on cascading use of renewable resources such as wood. Material like wood is planned for its multiple reuses under this system which ultimately benefits both economically and environmentally. CE also helps in fostering energy saving and reducing GHG emissions (Ghisellini, 2018). CE is a change in mindset which focuses on waste as a potentially useful resource and not as a problem to deal with and dispose of in landfills. In the case of wood, reuse may be the better option when compared with its recycling. An investment of 234% is required in the conventional recycling process of wood (Brown and Buranakarn, 2003). Thus, pushing the recycling benefit ratio below 1 and ultimately making recycling of wood non-profitable. Reuse is considered as the best option because of a larger increase in net carbon storage due to carbon storage in-use products (USEPA, 2012; Diya mantoglu and Fortuna, 2015). Therefore, this research concentrates on the reuse of salvaged wood from abandoned houses of Michigan rather than its recycling. 2.2 Characteristics of salvaged wood It is very important to study the characteristics of salvaged wood before it can be used to manufacture composite members like Glulam. The salvaged wood has its own past life like the story wood explains even when used in a new product. Wood goes through some changes in its first productive life, but all changes are not harmful. For example, salvaged wood has which has 16 sat in a building or structure for a very long period is likely to have lower moisture content than the freshly sawn wood because it is dried for many years. This change in the salvaged wood makes the wood more durable and adds value to the wood in long run (All-Recycling-Facts, 2014). Salvaged wood from houses is more likely to be stable in dimensions than freshly sawn wood as it has sat under load for many years and has already gone under all changes (Hasek, 2014). Salvaged wood has lesser amount of atmospheric CO2 than freshly cut wood. The reuse of wood will help in decreasing carbon emission as well. Between the mid-1800s to 1900s, the industrial revolution led to the logging of most of the old- growth forests in the upper Midwest of the US (Quinlan, 2013). These old-growth trees in the upper Midwest of US forests ranged from 100-500 years old (Quinlan, 2013). If the wood is not subjected to unfavorable conditions the wood not only stays stable but old- growth wood becomes more rot resistant and structurally stable than fresh lumber (Wisconsin Historical Society). As the tree gets older it becomes stronger and its growth rings become tighter (Wisconsin Historical Society). Michigan was one of the top producers from 1840 – 1900 and cradle for industry (Quinlan, 2013). Till 1930 most of the old-growth forests were logged out in the upper Midwest (Quinlan, 2013). There are high chances that these trees which were used from the 1840-1930s will be more stable and must have retained its properties till now. To know the properties of these old wood before use, we can use the “standard grade specifications for yard lumber” of 1923. Circular 296 of the department of agriculture for structural timber and circular 295 which dealt with basic grading rules and working stress for structural timber to know the properties of these old timbers as a benchmark to compare them with the existing stress carrying capacity. The difference between the minimum strength of timber mentioned in standards and 17 existing strength of these old, salvaged materials will give us the strength lost due to aging or unfavorable conditions and loading. 2.3 Effects of aging on Mechanical properties of salvaged wood The effect of aging on the mechanical properties of wood is of prime importance to maximize the reuse of salvaged lumber. It is important to note that mechanical properties of wood such as modulus of elasticity (MOE) and modulus of rupture (MOR are vital for reuse of salvaged lumber but are not directly related to aging of wood alone. They are also dependent on various factors such as an unknown history of tested wood, lack of standardized testing, and exposure of wood to different environmental conditions. Kranitz (2014) argued that the effect of loading history of wood is related to the age of wood, but it is not a result of the age of wood itself. In the same way, mechanical properties of damaged lumber are significantly reduced; while such reduction is not solely related to aging, but possibly due to state of conservation. After testing salvaged lumber many researchers concluded that the MOE of wood did not change much over the life cycle of wood. The researchers who reported change in MOE in salvaged lumber had different criteria for wood selection, testing, and analysis of the results. Hirashima (2005), in interesting research reported a decrease in Ultimate tensile strength and MOE of aged keyaki wood by 16.4 and 20.3%, respectively, compared to new wood and later found no significant difference in Ultimate tensile strength or MOE between Akamatsu wood aged 115 years and new wood. Nevertheless, the density of the new timber tested was different than the density of the old timber. Hence, it is difficult to determine if the difference in MOE values were solely due to aging of wood and not because of the difference in the density of the species or the environmental condition to which the primary wood was exposed too. 18 Rammer (1999), in ambitious research, concluded that both MOR and tensile strength of wood is affected by splits and checks in addition to the aging of lumber. Similarly, Chini et al. (2001) tested old southern pine structural members obtained from different buildings designed for different loading conditions. The average MOR of salvaged timber was approximately 10% lower than new timber. MOR in these experiments was affected by the defects and exposure of wood to different conditions rather than its age. 2.4 Glue-laminated timber Glue-laminated timber (glulam) was first used in Europe in the early 1890s (Glulam Product Guide, 2017). A series of glulam arches erected in 1934 at the US Department of Agriculture Forest Products Laboratory in Madison, Wisconsin is one of the oldest uses of the glulam in the US (Rammer et al., 2013). Glulam is a composite member manufactured by bonding horizontal layers of dimensional lumber or “lams” using adhesives (Glulam Product Guide, 2017). The grains of these laminations run parallel to the length direction of the member (ANSI A190.1, 2017). Glulam can be used for longer spans as any number of laminations can be joined to produce desired lengths with the help of adhesives. Adhesives used for glulam are required to meet ASTM D2559 and ANSI405 for exterior use and ASTM D7247 for heat durability. Mixing, spreading, assembly temperature, press time and adhesive curing time should be by adhesive manufacturer (ANSI A190.1, 2017). Glulam also has a greater strength-to-weight ratio than steel (AICT 117, 2010; APA, 2008). This enables glulam to be used in areas where intermediate supports are restricted and in structures where long spans are desired giving more flexibility to the designers during designing structures of longer spans. Glulam can offer superior structural performance. Its superior performance is combined with durability for long term. One of the main advantages of glulam is 19 that glulam has a high degree of engineering efficiency. Figure 2.4 shows glulam’s engineering efficiency when compared to Mechanically Graded Lumber (MSR) and visually graded lumber. Figure 2.2: Glued Laminated Timber (Glulam) (Source: Verma, 2018) Figure 2.3: Comparison of glulam’s engineering efficiency with Mechanically Graded Lumber (MSR) and visually graded lumber. (Source: The wood products council, 2010) 20 Uses of Glulam Glulam has several advantages over other construction materials like concrete and steel. When compared to concrete and steel glulam uses less energy for its manufacturing. It can be used in structures that require longer spans without intermediate supports. Glulam is comparatively lighter than steel and concrete which means it will require less joints and connections and will be easier to handle. It has versatile application and uses as it can be used in beams, columns stairs, and in aesthetical use such as cladding. Treated glulam are dimensionally stable, so this treated glulam can be used in structures with specific climatic demands in harsh weather. It also performs very well against deformation and tension caused by moisture. The carbonized layer around the glulam decreases the oxygen consumption and retards the combustion which makes it safer than steel in fire. All these advantages of glulam over other construction materials used in construction give glulam an edge over other material and prove that glulam can be used vastly used as an excellent alternative construction material. 2.4.1 Types of Configurations in Glulam Glulam is manufactured by bonding dimensional lumber together using adhesives. Maximum compression and tension occur at the top and bottom of the glulam, respectively, therefore strongest lumber is used at the outermost lams for glulam beams (ANSI A190.1, 2017). Comparatively lower structural quality lams can be used in the inner sections of the beams. Generally, glulam beams are manufactured in two configurations, unbalanced and balanced (APA, 2017). 21 2.4.2 Unbalanced Layup An unbalanced layup has higher bending stress on the tension side of the beam than the compression side of the beam (APA, 2017). The unbalanced layup has unequal capacity in positive and negative bending. This layup is mainly for designing simple beams or short cantilever beams. The unbalanced layup requires 5% tension lams on the bottom of the beams (ANSI A190.1, 2020). This imbalance in the bending stress allows us to use lumber more efficiently. Comparatively good quality lumber is used on the tension side of the beam to counter greater bending stress in the tension zone. Because of these unbalanced stresses in the beam, it becomes very vital to be careful while installation of these beams. Therefore, unbalanced beams are marked with “TOP” on the top side of the beam. Figure 2.4: Unbalanced layup 2.4.3 Balanced Layup In this type of layup, the bending stress is distributed uniformly from the horizontal centerline (APA, 2017). Balanced layup has equal capacity in both positive and negative bending. Balanced beams can be used as cantilever or continuous beams where the top or the bottom of the beam is 22 highly stressed in tension due to service load. This layup requires 5% tension lams on the top and bottom of the beams. Balanced beams are less cost-efficient than the unbalanced beam. A balanced layup has equal capacity in both positive and negative bending (APA, 2017). Figure 2.5: Balanced layup 2.4.4 Arrangement of Lumber in Glulam The arrangements of lumber in Glulam are crucial because of variations in stress distribution in top, bottom, and core layers. The arrangement of laminae by stiffness during the manufacturing process is advantageous (Koch, 1964). It not only makes the beam stiffer but also increases the strength of the beam. Stiffer and stronger laminae are placed on the outer edges where maximum tension and compression stresses occur. The stiffness of the outer laminae plays an important role in determining the overall strength of the beam (Moody, 1970). The comparison of the strength of the beams with laminae arranged by stiffness, appearance, and the random selection concluded that the beams with arranged laminae by stiffness not only increased the average strength but also decreased the variability between beams (Koch and Bohannan, 1965). Therefore, in this study, it 23 is important to keep salvaged lumber in core layers and virgin lumbers in outermost layers where tension and compression stress are maximum. 2.5 Lumber Grading The mechanical properties of wood vary significantly regardless of species and size. Sometimes strength of lumber of the same size and species may even differ by several hundred percent. The wood used in glulam is either visually or mechanically graded. Visual inspections are carried out to assess the physical characteristics of wood to grade without the use of machines. Many growth characteristics that affect the mechanical properties of lumber can be judged visually. (Kretschmann, 2006). Therefore, growth characteristics are used to group the wood in different grades (Kretschmann, 2006). In general, grading is based on defects and physical properties of wood such as knots, splits, density, pitch pockets, and checks and decay. To use wood economically and to reduce the complexity, wood with similar mechanical properties is grouped in the same grades. This lumber is called mechanically graded lumber. The characterization of wood in various stress grades is a result of engineering design, sorting criteria, and unique grade name. Mainly six design properties are considered while dividing the wood into different grades. These six properties are (a) modulus of elasticity for an edgewise loading orientation, (b) stress in shear parallel to the grain (c) stress in compression parallel to the grain (d) stress in tension parallel to the grain (e) extreme fiber stress in bending, and (f) stress in compression perpendicular to the grain, (AITC 119). ANSI/AITC A190.1 is used as a glulam manufacturing standard. It specifies product qualifications and quality assurance requirements. All glulam standards require positioning of lam by grades. The quality of lumber is a key to controlling glulam member performance. Design values of laminations are kept in accordance with ASTM D3737 which allows designing based on the growth characteristics of lumber such as knots, slope 24 of grain and density. ASTM D3737 has a standard analysis procedure to generate all major design properties. Table B1 from (ANSI-117, 2020) will be used to determine the layup requirement of glulam manufactured using salvaged lumber. There are 6 tension lamination grades, 302-20, 302- 22, 302-24, 302-26, 302-26, 302-28, 302-30. General rules as per chapter C6 of (ANSI 117, 2020) are applied for all grades and sizes of lumber graded as tension laminations. Chapter C6.8 will be used as exceptions to provisions in section C6.2, C6.3 and C6.4. Thickness of each lamination should not be more than 2 inches unless gap-filling adhesive is used for the face and edge bonds (ANSI A190.1, 2017). Dimensional tolerances should be as per section 6.3 of ANSI A190.1 standard. Other than mechanical grade of laminations the edge characteristic of lumber is also important. The edge characteristics of laminations should be in accordance with section C5.3.3 of the ANSI 117 standard. 2.6 Chapter Summary This chapter covers the existing literature of topics related to this research. It talks about circular economy and its objectives. Then it discusses the literature on glulam available in the market and elaborates the balanced and unbalanced layup in glulam. Then it discusses the importance of arrangement of laminations in glulam to identify that the use of salvaged lumber in the core layers and use of virgin lumber in the outer layers is vital. Last section of this chapter discusses the ANSI standards and their specific sections for lumber grading. 25 CHAPTER 3 METHODS 3.1 Introduction to Methodology The literature review conducted in chapter 2 provided the necessary foundation for deciding the methodology for this research. To full fill three objectives of this research that is (a) To characterize the residual mechanical and physical properties of salvaged lumber of deconstructed homes of Michigan. (b) To manufacture glulam panels (GSL-Glue-laminated Salvaged Lumber) using a mixture of salvaged lumber and virgin lumber; and (c) To analyze mechanical properties of Glulam panels manufactured with varying proportions of salvaged lumber with ANSI/APA standards (ANSI A190.1-2017); each objective was divided into three corresponding phases. Each phase was then further divided into various tasks. Completion of all tasks in one phase will mark the completion of that phase. Figure 3.1 shows the three phases of the methodology chapter and various tasks that are to be carried out to full fill all three objectives of this research. 3.2 Phase 1: Characterization of salvaged lumber Phase 1 is designed to full fill objective 1 of this research. Phase one is further divided into three sub-phases that is phase 1a, phase 1b (part 1), and phase 1b (part 2). In phase 1a, previous works related to the reuse of salvaged lumber or mechanical and physical characteristics of salvaged lumber is studied. Various literature available on related research helped in identifying various crucial variables of interest (VOI) for this study. VOI during sample collection and VOI during lab testing of collected samples were finalized. Also, all samples and their sub-samples were given specific codes so that wood samples tested for these all variables can be marked with the respective codes to identify the samples at the later stage of the research. Table 3.1 shows all the VOI. 26 The next task after the finalization of VOI and sample codes is to finalize the factors of interest (FOI). Three most important factors were finalized by studying available literature. These three factors were: (1) grades of salvaged lumber, (2) position and percentage of salvaged lumber, and (3) type of adhesives used for binding panels. Each factor was further divided into levels. Factor one had only one level of grade of lumber. Grading of lumber was done in two ways, mechanical grading and visual grading. Mechanical grading of salvaged lumber was decided based on Modulus of elasticity (MOE) and Modulus of rupture (MOR) of salvaged lumber. These two parameters were selected based on ANSI/APA standard Glulam guide. Visual grading of salvaged lumber was also carried out based on the shorthand grading guide of southern pine inspection bureau (SPIB). Sample number Location of salvaged wood Approximate duration of loading (in years) Variables to be measured for Type of species salvaged wood during sample collection Grade stamp Type of wood Visual grading Variables to be Dimensions of lumber (in feet) measured for salvaged wood Weight (in lbs.) Variables to be measure for MOE (in psi) salvaged wood in the lab Specific gravity Frequency (in Hz.) Table 3.1: Showing variables of interest to be measured for salvaged lumber during sampling and lab testing. 27 Figure 3.1: Three Phases and all tasks in three phases 28 Phase 1b consists of collecting samples from abandoned homes of the state of Michigan and then testing these collected samples for the characterization of the salvaged lumber. This phase is further divided into tasks. The first task involves collecting information about abandoned homes in the state of Michigan from the municipal corporation of Michigan. Abandoned home that was scheduled for demolition was identified and the sample was collected based on time, day of demolition, and location of the site as per convenience. 68 southern yellow pine and 192 eastern spruce samples were collected randomly from deconstructed houses in Bay City, Michigan in 2017. Spruce is one of the very common species which are used for manufacturing Glulam. The house was built in the mid-1950s; thus, lumber was loaded for approximately 60 years. The 68 samples were approximately 190” X 11.5” X 1.5” in dimension and 192 samples were of various length ranging 30” to 60” tested for all pre-decided variables of interest. Out of 68 samples 34 samples had grade stamps visible on them. The 68 samples were first visually graded using shorthand grading guide of southern pine inspection bureau (SPIB) as shown in APPENDIX D. Further, they were tested for the mechanical properties on Metrigaurd-340-E as they cleared the minimum sample length criteria for testing on Metrigaurd-340-E. Each sample was subjected to hand tapped vibrations 6 times. Metriguard gave the MOE, specific gravity, and the grade for the samples as shown in the APPENDIX B. 29 340 Interface unit Laptop Load cell Tripods Figure 3.2: Photograph of Metriguard-340-E and its components Figure 3.3: Photograph of Jointer 30 (a)Planer (b) Band Saw (C) Table Saw Figure 3.4: Photographs showing various equipments used during making samples for instron 31 Figure 3.5: Photograph of Instron model 4206 used for testing 3-point bending test Figure 3.6: (left) Testing of 16”x1”x1” sample on Instron (right) Blue-hill software interface 32 Phase 1b part 2 consists of checking the effect of physical properties in detail for these 68 samples. Therefore these 68 samples were further cut into 6 smaller pieces as shown in figure 3.7. All sub- samples were marked with unique codes as shown in figure 3.7. These 408 pieces were then again regraded on Metriguard and MOE and specific gravity for all these sub-samples was collected. Thirty random samples were collected from these regraded samples. Random numbers were generated using python language. Then these 30 samples were visually graded. After visual grading, samples were then resurfaced using planer and jointer and 3 sub-samples 16”x1”x1” were made from each 30 samples as shown in figure 3.8. The size of sample was selected as per ASTM D143-14. These 90 samples were subjected to 3-point bending test on Instron-4206. The MOE and MOR values of 90 samples are tabulated in APPENDIX C. The remaining 192 samples were shorter than 70” so they were tested on Instron-4206. All 192 samples were planned and 1 sub- samples of size 16”x1”x1” were made from each main sample. All 192 sub-samples were subjected to 3-point static bending test on Instron at the rate of 1.3mm/min as per ASTM D-143-14 and MOE and MOR values were recorded in the APPENDIX A. 20A(a) 20B(a) 20A(b) 20B(b) 20A(c) 20B(c) Figure 3.7: Showing 6 sub-samples made from each main sample (sample number 20 in this case) and their nomenclatures for all 68 samples. 33 Instron sample size 16”x1”x1” 20A(a)L 20A(a)M 20A(a)R Figure 3.8: Showing the Instron sample cut from each sub-sample (20A(a) in this case) with the nomenclature where L is left, M is middle, and R is right. MOR Vs MOE 20,000.00 18,000.00 16,000.00 14,000.00 12,000.00 MOR in psi 10,000.00 8,000.00 6,000.00 4,000.00 2,000.00 0.00 0.00 300,000.00 600,000.00 900,000.00 1,200,000.00 1,500,000.00 1,800,000.00 2,100,000.00 2,400,000.00 2,700,000.00 MOE in psi Figure 3.9: Comparison between values of MOR and MOE of 184 Instron samples 34 Figure 3.10: Phase 1-This phase consists of two sub phases that is phase 1a for literature review and phase 1b: Characterization of salvaged lumber. 35 From Phase Phase 1b part 1b part 1 2 Cutting 68 samples into 6 equal parts Marking all samples as per the pre decided coding method. Testing all sub- Randomly selecting 30 samples on samples Metrigaurd-340 Visually grading selected 30 samples Testing 3 samples each Objective 1 Collecting and from all 30 samples (total achieved. recording data 90) on Instron-4206 for MOE & MOR To Phase 2 Figure 3.11: Phase 1c- Sample collection and testing 36 3.3 Phase 2: Manufacturing of GLSL Phase 2 consists of the manufacturing of composite member, glulam using salvaged lumber (GLSL). 5 layered glulam panels are manufactured using all three factors with their respective levels. Table 3.2 shows the configuration of each sample type and the total number of samples required to be tested in each sample type. A total of 120 samples were manufactured. 30 samples for each type of configuration. 120 samples of five layered glulam were manufactured using salvaged lumber. Each type of sample had 30 replicas to avoid outliers and errors. 60 samples had salvaged lumber in middle three layers (second, third and fifth layer) of glulam (60% salvaged lumber and 40% virgin lumber) as shown in figure 3.12. Other 60 samples had salvaged lumber in the middle layer (20% salvaged lumber and 80% virgin lumber) as shown in figure 3.14. Two adhesives polyurethane and lignin were used for binding five layers of glulam. 60 samples were manufactured using PU based adhesive and 60 samples were made using lignin. All 120 samples were manufactured as per section 3.3 of this thesis. All 120 samples were tested on Instron-4602 for MOE and MOR values. Thirty control samples were manufactured using virgin lumber only, to cross check if the manufacturing method has any major impact on the MOE and MOR values of the samples. 37 Five layers for Glulam 60% 30 samples manufactured Salvaged Lumber panel Salvaged using PU. Virgin lumber panel lumber 40% 30 samples manufactured Salvaged using PU. lumber 100% 30 samples manufactured virgin using PU. Lumber Figure 3.12: Five layered Glulam panels with various percentages of salvaged wood in different positions. Factor Factor 2 Factor 3 1 Type of Percentage of salvaged No. of Grading samples lumber Type of samples of adhesive lumber 40% 60% 0% 1 4 YES PU 30 2 4 YES PU 30 3 4 YES PU 30 Total 90 Table 3.2 Sample type and total number of samples 38 From Phase 1 Phase 2 Manufacturing Glulam Objective 2 panels as per pre- achieved. decided factors and ANSI/APA standards Phase 3 Begins. Testing of newly manufactured Glulam panels for decided variables. Tabulating results Grading of tested samples based on results by comparing with ANSI/APA standards Analyzing data using factorial design (ANOVA) Conclusion Future Objective 3 recommendations achieved. Figure 3.13: Phase 2 Manufacturing, testing, and analyzing the results with future recommendations. 39 3.4 Performance of Glulam 3.4.1 Manufacturing standards and process Plaining salvaged Plaining virgin lumber to 2x4 lumber to 2x4 lumber lumber Checking moisture Checking moisture content content Cutting lumber into Cutting lumber into 18-inch length 18-inch length Visual grading Visual grading Applying glue and Layup Pressing glulam Curing Finishing to remove beads of glue. Figure 3.14: Process flow diagram for glulam manufacturing 40 Glulam was manufactured by gluing salvaged lumber and virgin lumber together to form larger and stronger structural members. The flow chart of the glulam manufacturing process is shown in figure 3.14. Moisture content of salvaged lumber was first measured using a hand-held moisture meter. As the salvaged wood was sitting in a dry environment for about two years its moisture content was below 12%. Therefore, kiln drying was not required for drying salvaged lumber. After checking the moisture content plaining of salvaged lumber was carried out. These lumbers were passed from jointer and planner to get desired (2x4) lumber dimensions. Then these lumbers were cut to 18-inch length using a circular saw. A total of 240 laminations was made and all 240 laminations were visually graded as per ANSI 117 standard for its edge characteristics. Virgin lumbers were directly obtained from the market. Moisture content was checked and confirmed for each lumber. Then all lumbers were planned to 2x4 lumber by passing them from jointer and planner. The 2x4 lumbers were then cut to 18-inch length using a circular saw. A total of 360 laminations was made and visually graded for their edge characteristics. After making salvaged lumber laminations and virgin lumber laminations structural glue (polyurethane) was applied on the faces of laminations. The resinated lumber was assembled into three specified lay-up patterns as shown in figure 3.12. Ready samples were then clamped in a clamping bed and pressed by the manual press for 30 mins to bring the lumber into close contact. After 30 mins the glulam samples were removed from the clamping system. The samples were allowed to cure for 24 hours. After curing, beads of resin that squeezed out between the boards were removed before testing. 41 Figure 3.15: Layup requirements for structural glued laminated timber (Southern Pine Fir) (Source: ANSI 117, 2020) Code of sample The method used to calculate/identify variables Sample number Position of salvaged lumber in panel Moisture content Oven drying method Variables to be Dimensions of lumber (in measured for inches/feet) newly manufactured Density CLT/glulam panel using MOR salvaged lumber MOE Metriguard-340 Specific gravity Table 3.3 List of variables to be measured for newly manufactured Glulam panel. 42 3.5 Phase 3: Mechanical testing of manufactured Glulam panel Phase 3 Once GLSL samples were manufactured they were tested for all VOI, and results were tabulated. The moisture content of manufactured panels was measured using a moisture meter. All 120 samples were tested on Instron by keeping a 1-inch overhang on both sides as shown in the figure. All 120 sub-samples were subjected to a 3-point static bending test on Instron at the rate of 1.3mm/min as per ASTM D-143-14 and MOE and MOR values were recorded in APPENDIX E. 3.6 Data Analysis Descriptive statistics are used to analyze the recorded data. Informed by factorial design the one- way ANOVA was used. Hypothesis tests were carried out wherein the classification of data is based on two factors (i) Position of salvaged lumber in GLSL (ii) Type of adhesive used for manufacturing GLSL. It was used to compare levels of the two independent variables involving multiple observations at each level. The one-way ANOVA helps in examining the effect of the two factors on the continuous dependent variable. 3.7 Data Quality Measures To maintain the accuracy of testing Metrigaurd-340 equipment was calibrated every week. Once Glulam panels are manufactured and tested, some tests will be randomly repeated for already tested samples again to cross-check the accuracy of the tested sample readings. This will not only help in testing the accuracy of the experiments but also help in eliminating false reading during the final analysis of the observations and drawing out the conclusion at the end of the research. To cross-check the reliability of the manufacturing process, 30 glulam control samples are manufactured with 100% virgin lumber of 1.8 Mpsi were tested on Instron. Also, to check the accuracy of the calibration of Instron, 30 virgin lumber samples of size 16”x1”x1” were tested. 43 3.8 Chapter Summary This chapter starts by explaining the method used for achieving all three objectives of the research. The method for fulfilling the first objective of characterization of salvaged lumber is described in Phase 1 part 1 and part 2. The purpose of phase 2 is to achieve the second objective of manufacturing GLSL using salvaged lumber. Phase 3 helps is achieving the third objective It consists of 3 phases and each phase is subdivided into tasks to achieve the third objective of analyzing the data obtained from testing the GLSL. A strong positive correlation between MOE and MOR was observed for the 184 samples tested on Instron. MOE from Metriguard 340-E was found to be lesser by an average of 0.54 Mpsi when compared with MOE from Instron for the same samples. A correlation between visual grading of salvaged lumber and MOE values was found. Finally, two-way ANOVA was used to analyze the 2 x 2 factorial matrix. 44 CHAPTER 4 RESULTS 4.1 Visual Inspection Out of 68 samples of salvaged lumber, 27 Samples were visually inspected for Knots, shakes/checks, end splits, the slope of grain, nail holes, and physical damage. Results are tabulated in APPENDIX D. Shorthand grading guide of southern pine inspection bureau was used for visual grading of these 27 samples. All 27 samples had a slope of less than 1:10. 3.7% of total samples were of grade 1, 18.5% of samples were of grade 2, 11.1% were of grades 3, and 29.6% were of grade 4. 2.0E6 SPF ANSI 117-2020 1.67; edge characteristics < 1/6 of cross-section 1.8E3 SPF ANSI 117-2020 1.48; edge characteristics < 1/3 of cross-section 1.4E2 SPF ANSI 117-2020 1.2; edge characteristics < 1/2 of cross-section Table 4.1: Table showing criteria for visual characteristics and their reference standards Out of the total of 27 samples, 21 samples were graded out as 2.0 E6 SPF based on MOE values from Merguard. Out of these 21 samples, two samples could not meet the E6 visual requirements. Sample numbers 44 and 58 both graded out as 2.0E6 SPF based on MOE; however, due to the presence of large knots, they could not meet the E6 portion of the grade. So, 19 out of 21 samples passed 2.0E6 SPF grade criteria, both from MOE and visual requirements point of view. 45 Number of Samples Passing E Only (n=68) E Plus Visual (n=27) Grade Number % Number % 2.0E6 SPF 43 63.2 21 77.7 1.8E3 SPF 55 80.8 27 100 1.4E2 SPF 66 97.0 27 100 Table 4.2: Lamination Grade Results The MOE and MOR relationship were studied based on the results obtained from testing 408 southern pine samples on Metrigaurd-340E for MOE and then testing 30 randomly selected samples from 408 samples on Instron for MOE and MOR. Figure 3.9 shows a comparison between values of MOR and MOE of 184 Instron samples. The Pearson correlations were run between sample MOR and MOE obtained from these 186 samples. MOR and MOE had a strong positive correlation to each other with r=.811 after ignoring 2 outliers. The value of t- statistics were found to be 18.69 with 184 as the degree of freedom. The p-value of the given data is 4.017 x 10-44 which is less than 0.01. Hence the given data is statistically significant. 46 MOR Vs MOE 20,000.00 18,000.00 16,000.00 14,000.00 12,000.00 MOR in psi 10,000.00 8,000.00 6,000.00 4,000.00 2,000.00 0.00 0.00 500,000.00 1,000,000.00 1,500,000.00 2,000,000.00 2,500,000.00 MOE in psi Figure 4.1: Comparison between values of MOR and MOE of 184 Instron samples Figure 3.11 shows the difference between MOE values from Metriguard 340-E and Instron. MOE values obtained from Instron were higher for 93% of tested samples when compared to MOE values obtained from Metriguard 340-E. Figure 3.10 shows the box plot of the difference between MOE values of Metriguard 340-E and Instron. The box plot showed the median value of .46 Mpsi and the mean value of 0.54 Mpsi. 47 Figure 4.2: Box plot showing the difference between MOE values obtained from Metriguard 340-E and Instron 3.5 3 2.5 MOE in Mpsi 2 1.5 1 0.5 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Number of main samples Average MOE from Instron in Mpsi MOE from Metrigaurd in Mpsi Figure 4.3: Bar graph showing number of samples with the difference between average MOE values obtained from Metriguard 340-E and Instron 48 9% 4% Grade 1 28% 59% Grade 2 Grade 3 Grade 4 Figure 4.4: Pie chart showing the distribution of grades for 68 samples of salvaged lumber based on MOE values from Metriguard Out of 68 samples, 43 samples were graded as 2.0E6 SPF based on MOE values obtained from Metrigaurd-340. 55 samples were graded as 1.8E6 SPF and 66 samples were graded as 1.4E6 SPF. One-way ANOVA was run between 40% of salvaged lumber samples and Control samples, 60% of salvaged lumber samples and Control samples, and 60% of salvaged lumber samples and 40% of salvaged lumber samples for MOE, MOR, and maximum flexural load. SPSS software was used to run one-way ANOVA. The Independent variable is a type of lumber that is salvaged or virgin, the dependent variable is MOE and MOR. 49 One way Between subjects ANOVA was run with the percentage of salvaged lumber as the independent variable and MOR, MOE, and Maximum flexural strength as the dependent variable. Figure 4.5: Screenshot from SPSS software showing Tukey test selection with 0.05 significance level A one way Between subjects ANOVA was run with the percentage of salvaged lumber as the independent variable and MOR, MOE, and Maximum flexural strength as the dependent variable. 50 4.2 Modulus of elasticity Figure 4.6: Descriptive statistics and Test of homogeneity of variance for MOE values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. 51 Figure 4.7: Tests of equality of means and Post Hoc test for MOE values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. Null Hypothesis: There are no significant differences in MOE values across different percentages of salvaged lumber in glulam. Alternate hypothesis: There is significant differences in MOE values across different percentages of salvaged lumber in glulam. This hypothesis tests if the MOE values differ across the three types of layups. As each sample was drawn independently of the other sample, the values of MOE are assumed to be normally distributed. The results showed no significant difference between the percentage of lumber and MOE of glulam. Tukey post Hoc analysis revealed that 40% of salvaged lumber samples is not significantly different from 60% of salvaged lumber samples (p=0.999>0.05) and the Control samples (p=0.993>0.05). Also, control samples are not significantly different than 60% of salvaged lumber samples (p=986>0.05). The 52 null hypothesis that there is no significant difference in MOE of glulam between the different percentages of salvaged lumber samples would be accepted. Figure 4.8: Scheffe test for MOE values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. 53 Figure 4.9: Graph of Mean of MOE values on y-axis vs Percentage salvage lumber on the x-axis for 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. Mean MOE for 60% of salvaged lumber samples was around 30500 psi and standard deviation of 10432.91, Mean MOE for 40% of salvaged lumber samples was around 30700 psi and standard deviation of 13260.94, and that of control samples was around 31100 psi and standard deviation of 14494.52. 54 4.3 Modulus of rupture Figure 4.10: Descriptive statistics and Test of homogeneity of variance for MOR values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. 55 Figure 4.11: Tests of equality of means and Post Hoc test for MOR values of 60% of salvaged lumber samples ,40% of salvaged lumber samples, and control samples. Null Hypothesis: There is no significant differences in MOR values across different percentages of salvaged lumber in glulam. Alternate hypothesis: There is significant differences in MOE values across different percentages of salvaged lumber in glulam. This hypothesis tests if the MOR values differ across the three types of layups. As each sample was drawn independently of the other sample. So, values of MOR are assumed to be normally distributed. The results showed a significant difference between the percentage of lumber and MOR of glulam. Tukey post Hoc analysis revealed that 40% of salvaged lumber samples is not significantly different from 60% of salvaged lumber samples (p=0.271>0.05) and the Control samples (p=0.424>0.05). Nevertheless, control samples have significantly more MOR on average than 60% of salvaged lumber samples 56 (p=0.017<0.05). The null hypothesis that there is no significant difference in MOR values of glulam between the different percentages of salvaged lumber samples would be rejected. The alternate hypothesis that there is a significant difference in MOR values of glulam between the different percentages of salvaged lumber samples is accepted, as the p-value for the control sample is greater than 0.05). Figure 4.12: Scheffe test for MOR values of 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples 57 Figure 4.13: Graph of Mean of MOR values on y-axis vs Percentage salvage lumber on the x- axis for 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples Mean MOR for 60% of salvaged lumber samples was around 2250 psi and standard deviation of 246.40, Mean MOR for 40% of salvaged lumber samples was around 2300 psi and standard deviation of 492.45 and that of control samples was around 2700 psi and standard deviation of 338.02. 58 4.4 Maximum flexural load Figure 4.14: Descriptive statistics and Test of homogeneity of variance for MOR values of 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples. 59 Figure 4.15: Tests of equality of means and Post Hoc test for MOR values of 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples. Null Hypothesis: There is no significant differences in maximum flexural strength values across different percentages of salvaged lumber in glulam. Alternate hypothesis: There is significant differences in maximum flexural strength values across different percentages of salvaged lumber in glulam. The results showed a significant difference between the percentage of lumber and maximum flexural strength. Tukey post Hoc analysis revealed that 40% of salvaged lumber samples is not significantly different from 60% of salvaged lumber samples (p=0.250>0.05) and the Control samples (p=0.454>0.05). Nevertheless, control samples have significantly more maximum flexural strength on average than 60% of salvaged lumber samples samples (p=0.017<0.05). The null hypothesis that there is no significant difference in strength properties of glulam between the different percentages of salvaged lumber samples would be rejected. 60 Figure 4.16: Scheffe test for Maximum Flexural Load values of 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples Figure 4.17: Graph of Mean of MFL values on y-axis vs Percentage salvage lumber on the x-axis for 40% of salvaged lumber samples, 60% of salvaged lumber samples, and control samples Mean MFL for 60% of salvaged lumber samples was around 13006 lbf and standard deviation of 1388.111, Mean MFL for 40% of salvaged lumber samples was around 13877 lbf and standard 61 deviation of 2778.383and that of control samples was around 14530 lbf and standard deviation of 1904.202. 4.5 Chapter summary This chapter consists of data analysis. One-way ANOVA was used to analyze the collected data. One-way ANOVA was used on strength properties (MOE, MOR, and Maximum flexural load) of glulam on all three types of layups. The next chapter will focus on the conclusions and future areas for improvement. 62 CHAPTER 5 SUMMARY, CONTRIBUTIONS, AND FUTURE RESEARCH The goal of this study is to characterize the suitability for salvaged lumber to be used as a feedstock for glulam and determine the physical and mechanical properties of such manufactured products against industry reference standards, such as ANSI/APA. This research aims to find the answer to the following question: “Does the percentage of salvage lumber significantly influence the MOR, MOE, and Maximum flexural strength of glulam?” There are three main objectives of this research: 1. To characterize the residual mechanical and physical properties of salvaged lumber of deconstructed homes of Michigan: Grading of lumber was done in two ways, mechanical grading and visual grading. Mechanical grading of salvaged lumber was decided based on the Modulus of elasticity (MOE) and Modulus of rupture (MOR) of salvaged lumber. These two parameters were selected based on ANSI/APA standard Glulam guide. Visual grading of salvaged lumber was also carried out based on the shorthand grading guide of the southern pine inspection bureau (SPIB). 97% of the samples had MOE above 1.4E6 SPF. Out of 68 samples, 43 samples were graded as 2.0E6 SPF based on MOE values obtained from Metrigaurd-340. 55 samples were graded as 1.8E6 SPF and 66 samples were graded as 1.4E6 SPF. 2. To manufacture glulam panels (GSL-Glu-laminated Salvaged Lumber) using a mixture of salvaged lumber and virgin lumber; and: After making salvaged lumber laminations and virgin lumber laminations structural glue (polyurethane) was applied on the faces of laminations. The resinated lumber was assembled into three specified lay-up patterns as shown in figure 3.14. Ready samples were then clamped in a clamping bed and pressed by 63 the manual press for 30 mins to bring the lumber into close contact. After 30 mins the glulam samples were removed from the clamping system. The samples were allowed to cure for 24 hours. After curing, beads of resin that squeezed out between the boards were removed before testing. 3. To analyze mechanical properties of Glulam panels manufactured with varying proportions of salvaged lumber against glulam samples made with virgin lumber: • The results for One-way ANOVA for MOR values showed no significant difference between the percentage of lumber and MOE of glulam. Tukey post Hoc analysis revealed that 40% of salvaged lumber samples is not significantly different from 60% of salvaged lumber samples (p=0.999>0.05) and the Control samples (p=0.993>0.05). Also, control samples are not significantly different than 60% of salvaged lumber samples (p=986>0.05). The null hypothesis that there is no significant difference in MOE of glulam between the different percentages of salvaged lumber samples would be accepted. • The results for One-way ANOVA for MOR values showed a significant difference between the percentage of lumber and MOR of glulam. Tukey post Hoc analysis revealed that 40% of salvaged lumber samples is not significantly different from 60% of salvaged lumber samples (p=0.271>0.05) and the Control samples (p=0.424>0.05). Nevertheless, control samples have significantly more MOR on average than 60% of salvaged lumber samples (p=0.017<0.05). The null hypothesis that there is no significant difference in MOR values of glulam between the different percentages of salvaged lumber samples would be rejected. The alternate hypothesis that there is a significant difference in MOR values of glulam between the different percentages of salvaged lumber samples is accepted, as the p-value for the control sample is greater than 0.05). 64 • The results for One-way ANOVA for MFL values showed a significant difference between the percentage of lumber and maximum flexural strength. Tukey post Hoc analysis revealed that 40% of salvaged lumber samples is not significantly different from 60% of salvaged lumber samples (p=0.250>0.05) and the Control samples (p=0.454>0.05). Nevertheless, control samples have significantly more maximum flexural strength on average than 60% of salvaged lumber samples (p=0.017<0.05). The null hypothesis that there is no significant difference in strength properties of glulam between the different percentages of salvaged lumber samples would be rejected. Percentage Reduction % when compared with control samples of salvaged lumber MOR MOE MFL 40% 4.7% 4.50% 1.35% 60% 10.50% 10.50% 1.90% Table 5.1 Showing percent reduction in MOE, MOR, and MFL values of samples • The data concludes that when compared with control samples of glulam, the glulam manufactured with 60% of salvaged lumber had a reduction of 10.5% in MOR, 10.5% in MFL, and 1.9% in MOE as shown in table 4.1. when compared with control samples of glulam the glulam manufactured with 40% of salvaged lumber had a reduction of 4.7% in MOR, 4.5% in MFL, and 1.35% in MOE. • These reduction percentages are less than 11% for all mechanical properties. In other words, we can say that even for glulam samples made of 60% of salvaged lumber the reduction percentage for all mechanical properties is going to be less than 11%. The reduction percentage for MOE between two consecutive grades turns out to be 33% approximately so we can safely say in absence of any data about a given salvaged sample 65 we can assume that MOE of that salvaged lumber will be one grade below the actual MOE of that sample before use. • This research suggested that minor defects in salvaged lumber have only a small effect on mechanical properties of Glulam panel made of salved lumber as only 7% of samples slipped one grade below the original grade when graded visually. • Glulam panel made of salved lumber can be used in places where were cross sectional area and weight doesn’t play a crucial role. For example, in underground structure and foundations. The size of foundation going underground can be bigger in size and more in weight therefore bigger sized glulam panels can be made of salved lumbers and they can be used for foundation purpose. Additionally, these glulam panels made of salvaged lumber can be used in nonstructural places as well such as in partition walls and other members in the building which are not structural members. 5.2 Future Recommendations The project findings encourage further research to boost this concept towards commercial use by testing the properties of such glulam panels made with various percentages of salvaged lumber on a larger scale. • In this research age of tree, duration of loading, type of loading, moisture content of samples, and density of samples was not taken in the account. Future research can consider these multiple factors and collect larger number of samples to perform statistical analysis for more than two factors. • Another governing factor which has potential to influence on the mechanical properties of the glulam samples is species of the tree from which samples are extracted. Future research 66 can be carried on different species of trees and their effect on the mechanical properties of glulam. • This research was carried out on a very small scale so large sample size will help future research to get more precise results. Also, manufacturing glulam panels in factories with computer aided manufacturing process will help in bolstering the results obtained in this research. Also, automated and computer aided manufacturing process will reduce the chances of human error and will provide uniformity in manufacturing of glulam samples. • We still don’t have any standards for dealing with physical characteristics found in reclaimed wood (e.g., nail holes, fungus, decay, and other damages). Future research can concentrate on developing a standard based on such study where salvaged lumber can be graded based on the in-service damages as well. • Future studies can concentrate on effect of type of glue on mechanical properties of Glulam manufactured with salvaged lumber and try to answer the following research question: Can conventional PUR adhesives be replaced with a non-toxic biodegradable alternative such as lignin? This research will help to replace the commonly used toxic and non- biodegradable adhesives with biodegradable adhesives such as lignin. 67 APPENDICES 68 APPENDIX A MFL and MOR values of raw 186 samples 69 Maximum Extension at Modulus (Young's Flexure Width Thickness MOR Specimen Flexure load Max. load stress 2 mm - 3 mm) SR NO label (mm) (mm) (lbf) (mm) (psi) (psi) 1 1c 25.4 25.4 513.82 9.07 10,790.22 1,311,931.13 2 4b 25.4 25.4 444.56 10.28 9,335.76 1,052,187.70 3 5B 25.4 25.4 376.91 6.8 7,915.11 1,137,494.19 4 6A 25.4 25.4 698.25 11.96 14,663.25 1,633,297.57 5 7A 25.4 25.4 612.88 13.07 12,870.48 1,595,807.54 6 8A 25.4 25.4 483.22 7.9 10,147.62 1,458,909.19 7 9B 25.4 25.4 565.36 11.08 11,872.56 1,480,686.06 8 31A 25.4 25.4 491.27 10.01 10,316.67 1,177,750.45 9 30A 25.4 25.4 388.18 8.38 8,151.78 996,373.50 10 29A 25.4 25.4 558.92 10.96 11,737.32 1,323,818.26 11 28B 25.4 25.4 305.23 7.79 6,409.83 1,091,803.72 12 27A 25.4 25.4 591.13 12.29 12,413.73 1,321,102.66 13 26B 25.4 25.4 548.45 8.04 11,517.45 1,449,260.98 14 25B 25.4 25.4 299.6 7.45 6,291.60 1,170,489.49 15 24A 25.4 25.4 501.74 13.05 10,536.54 1,303,130.17 16 23A 25.4 25.4 308.45 7.63 6,477.45 920,278.49 17 22A 25.4 25.4 414.76 10.62 8,709.96 1,032,574.05 18 41A 25.4 25.4 532.34 11.78 11,179.14 1,367,515.48 19 40A 25.4 25.4 319.73 6.82 6,714.33 918,509.56 20 39A 25.4 25.4 464.69 7.69 9,758.49 1,273,184.19 21 38A 25.4 25.4 425.23 7.56 8,929.83 1,206,640.41 22 37A 25.4 25.4 483.22 9.62 10,147.62 1,134,418.87 23 36A 25.4 25.4 463.89 7.49 9,741.69 1,345,651.36 24 35B 25.4 25.4 328.59 5.53 6,900.39 1,237,263.05 25 34A 25.4 25.4 440.53 9.2 9,251.13 1,220,032.61 26 33A 25.4 25.4 380.13 7.01 7,982.73 1,158,519.06 27 32A 25.4 25.4 498.52 10.81 10,468.92 1,101,553.25 28 48A 25.4 25.4 511.4 12.7 10,739.40 1,275,284.30 29 47A 25.4 25.4 289.13 5.2 6,071.73 1,260,196.48 30 46A 25.4 25.4 628.18 10.09 13,191.78 1,415,894.92 Table 6.1: MFL and MOR values of 186 samples 70 Table 6.1 (Cont’d) Maximum Extension at Modulus (Young's Flexure Width Thickness MOR Specimen Flexure load Max. load stress 2 mm - 3 mm) SR NO label (mm) (mm) (lbf) (mm) (psi) (psi) 31 45A 25.4 25.4 467.91 9.39 9,826.11 1,059,257.61 32 44B 25.4 25.4 436.51 7.84 9,166.71 1,178,408.39 33 43A 25.4 25.4 387.38 7.98 8,134.98 1,164,491.80 34 42A 25.4 25.4 394.63 7.34 8,287.23 1,090,355.70 35 58A 25.4 25.4 714.35 11.13 15,001.35 1,636,469.30 36 57A 25.4 25.4 439.73 9.43 9,234.33 1,201,108.20 37 56A 25.4 25.4 645.9 7.9 13,563.90 1,693,345.12 38 55A 25.4 25.4 235.17 5.79 4,938.57 982,815.75 39 54A 25.4 25.4 477.58 10.64 10,029.18 1,264,976.17 40 53A 25.4 25.4 454.22 9.77 9,538.62 1,166,387.35 41 52A 25.4 25.4 619.32 12.33 13,005.72 1,579,627.17 42 51A 25.4 25.4 530.73 9.59 11,145.33 1,382,680.05 43 50A 25.4 25.4 545.23 14.03 11,449.83 1,268,741.40 44 49A 25.4 25.4 504.16 7.54 10,587.36 1,486,968.02 45 68A 25.4 25.4 436.51 7.01 9,166.71 1,496,250.77 46 67B 25.4 25.4 283.49 6.59 5,953.29 895,942.60 47 66A 25.4 25.4 506.57 11.03 10,637.97 1,281,407.97 48 65A 25.4 25.4 355.17 5.6 7,458.57 1,274,902.65 49 64A 25.4 25.4 537.98 11.51 11,297.58 1,390,963.39 50 63A 25.4 25.4 523.48 10.54 10,993.08 1,271,241.49 51 62A 25.4 25.4 504.16 10.9 10,587.36 1,325,660.06 52 61A 25.4 25.4 506.57 11.85 10,637.97 1,325,007.08 53 60A 25.4 25.4 468.72 9.01 9,843.12 1,375,883.40 54 59A 25.4 25.4 177.99 5.9 3,737.79 755,306.85 55 78A 25.4 25.4 579.86 11.64 12,177.06 1,441,127.83 56 77A 25.4 25.4 508.18 10.31 10,671.78 1,305,408.67 57 76A 25.4 25.4 556.5 11.55 11,686.50 1,469,769.85 58 75B 25.4 25.4 519.46 9.99 10,908.66 1,567,393.42 59 74A 25.4 25.4 506.57 8.61 10,637.97 1,355,152.89 60 73A 25.4 25.4 340.67 6.82 7,154.07 1,286,518.56 61 72A 25.4 25.4 583.08 10.68 12,244.68 1,544,388.24 62 71A 25.4 25.4 624.96 14.23 13,124.16 1,698,816.89 71 Table 6.1 (Cont’d) Maximum Extension at Modulus (Young's Flexure Width Thickness MOR Specimen Flexure load Max. load stress 2 mm - 3 mm) SR NO label (mm) (mm) (lbf) (mm) (psi) (psi) 63 70A 25.4 25.4 525.9 12.42 11,043.90 1,272,231.30 64 69B 25.4 25.4 326.17 6.97 6,849.57 1,118,392.28 65 88B 25.4 25.4 622.54 12.24 13,073.34 1,608,570.04 66 87A 25.4 25.4 592.74 14.85 12,447.54 1,536,825.55 67 86A 25.4 25.4 480.8 9.89 10,096.80 1,175,632.15 68 85A 25.4 25.4 395.43 5.88 8,304.03 1,366,567.84 69 84A 25.4 25.4 454.22 9.29 9,538.62 1,299,344.44 70 83B 25.4 25.4 318.92 5.28 6,697.32 1,264,237.45 71 82A 25.4 25.4 587.11 12.05 12,329.31 1,528,597.35 72 81A 25.4 25.4 336.64 5.9 7,069.44 1,136,664.86 73 80A 25.4 25.4 895.56 11.37 18,806.76 2,032,897.31 74 79A 25.4 25.4 507.38 10.12 10,654.98 1,437,226.97 75 96B 25.4 25.4 568.58 14.46 11,940.18 1,515,297.66 76 95A 25.4 25.4 133.69 4.5 2,807.49 671,453.74 77 94B 25.4 25.4 533.95 9.37 11,212.95 1,511,353.95 78 93A 25.4 25.4 600.8 12.74 12,616.80 1,333,894.41 79 92A 25.4 25.4 666.84 13.5 14,003.64 1,745,922.22 80 91A 25.4 25.4 602.41 9.83 12,650.61 1,784,595.38 81 90A 25.4 25.4 559.72 12.01 11,754.12 1,393,600.06 82 89A 25.4 25.4 492.88 10 10,350.48 1,592,216.02 83 106A 25.4 25.4 527.51 10.11 11,077.71 1,517,667.09 84 107A 25.4 25.4 454.22 10.73 9,538.62 1,122,964.59 85 105A 25.4 25.4 422.01 8.58 8,862.21 1,151,946.05 86 104B 25.4 25.4 353.55 8.69 7,424.55 1,125,708.92 87 103A 25.4 25.4 486.44 13.65 10,215.24 1,250,402.52 88 102B 25.4 25.4 366.44 4.74 7,695.24 1,627,181.68 89 101B 25.4 25.4 696.63 8.95 14,629.23 1,944,057.68 90 100B 25.4 25.4 492.88 10.28 10,350.48 1,536,648.22 91 99A 25.4 25.4 550.06 11.41 11,551.26 1,422,045.65 92 136A 25.4 25.4 859.32 12.15 18,045.72 2,112,386.15 93 116A 25.4 25.4 382.55 8.15 8,033.55 1,238,098.03 94 115A 25.4 25.4 264.97 6.16 5,564.37 1,060,942.49 72 Table 6.1 (Cont’d) Maximum Extension at Modulus (Young's Flexure Width Thickness MOR Specimen Flexure load Max. load stress 2 mm - 3 mm) SR NO label (mm) (mm) (lbf) (mm) (psi) (psi) 95 114A 25.4 25.4 376.91 6.4 7,915.11 1,334,153.13 96 113A 25.4 25.4 761.06 10.94 15,982.26 1,984,216.06 97 112A 25.4 25.4 604.82 10.51 12,701.22 1,507,738.89 98 111A 25.4 25.4 679.72 11.65 14,274.12 1,598,495.44 99 110B 25.4 25.4 196.51 6.22 4,126.71 1,016,853.05 100 109A 25.4 25.4 463.89 8.01 9,741.69 1,462,616.04 101 108A 25.4 25.4 442.14 7.75 9,284.94 1,395,031.07 102 117A 25.4 25.4 392.21 6.26 8,236.41 1,615,081.41 103 118A 25.4 25.4 106.31 4.09 2,232.51 564,258.48 104 119A 25.4 25.4 639.45 13.05 13,428.45 1,610,252.54 105 120A 25.4 25.4 646.7 9.67 13,580.70 1,864,399.87 106 121A 25.4 25.4 495.3 11.64 10,401.30 1,361,644.84 107 122B 25.4 25.4 450.2 7.99 9,454.20 1,444,347.64 108 123A 25.4 25.4 624.15 12.64 13,107.15 1,670,033.19 109 124A 25.4 25.4 451 8.13 9,471.00 1,388,719.58 110 125A 25.4 25.4 591.94 10.39 12,430.74 1,416,569.52 111 126B 25.4 25.4 380.13 7.01 7,982.73 1,367,609.55 112 127B 25.4 25.4 734.49 10.3 15,424.29 2,047,565.53 113 128A 25.4 25.4 475.16 9.23 9,978.36 1,387,634.43 114 129B 25.4 25.4 236.78 4.57 4,972.38 1,034,977.34 115 130B 25.4 25.4 225.5 6.76 4,735.50 953,764.95 116 131A 25.4 25.4 591.13 8.81 12,413.73 1,860,029.88 117 132A 25.4 25.4 552.48 8.67 11,602.08 1,581,763.19 118 133A 25.4 25.4 612.88 11.81 12,870.48 1,715,133.02 119 134A 25.4 25.4 782 15.24 16,422.00 1,898,480.17 120 135B 25.4 25.4 549.26 11.14 11,534.46 1,432,890.57 121 137A 25.4 25.4 227.11 12.29 4,769.31 586,722.73 122 138B 25.4 25.4 356.78 5.23 7,492.38 1,527,098.28 123 139A 25.4 25.4 712.74 13.22 14,967.54 1,725,684.35 124 140A 25.4 25.4 482.41 6.84 10,130.61 1,604,110.43 125 141A 25.4 25.4 431.67 6.71 9,065.07 1,393,810.31 126 142A 25.4 25.4 612.07 9.98 12,853.47 1,510,827.40 73 Table 6.1 (Cont’d) Maximum Extension at Modulus (Young's Flexure Width Thickness MOR Specimen Flexure load Max. load stress 2 mm - 3 mm) SR NO label (mm) (mm) (lbf) (mm) (psi) (psi) 127 143A 25.4 25.4 670.86 8.62 14,088.06 1,961,532.27 128 144A 25.4 25.4 697.44 8.04 14,646.24 2,055,788.16 129 145A 25.4 25.4 571 10.96 11,991.00 1,632,414.70 130 146A 25.4 25.4 568.58 10.9 11,940.18 1,445,922.84 131 147A 25.4 25.4 645.9 13.62 13,563.90 1,576,180.83 132 148A 25.4 25.4 299.6 8.92 6,291.60 987,844.37 133 149A 25.4 25.4 517.04 6.72 10,857.84 1,619,767.58 134 150A 25.4 25.4 538.79 9.93 11,314.59 1,485,537.60 135 151A 25.4 25.4 509.79 9.42 10,705.59 1,427,988.38 136 152A 25.4 25.4 722.41 12.65 15,170.61 1,766,900.69 137 153A 25.4 25.4 554.89 10.44 11,652.69 1,534,296.53 138 154A 25.4 25.4 332.62 6.4 6,985.02 1,363,218.14 139 155B 25.4 25.4 609.66 11.78 12,802.86 1,637,513.61 140 156A 25.4 25.4 741.73 13.17 15,576.33 1,914,347.29 141 157A 25.4 25.4 441.34 7.78 9,268.14 1,257,233.09 142 158A 25.4 25.4 666.03 9.95 13,986.63 1,642,700.63 143 159B 25.4 25.4 389.8 7.99 8,185.80 1,177,038.76 144 160A 25.4 25.4 662.81 11.82 13,919.01 1,729,390.59 145 161B 25.4 25.4 525.09 11.26 11,026.89 1,381,976.69 146 162A 25.4 25.4 637.84 10.82 13,394.64 1,523,372.04 147 163A 25.4 25.4 196.51 7.62 4,126.71 1,019,782.87 148 164B 25.4 25.4 876.23 9.65 18,400.83 2,294,273.58 149 165A 25.4 25.4 614.49 9.67 12,904.29 1,581,372.07 150 166A 25.4 25.4 403.49 5.27 8,473.29 1,619,517.46 151 167A 25.4 25.4 458.25 5.3 9,623.25 1,993,467.65 152 168A 25.4 25.4 384.96 9.39 8,084.16 1,167,953.13 153 169A 25.4 25.4 512.21 11.66 10,756.41 1,356,860.72 154 170A 25.4 25.4 579.86 11.58 12,177.06 1,711,267.22 155 171B 25.4 25.4 777.17 11.92 16,320.57 1,738,878.40 156 172B 25.4 25.4 258.52 4.77 5,428.92 1,135,972.71 157 173B 25.4 25.4 361.61 6.24 7,593.81 1,477,280.98 158 174A 25.4 25.4 404.29 6.93 8,490.09 1,451,690.40 74 Table 6.1 (Cont’d) Maximum Extension at Modulus (Young's Flexure Width Thickness MOR Specimen Flexure load Max. load stress 2 mm - 3 mm) SR NO label (mm) (mm) (lbf) (mm) (psi) (psi) 159 175A 25.4 25.4 732.07 10.22 15,373.47 2,059,695.10 160 176A 25.4 25.4 695.83 9.65 14,612.43 2,194,450.49 161 167A 25.4 25.4 458.25 5.3 9,623.25 1,993,467.65 162 168A 25.4 25.4 384.96 9.39 8,084.16 1,167,953.13 163 169A 25.4 25.4 512.21 11.66 10,756.41 1,356,860.72 164 170A 25.4 25.4 579.86 11.58 12,177.06 1,711,267.22 165 171B 25.4 25.4 777.17 11.92 16,320.57 1,738,878.40 166 172B 25.4 25.4 258.52 4.77 5,428.92 1,135,972.71 167 173B 25.4 25.4 361.61 6.24 7,593.81 1,477,280.98 168 174A 25.4 25.4 404.29 6.93 8,490.09 1,451,690.40 169 175A 25.4 25.4 732.07 10.22 15,373.47 2,059,695.10 170 176A 25.4 25.4 695.83 9.65 14,612.43 2,194,450.49 171 177B 25.4 25.4 220.67 9.74 4,634.07 1,252,822.27 172 178B 25.4 25.4 87.79 2.95 1,843.59 0 173 179B 25.4 25.4 471.14 8.31 9,893.94 1,574,055.85 174 180A 25.4 25.4 569.39 9.85 11,957.19 1,404,668.12 175 181B 25.4 25.4 515.43 8.3 10,824.03 1,643,890.69 176 182A 25.4 25.4 430.87 13.09 9,048.27 1,336,496.15 177 183A 25.4 25.4 358.39 6.28 7,526.19 1,252,074.51 178 184B 25.4 25.4 545.23 6.49 11,449.83 1,817,144.54 179 185A 25.4 25.4 379.33 6.92 7,965.93 1,359,780.00 180 186B 25.4 25.4 475.97 7.91 9,995.37 1,299,367.02 181 187A 25.4 25.4 166.71 4.96 3,500.91 1,136,208.76 182 191 A 25.4 25.4 494.49 12.05 10,384.29 1,417,713.59 183 190 A 25.4 25.4 496.91 13.75 10,435.11 1,072,324.49 184 189 A 25.4 25.4 611.27 9.7 12,836.67 1,574,646.78 185 188 A 25.4 25.4 8.06 3.55 169.26 6,859,858.77 186 OUTLIER 25.4 25.4 572.61 11.66 12,024.81 1,700,098.33 75 APPENDIX B MOE values of raw samples obtained from Metriguard 76 Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 1 1 1.98 4 0.553 62.6 15.8 3.77 2 1.98 4 0.553 62.6 15.8 3.78 3 1.98 4 0.553 62.6 15.8 3.78 4 2.06 4 0.57 64.6 15.8 3.79 5 2.06 4 0.57 64.6 15.8 3.79 6 2.06 4 0.569 64.4 15.8 3.8 2 1 2.63 1 0.708 80.9 16 3.77 2 2.63 1 0.708 80.9 16 3.77 3 2.63 1 0.708 80.9 16 3.77 4 2.72 1 0.736 84.1 16 3.76 5 2.72 1 0.735 84 16 3.77 6 2.73 1 0.736 84.1 16 3.77 3 1 2.18 3 0.635 72.6 16 3.62 2 2.17 3 0.635 72.6 16 3.62 3 2.16 3 0.635 72.6 16 3.61 4 2.21 3 0.645 73.8 16 3.62 5 2.21 3 0.646 73.9 16 3.61 6 2.22 3 0.647 74 16 3.62 4 1 1.95 4 0.506 57.9 16 3.86 2 1.96 4 0.506 57.9 16 3.86 3 1.95 4 0.505 57.7 16 3.86 4 2.04 4 0.53 60.6 16 3.85 5 2.04 4 0.531 60.7 16 3.85 6 2.04 4 0.532 60.8 16 3.84 5 1 2.06 4 0.569 64.9 16 3.75 2 2.05 4 0.569 64.9 16 3.75 3 2.06 4 0.569 64.9 16 3.75 4 2.18 3 0.603 68.7 16 3.75 5 2.17 3 0.602 68.6 16 3.75 6 2.18 3 0.603 68.7 16 3.75 Table 6.2: MOE values of raw sample obtained from Metriguard 77 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 6 1 1.99 4 0.611 69.9 16 3.53 2 1.99 4 0.613 70.1 16 3.52 3 1.99 4 0.612 70 16 3.52 4 1.89 4 0.583 66.6 16 3.52 5 1.9 4 0.584 66.7 16 3.53 6 1.9 4 0.584 66.7 16 3.52 7 1 1.33 4 0.539 61.6 16 3.07 2 1.33 4 0.541 61.9 16 3.07 3 1.33 4 0.539 61.6 16 3.07 4 1.32 4 0.537 61.4 16 3.06 5 1.32 4 0.537 61.4 16 3.06 6 1.33 4 0.539 61.6 16 3.07 8 1 2.11 3 0.569 64.3 15.8 3.85 2 2.13 3 0.568 64.2 15.8 3.87 3 2.09 4 0.569 64.3 15.8 3.84 4 2.11 3 0.577 65.2 15.8 3.82 5 2.09 4 0.577 65.2 15.8 3.81 6 2.1 3 0.577 65.2 15.8 3.82 9 1 2.83 1 0.664 75.9 16 4.03 2 2.85 1 0.664 75.9 16 4.05 3 2.85 1 0.665 76 16 4.05 4 2.77 1 0.64 73.1 16 4.06 5 2.75 1 0.64 73.1 16 4.05 6 2.74 1 0.639 73 16 4.05 10 1 1.94 4 0.537 60.7 15.8 3.81 2 1.95 4 0.537 60.7 15.8 3.81 3 1.96 4 0.537 60.7 15.8 3.82 4 1.95 4 0.539 60.9 15.8 3.81 5 1.94 4 0.539 60.9 15.8 3.79 6 1.93 4 0.539 60.9 15.8 3.79 11 1 1.56 4 0.549 62.8 15.8 3.37 2 1.56 4 0.55 62.9 15.8 3.37 3 1.55 4 0.549 62.8 15.8 3.37 4 1.54 4 0.543 62.1 15.8 3.37 78 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 5 1.54 4 0.544 62.2 15.8 3.37 6 1.54 4 0.543 62.1 15.8 3.37 12 1 1.87 4 0.562 64.3 15.8 3.64 2 1.86 4 0.562 64.3 15.8 3.64 3 1.86 4 0.56 64.1 15.8 3.64 4 1.77 4 0.539 61.6 15.8 3.63 5 1.77 4 0.539 61.6 15.8 3.63 6 1.77 4 0.537 61.4 15.8 3.63 13 1 2.34 3 0.625 71.4 16 3.78 2 2.33 3 0.625 71.4 16 3.78 3 2.33 3 0.625 71.4 16 3.78 4 2.48 2 0.67 76.6 16 3.76 5 2.48 2 0.668 76.4 16 3.77 6 2.48 2 0.667 76.3 16 3.77 14 1 2.94 1 0.699 79.9 16 4.01 2 2.94 1 0.7 80 16 4.01 3 2.94 1 0.699 79.9 16 4.01 4 2.81 1 0.671 76.7 16 4.01 5 2.82 1 0.671 76.7 16 4.01 6 2.82 1 0.673 77 16 4.01 15 1 2.91 1 0.648 74.1 16 4.14 2 2.9 1 0.647 74 16 4.14 3 2.91 1 0.648 74.1 16 4.14 4 2.69 1 0.598 68.4 16 4.15 5 2.69 1 0.598 68.4 16 4.15 6 2.69 1 0.597 68.3 16 4.15 16 1 1.81 4 0.521 59.9 15.9 3.7 2 1.82 4 0.52 59.8 15.9 3.71 3 1.81 4 0.519 59.7 15.9 3.7 4 1.76 4 0.514 59.1 15.9 3.67 5 1.74 4 0.513 59 15.9 3.66 6 1.75 4 0.515 59.2 15.9 3.66 17 1 1.48 4 0.512 59.1 16 3.35 79 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 2 1.49 4 0.512 59.1 16 3.35 3 1.48 4 0.512 59.1 16 3.35 4 1.53 4 0.524 60.5 16 3.36 5 1.53 4 0.524 60.5 16 3.36 6 1.53 4 0.525 60.6 16 3.37 18 1 2.24 3 0.611 69.8 16 3.77 2 2.26 3 0.611 69.8 16 3.78 3 2.24 3 0.611 69.8 16 3.77 4 2.19 3 0.608 69.4 16 3.73 5 2.19 3 0.608 69.4 16 3.73 6 2.21 3 0.608 69.4 16 3.75 19 1 2.24 3 0.563 64.5 15.9 3.98 2 2.23 3 0.562 64.4 15.9 3.99 3 2.23 3 0.561 64.3 15.9 3.98 4 2.33 3 0.587 67.3 15.9 3.99 5 2.33 3 0.587 67.3 15.9 3.98 6 2.33 3 0.586 67.1 15.9 3.98 20 1 2.09 4 0.601 69.4 16 3.67 2 2.09 4 0.6 69.3 16 3.67 3 2.1 3 0.602 69.6 16 3.68 4 2.12 3 0.607 70.1 16 3.68 5 2.12 3 0.607 70.1 16 3.68 6 2.12 3 0.605 69.9 16 3.68 21 1 2.31 3 0.654 74.7 16 3.69 2 2.31 3 0.653 74.6 16 3.69 3 2.31 3 0.653 74.6 16 3.69 4 2.25 3 0.636 72.6 16 3.69 5 2.25 3 0.636 72.6 16 3.69 6 2.25 3 0.636 72.6 16 3.69 22 1 2.1 3 0.583 66.5 16 3.75 2 2.1 3 0.584 66.6 16 3.74 3 2.1 4 0.582 66.3 16 3.74 4 2.01 4 0.56 63.8 16 3.74 5 2.01 4 0.56 63.8 16 3.74 80 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 6 2.01 4 0.559 63.7 16 3.74 23 1 2.26 3 0.661 75.5 16 3.63 2 2.26 3 0.661 75.5 16 3.64 3 2.27 3 0.661 75.5 16 3.64 4 2.21 3 0.645 73.7 16 3.64 5 2.2 3 0.644 73.6 16 3.64 6 2.21 3 0.644 73.6 16 3.64 24 1 2.24 3 0.619 70.7 16 3.75 2 2.25 3 0.619 70.7 16 3.75 3 2.24 3 0.618 70.6 16 3.75 4 2.27 3 0.628 71.7 16 3.74 5 2.27 3 0.628 71.7 16 3.74 6 2.27 3 0.627 71.6 16 3.74 25 1 1.94 4 0.53 60.5 16 3.76 2 1.94 4 0.53 60.5 16 3.76 3 1.94 4 0.53 60.5 16 3.76 4 2.07 4 0.565 64.5 16 3.77 5 2.07 4 0.565 64.5 16 3.77 6 2.07 4 0.565 64.5 16 3.77 26 1 1.03 4 0.532 60.2 15.8 2.79 2 1.02 4 0.532 60.2 15.8 2.78 3 1.03 4 0.532 60.2 15.8 2.79 4 0.94 8 0.486 55 15.8 2.79 5 0.94 8 0.486 55 15.8 2.79 6 0.94 8 0.485 54.9 15.8 2.79 27 1 1.72 4 0.547 61.6 15.8 3.59 2 1.72 4 0.548 61.8 15.8 3.59 3 1.73 4 0.548 61.8 15.8 3.59 4 1.67 4 0.532 59.9 15.8 3.59 5 1.67 4 0.531 59.8 15.8 3.59 6 1.67 4 0.533 60 15.8 3.59 28 1 1.75 4 0.552 62.4 15.8 3.57 2 1.75 4 0.553 62.6 15.8 3.57 81 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 3 1.75 4 0.553 62.6 15.8 3.57 4 1.72 4 0.541 61.2 15.8 3.58 5 1.71 4 0.539 61 15.8 3.58 6 1.72 4 0.54 61.1 15.8 3.58 29 1 1.73 4 0.603 67.9 15.8 3.42 2 1.74 4 0.603 67.9 15.8 3.43 3 1.73 4 0.603 67.9 15.8 3.43 4 1.67 4 0.585 65.9 15.8 3.42 5 1.67 4 0.585 65.9 15.8 3.42 6 1.67 4 0.584 65.8 15.8 3.42 30 1 1.85 4 0.532 60.8 16 3.66 2 1.85 4 0.533 61 16 3.66 3 1.86 4 0.532 60.8 16 3.67 4 1.93 4 0.549 62.8 16 3.69 5 1.92 4 0.548 62.7 16 3.68 6 1.93 4 0.549 62.8 16 3.68 31 1 2.25 3 0.664 75.9 16 3.62 2 2.26 3 0.664 75.9 16 3.62 3 2.25 3 0.665 76 16 3.62 4 2.44 2 0.72 82.3 16 3.62 5 2.45 2 0.719 82.2 16 3.62 6 2.45 2 0.72 82.3 16 3.62 32 1 2.51 2 0.65 73.8 15.9 3.91 2 2.5 2 0.65 73.8 15.9 3.9 3 2.51 2 0.652 74 15.9 3.9 4 2.36 3 0.617 70 15.9 3.89 5 2.36 3 0.615 69.7 15.9 3.89 6 2.36 3 0.615 69.7 15.9 3.9 33 1 3.48 1 0.744 85 16 4.23 2 3.49 1 0.745 85.1 16 4.24 3 3.5 1 0.747 85.4 16 4.24 4 3.58 1 0.763 87.2 16 4.24 5 3.57 1 0.761 87 16 4.24 6 3.58 1 0.763 87.2 16 4.25 82 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 34 1 2.35 3 0.579 64.7 16 3.95 2 2.36 3 0.58 64.8 16 3.95 3 2.35 3 0.579 64.7 16 3.95 4 2.5 2 0.622 69.5 16 3.93 5 2.5 2 0.621 69.4 16 3.93 6 2.51 2 0.623 69.6 16 3.93 35 1 2.41 2 0.699 79.2 15.8 3.71 2 2.4 2 0.699 79.2 15.8 3.71 3 2.4 2 0.699 79.2 15.8 3.71 4 2.22 3 0.642 72.6 15.8 3.72 5 2.22 3 0.644 72.8 15.8 3.71 6 2.23 3 0.644 72.8 15.8 3.72 36 1 2.23 3 0.64 74.4 16 3.66 2 2.23 3 0.64 74.4 16 3.66 3 2.23 3 0.642 74.7 16 3.66 4 2.38 3 0.686 79.9 16 3.65 5 2.38 3 0.684 79.6 16 3.65 6 2.38 3 0.686 79.9 16 3.65 37 1 2.41 2 0.649 74.2 16 3.77 2 2.4 3 0.647 74 16 3.77 3 2.41 2 0.649 74.2 16 3.77 4 2.53 2 0.693 79.2 16 3.75 5 2.54 2 0.693 79.2 16 3.75 6 2.53 2 0.693 79.2 16 3.75 38 1 2.33 3 0.602 68.8 16 3.85 2 2.33 3 0.603 68.9 16 3.85 3 2.34 3 0.602 68.8 16 3.86 4 2.21 3 0.565 64.7 16 3.87 5 2.22 3 0.565 64.7 16 3.88 6 2.22 3 0.566 64.8 16 3.88 39 1 2.08 4 0.523 59.8 16 3.9 2 2.08 4 0.524 59.9 16 3.9 3 2.08 4 0.523 59.8 16 3.9 83 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 4 2.13 3 0.538 61.6 16 3.89 5 2.14 3 0.54 61.8 16 3.89 6 2.13 3 0.538 61.6 16 3.9 40 1 2.1 4 0.577 65.9 16 3.74 2 2.11 3 0.579 66.2 16 3.74 3 2.1 4 0.578 66 16 3.74 4 2.23 3 0.612 70 16 3.75 5 2.23 3 0.612 70 16 3.75 6 2.23 3 0.613 70.1 16 3.74 41 1 1.93 4 0.523 59.1 15.8 3.85 2 1.93 4 0.523 59.1 15.8 3.85 3 1.93 4 0.523 59.1 15.8 3.85 4 2.01 4 0.544 61.6 15.8 3.85 5 2.01 4 0.543 61.4 15.8 3.85 6 2.01 4 0.543 61.4 15.8 3.85 42 1 2.41 2 0.654 74.8 16 3.76 2 2.43 2 0.654 74.8 16 3.78 3 2.41 2 0.654 74.8 16 3.77 4 2.45 2 0.667 76.2 16 3.76 5 2.45 2 0.667 76.2 16 3.76 6 2.44 2 0.667 76.2 16 3.76 43 1 1.76 4 0.611 69.8 16 3.33 2 1.75 4 0.609 69.5 16 3.33 3 1.76 4 0.612 69.9 16 3.33 4 1.84 4 0.638 72.9 16 3.33 5 1.99 4 0.664 75.8 16 3.39 6 1.82 4 0.634 72.4 16 3.33 44 1 1.8 4 0.501 57.2 16 3.72 2 1.58 4 0.522 59.7 16 3.41 3 1.8 4 0.501 57.2 16 3.72 4 1.91 4 0.526 60.1 16 3.74 5 1.85 4 0.513 58.6 16 3.73 6 1.85 4 0.513 58.6 16 3.72 84 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 45 1 1.87 4 0.549 62.7 16 3.63 2 1.88 4 0.55 62.8 16 3.63 3 1.87 4 0.548 62.6 16 3.63 4 1.9 4 0.571 65.2 16 3.57 5 1.82 4 0.534 61 16 3.63 6 1.9 4 0.551 62.9 16 3.64 46 1 2.45 2 0.653 74.7 16 3.8 2 2.46 2 0.655 74.9 16 3.8 3 2.45 2 0.654 74.8 16 3.8 4 2.34 3 0.627 71.6 16 3.79 5 2.35 3 0.628 71.7 16 3.8 6 2.42 2 0.636 72.7 16 3.83 47 1 2.58 2 0.695 79.4 16 3.78 2 2.58 2 0.694 79.3 16 3.79 3 2.62 1 0.706 80.7 16 3.78 4 2.69 1 0.727 83 16 3.78 5 2.68 1 0.726 82.9 16 3.77 6 2.68 1 0.724 82.7 16 3.78 48 1 2.97 1 0.719 81.7 15.9 4.03 2 2.98 1 0.718 81.6 15.9 4.04 3 2.98 1 0.718 81.6 15.9 4.04 4 2.87 1 0.695 79 15.9 4.03 5 2.86 1 0.695 79 15.9 4.02 6 2.88 1 0.695 79 15.9 4.03 49 1 2.48 2 0.609 69.5 16 3.96 2 2.48 2 0.608 69.4 16 3.96 3 2.49 2 0.611 69.8 16 3.96 4 2.42 2 0.591 67.6 16 3.97 5 2.42 2 0.592 67.7 16 3.97 6 2.41 2 0.596 68.1 16 3.94 50 1 1.88 4 0.576 65.8 16 3.54 2 1.88 4 0.576 65.8 16 3.55 3 1.89 4 0.578 66 16 3.54 4 1.78 4 0.545 62.2 16 3.54 85 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 5 1.79 4 0.545 62.2 16 3.56 6 1.79 4 0.547 62.4 16 3.55 51 1 1.43 4 0.505 57.7 16 3.3 2 1.43 4 0.506 57.8 16 3.3 3 1.43 4 0.505 57.7 16 3.3 4 1.47 4 0.518 59.2 16 3.31 5 1.47 4 0.519 59.3 16 3.31 6 1.47 4 0.518 59.2 16 3.31 52 1 2.1 3 0.593 67.8 16 3.69 2 2.1 4 0.593 67.8 16 3.69 3 2.09 4 0.591 67.6 16 3.69 4 2.34 3 0.665 75.9 16 3.68 5 2.35 3 0.666 76 16 3.69 6 2.34 3 0.664 75.8 16 3.68 53 1 1.74 4 0.541 61.6 15.9 3.54 2 1.75 4 0.544 62 15.9 3.54 3 1.74 4 0.542 61.7 15.9 3.54 4 1.7 4 0.523 59.5 15.9 3.57 5 1.7 4 0.523 59.5 15.9 3.57 6 1.7 4 0.523 59.5 15.9 3.56 54 1 1.67 4 0.654 74.1 15.8 3.19 2 1.68 4 0.657 74.3 15.8 3.19 3 1.67 4 0.654 74.1 15.8 3.19 4 1.65 4 0.646 73.1 15.8 3.19 5 1.66 4 0.648 73.4 15.8 3.2 6 1.65 4 0.646 73.1 15.8 3.19 55 1 2.47 2 0.649 74.2 16 3.82 2 2.46 2 0.649 74.2 16 3.82 3 2.46 2 0.649 74.2 16 3.82 4 2.62 1 0.698 79.8 16 3.8 5 2.61 1 0.697 79.7 16 3.8 6 2.62 1 0.698 79.8 16 3.8 56 1 2.42 2 0.663 75.7 16 3.75 86 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 2 2.42 2 0.664 75.8 16 3.75 3 2.42 2 0.663 75.7 16 3.75 4 2.33 3 0.635 72.6 16 3.75 5 2.47 2 0.638 72.9 16 3.86 6 2.33 3 0.635 72.6 16 3.76 57 1 1.84 4 0.61 70.5 16 3.43 2 1.84 4 0.61 70.5 16 3.43 3 1.84 4 0.609 70.4 16 3.43 4 1.76 4 0.577 66.7 16 3.45 5 1.76 4 0.577 66.7 16 3.45 6 1.75 4 0.577 66.7 16 3.44 58 1 2.03 4 0.674 77 16 3.43 2 2.03 4 0.672 76.7 16 3.43 3 2.03 4 0.674 77 16 3.43 4 1.93 4 0.634 72.4 16 3.45 5 1.92 4 0.634 72.4 16 3.44 6 1.92 4 0.635 72.5 16 3.43 59 1 1.99 4 0.644 73.6 16 3.47 2 1.98 4 0.644 73.6 16 3.47 3 1.99 4 0.644 73.6 16 3.47 4 1.94 4 0.629 71.8 16 3.47 5 1.95 4 0.631 72 16 3.47 6 1.95 4 0.63 71.9 16 3.47 60 1 2.27 3 0.578 66 16 3.92 2 2.28 3 0.576 65.7 16 3.93 3 2.28 3 0.578 66 16 3.93 4 2.35 3 0.605 69 16 3.9 5 2.35 3 0.605 69 16 3.9 6 2.36 3 0.607 69.2 16 3.9 61 1 2.47 2 0.69 78.1 15.8 3.81 2 2.46 2 0.688 77.9 15.8 3.81 3 2.46 2 0.688 77.9 15.8 3.81 4 2.33 3 0.652 73.8 15.8 3.8 5 2.33 3 0.652 73.8 15.8 3.81 87 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 6 2.36 3 0.656 74.3 15.8 3.82 62 1 1.75 4 0.499 57 16 3.7 3 1.75 4 0.498 56.9 16 3.7 4 1.74 4 0.498 56.9 16 3.7 5 1.8 4 0.514 58.7 16 3.7 6 1.8 4 0.513 58.6 16 3.7 63 1 1.62 4 0.583 66.4 16 3.31 2 1.63 4 0.583 66.4 16 3.31 3 1.62 4 0.581 66.3 16 3.31 4 1.59 4 0.575 65.6 16 3.29 5 1.6 4 0.577 65.9 16 3.29 6 1.6 4 0.577 65.9 16 3.29 64 1 2.2 3 0.642 73.3 16 3.66 2 2.21 3 0.643 73.5 16 3.66 3 2.2 3 0.641 73.2 16 3.66 4 2.28 3 0.668 76.4 16 3.65 5 2.29 3 0.672 76.7 16 3.65 6 2.29 3 0.671 76.6 16 3.65 65 1 1.58 4 0.65 74.3 16 3.08 2 1.58 4 0.649 74.2 16 3.08 3 1.58 4 0.649 74.2 16 3.08 4 1.47 4 0.604 69 16 3.08 5 1.47 4 0.603 68.9 16 3.08 6 1.47 4 0.602 68.8 16 3.08 66 1 1.87 4 0.543 62 16 3.66 2 1.86 4 0.542 61.9 16 3.66 3 1.86 4 0.542 61.9 16 3.66 4 1.81 4 0.527 60.3 16 3.66 5 1.8 4 0.525 60 16 3.66 6 1.8 4 0.525 60 16 3.66 67 1 2.03 4 0.638 72.9 16 3.52 2 2.03 4 0.637 72.7 16 3.53 3 2.03 4 0.638 72.9 16 3.52 88 Table 6.2 (Cont’d) Weight Sample Number Run Number E [Mpsi] Grade SG Length [ft] Freq. [Hz] [lbs] 4 2.04 4 0.637 72.7 16 3.54 5 2.04 4 0.636 72.6 16 3.54 6 2.03 4 0.636 72.6 16 3.53 68 1 2.15 3 0.545 62.2 16 3.92 2 2.16 3 0.548 62.6 16 3.92 3 2.15 3 0.546 62.4 16 3.92 4 1.85 4 0.467 53.4 16 3.93 5 1.85 4 0.466 53.2 16 3.93 6 1.84 4 0.464 53 16 3.93 89 APPENDIX C MFL and MOR values of selected 82 samples 90 Modulus Maximum Extension (Young's Specimen Width Thickness Flexure at Max MOR SR Flexure stress 2 label load load mm - 3 mm) (mm) (mm) (lbf) (mm) (psi) (psi) 1 37AaR 25.4 25.4 723.54 12.79 15,194.24 1,821,637.58 2 35AbM 25.4 25.4 577.94 7.11 12,136.78 1,792,798.69 3 35AbL 25.4 25.4 868.22 13 18,232.71 1,866,389.70 4 35AcR 25.4 25.4 421.7 5.93 8,855.70 1,420,019.39 5 35AcM 25.4 25.4 900.19 11.1 18,904.02 2,015,357.42 6 34BaR 25.4 25.4 900.19 12.34 18,904.02 2,254,493.94 7 35AcL 25.4 25.4 774.13 11.02 16,256.75 1,980,164.70 8 32AaL 25.4 25.4 919.72 13.9 19,314.21 2,188,501.72 9 66AbM 25.4 25.4 674.7 15.99 14,168.76 1,642,384.41 10 66AbL 25.4 25.4 5.34 0 112.04 ----- 11 66AbL 25.4 25.4 784.78 15.31 16,480.37 1,709,953.65 12 66AbR 25.4 25.4 579.71 10.83 12,173.82 1,240,722.02 13 4BbL 25.4 25.4 625.87 10.31 13,143.28 1,512,460.17 14 39AcM 25.4 25.4 731.52 14.22 15,361.83 1,657,821.99 15 63BaM 25.4 25.4 424.35 10.41 8,911.26 1,438,521.13 16 54BaL 25.4 25.4 418.15 7.38 8,781.16 1,209,491.55 17 41BbL 25.4 25.4 6.22 0.43 130.56 ----- 18 41BbL 25.4 25.4 679.13 12.3 14,261.81 1,566,470.22 19 63BaL 25.4 25.4 741.28 13.18 15,566.93 1,619,394.97 20 39AcL 25.4 25.4 573.49 9.21 12,043.26 1,513,158.64 21 39AcR 25.4 25.4 688.9 12.81 14,466.91 1,634,996.77 22 37AaL 25.4 25.4 848.69 13.86 17,822.52 2,002,453.17 23 37AaM 25.4 25.4 863.79 12.11 18,139.65 2,049,126.84 24 41BbM 25.4 25.4 709.32 11.1 14,895.62 1,580,547.69 25 41BbR 25.4 25.4 460.74 9.07 9,675.62 1,145,648.28 26 46AcM 25.4 25.4 680.02 7.16 14,280.33 2,190,092.91 Table 6.3: MFL and MOR samples of selected 82 samples 91 Table 6.3 (Cont’d) Modulus Maximum Extension (Young's Specimen Width Thickness Flexure at Max MOR SR Flexure stress 2 label load load mm - 3 mm) (mm) (mm) (lbf) (mm) (psi) (psi) 27 48BaM 25.4 25.4 818.51 11.68 17,188.71 2,107,911.11 28 34BaM 25.4 25.4 740.4 13.67 15,548.41 2,066,032.15 29 34BaL 25.4 25.4 795.43 12.81 16,703.98 2,019,483.10 30 54AcR 25.4 25.4 562.84 11 11,819.64 1,322,618.13 31 54AcM 25.4 25.4 545.09 8.61 11,446.95 1,386,263.26 32 14BcM 25.4 25.4 925.04 14.9 19,425.79 2,279,256.19 33 37AcL 25.4 25.4 831.83 13.26 17,468.35 1,958,755.89 34 32AaR 25.4 25.4 831.83 14.62 17,468.35 1,669,604.78 35 32AaM 25.4 25.4 781.23 9.79 16,405.83 1,988,730.03 36 6AbM 25.4 25.4 768.8 12.5 16,144.71 1,464,829.43 37 4BbR 25.4 25.4 744.83 13.02 15,641.47 1,670,498.26 38 6AbL 25.4 25.4 795.43 13.87 16,703.98 1,481,410.45 39 4BbM 25.4 25.4 694.24 12.81 14,578.95 1,619,735.76 40 4BcR 25.4 25.4 677.37 12.59 14,224.77 1,623,109.88 41 63BaR 25.4 25.4 666.7 8.88 14,000.70 1,687,831.43 42 4BcM 25.4 25.4 721.75 11.38 15,156.74 1,880,163.50 43 4BcL 25.4 25.4 774.13 15.38 16,256.75 1,809,696.76 44 46AcL 25.4 25.4 947.24 11.22 19,892.00 2,223,754.61 45 46AcR 25.4 25.4 641.85 7.17 13,478.93 1,814,996.26 46 48BaL 25.4 25.4 790.11 10.42 16,592.41 2,051,822.02 47 48BaR 25.4 25.4 721.75 11.82 15,156.74 1,894,599.97 48 54AcR 25.4 25.4 841.59 14.46 17,673.44 1,780,289.30 49 54AcL 25.4 25.4 578.82 10.86 12,155.30 1,341,018.74 50 56AaL 25.4 25.4 709.32 11.48 14,895.62 1,786,190.35 51 54AcM 25.4 25.4 647.19 14.15 13,590.97 1,336,473.79 52 38BbR 25.4 25.4 653.95 9.54 13,732.95 1,587,494.89 53 8BbR 25.4 25.4 618.52 11.38 12,988.92 1,449,163.17 54 68AaM 25.4 25.4 721.6 12 15,153.60 1,889,539.52 55 68AaR 25.4 25.4 674.89 12.4 14,172.69 1,714,466.37 56 68AaL 25.4 25.4 662 11.27 13,902.00 1,859,132.73 57 32BcR 25.4 25.4 808.74 12.25 16,983.62 1,987,273.86 92 Table 6.3 (Cont’d) Modulus Maximum Extension (Young's Specimen Width Thickness Flexure at Max MOR SR Flexure stress 2 label load load mm - 3 mm) (mm) (mm) (lbf) (mm) (psi) (psi) 58 32BcM 25.4 25.4 930.37 11.98 19,537.83 2,207,434.18 59 1BcM 25.4 25.4 743.05 9.49 15,603.96 1,856,833.98 60 32BcL 25.4 25.4 881.54 12.2 18,512.35 2,094,528.34 61 27BbR 25.4 25.4 335.59 5.94 7,047.34 1,239,332.47 62 27BbM 25.4 25.4 655.17 12.03 13,758.56 1,612,146.31 63 38BbL 25.4 25.4 670.86 11.64 14,088.06 1,561,814.25 64 60AcM 25.4 25.4 644.29 7.72 13,530.09 1,807,677.19 65 60AcL 25.4 25.4 686.97 11.78 14,426.37 1,478,893.00 66 47AaL 25.4 25.4 1,014.75 9.98 21,309.75 2,331,981.29 67 37AcR 25.4 25.4 832.74 15.18 17,487.54 1,897,098.12 68 47AaM 25.4 25.4 1,219.31 12.35 25,605.51 2,721,824.79 69 28AcL 25.4 25.4 725.63 11.75 15,238.23 1,679,727.45 70 28AcM 25.4 25.4 569.39 8.35 11,957.19 1,608,276.15 71 28AcR 25.4 25.4 744.15 10.76 15,627.15 1,679,541.52 72 37AcM 25.4 25.4 608.85 12.5 12,785.85 1,234,104.40 73 1BcL 25.4 25.4 587.11 11.91 12,329.31 1,362,055.05 74 14BcL 25.4 25.4 1,024.41 11.03 21,512.61 2,579,136.06 75 20AcM 25.4 25.4 575.03 11.42 12,075.63 1,197,952.23 76 20AcL 25.4 25.4 801.33 15.19 16,827.93 1,625,123.89 77 20AcR 25.4 25.4 547.64 14.83 11,500.44 1,204,071.96 78 56BaR 25.4 25.4 702.27 10.47 14,747.67 1,563,913.31 79 56BaM 25.4 25.4 703.88 9.98 14,781.48 1,840,825.31 80 8BbM 25.4 25.4 575.83 8.56 12,092.43 1,438,616.52 81 56BaL 25.4 25.4 695.83 9.7 14,612.43 1,911,981.80 82 8BbL 25.4 25.4 633.82 9.2 13,310.22 1,481,203.62 93 APPENDIX D Visual grading of 27 samples 94 KNOTS NAIL HOLES (1/8 in.) DAMAGE Sampl Run SHAKE/ END SLOPE e E Gra Weight Length Freq. Wide Gra Wide Numbe SG Narrow Wide face CHECK SPLIT OF Grade Numbe [Mpsi] de [lbs] [ft] [Hz] face de Narrow face Wide face Wide face Wide face Edge r face Centerline (in.) (in.) GRAIN Narrow face (in.) r Edge face Center Edge Centerline (in.) (in.) (in.) (in.) (in.) line 4 screw 39 1 2.08 4 0.523 59.8 16 3.9 0 10.25 0 15 4 1 <1:10 1 0 8 holes (0.5” l b h l b h l b h dia) 2 2.08 4 0.524 59.9 16 3.9 3 2.08 4 0.523 59.8 16 3.9 4 2.13 3 0.538 61.6 16 3.89 5 2.14 3 0.54 61.8 16 3.89 6 2.13 3 0.538 61.6 16 3.9 4 screw 0. 40 1 2.1 4 0.577 65.9 16 3.74 0 0 0 12 4 1 <1:10 1 1 13 holes (0.5” 0 0 0 0 0 0 10 0.5 5 dia) 0. 2 2.11 3 0.579 66.2 16 3.74 15 0.5 5 3 2.1 4 0.578 66 16 3.74 4 2.23 3 0.612 70 16 3.75 5 2.23 3 0.612 70 16 3.75 6 2.23 3 0.613 70.1 16 3.74 4 screw 41 1 1.93 4 0.523 59.1 15.8 3.85 0 21 0 16 0 1 <1:10 1 0 11 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 2 1.93 4 0.523 59.1 15.8 3.85 3 1.93 4 0.523 59.1 15.8 3.85 4 2.01 4 0.544 61.6 15.8 3.85 5 2.01 4 0.543 61.4 15.8 3.85 6 2.01 4 0.543 61.4 15.8 3.85 4 screw 42 1 2.41 2 0.654 74.8 16 3.76 0 4.5 0 0 0 1 <1:10 1 2 11 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 2 2.43 2 0.654 74.8 16 3.78 3 2.41 2 0.654 74.8 16 3.77 4 2.45 2 0.667 76.2 16 3.76 5 2.45 2 0.667 76.2 16 3.76 6 2.44 2 0.667 76.2 16 3.76 Table 6.4: Visual grading of 27 samples 95 Table 6.4 (Cont’d) KNOTS NAIL HOLES (1/8 in.) DAMAGE Sampl Run SHAKE/ END SLOPE e E Gra Weight Length Freq. Wide Gra Wide Numbe SG Narrow Wide face CHECK SPLIT OF Grade Numbe [Mpsi] de [lbs] [ft] [Hz] face de Narrow face Wide face Wide face Wide face Edge r face Centerline (in.) (in.) GRAIN Narrow face (in.) r Edge face Center Edge Centerline (in.) (in.) (in.) (in.) (in.) line 4 screw 43 1 1.76 4 0.611 69.8 16 3.33 0 12.5 0 30 0 1 <1:10 1 1 6 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 2 1.75 4 0.609 69.5 16 3.33 3 1.76 4 0.612 69.9 16 3.33 4 1.84 4 0.638 72.9 16 3.33 5 1.99 4 0.664 75.8 16 3.39 6 1.82 4 0.634 72.4 16 3.33 0 1 <1:10 1 4 screw 0. 44 1 1.8 4 0.501 57.2 16 3.72 0 16.25 2 3 0 7 holes (0.5” 0 0 0 0 0 0 3 1.5 5 dia) 0. 2 1.58 4 0.522 59.7 16 3.41 7 1 5 3 1.8 4 0.501 57.2 16 3.72 4 1.91 4 0.526 60.1 16 3.74 5 1.85 4 0.513 58.6 16 3.73 6 1.85 4 0.513 58.6 16 3.72 4 screw 45 1 1.87 4 0.549 62.7 16 3.63 0 13.25 0 3.5 2 1 <1:10 1 0 14 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 2 1.88 4 0.55 62.8 16 3.63 3 1.87 4 0.548 62.6 16 3.63 4 1.9 4 0.571 65.2 16 3.57 5 1.82 4 0.534 61 16 3.63 6 1.9 4 0.551 62.9 16 3.64 4 screw 0. 46 1 2.45 2 0.653 74.7 16 3.8 0 8 0 72 0 1 <1:10 1 0 9 holes (0.5” 0 0 0 6 0.25 0.25 6 0.25 25 dia) 2 2.46 2 0.655 74.9 16 3.8 3 2.45 2 0.654 74.8 16 3.8 4 2.34 3 0.627 71.6 16 3.79 5 2.35 3 0.628 71.7 16 3.8 6 2.42 2 0.636 72.7 16 3.83 4 screw 47 1 2.58 2 0.695 79.4 16 3.78 0 5.25 0 12 0 1 <1:10 1 0 10 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 2 2.58 2 0.694 79.3 16 3.79 96 Table 6.4 (Cont’d) KNOTS NAIL HOLES (1/8 in.) DAMAGE Sampl Run SHAKE/ END SLOPE e E Gra Weight Length Freq. Wide Gra Wide Numbe SG Narrow Wide face CHECK SPLIT OF Grade Numbe [Mpsi] de [lbs] [ft] [Hz] face de Narrow face Wide face Wide face Wide face Edge r face Centerline (in.) (in.) GRAIN Narrow face (in.) r Edge face Center Edge Centerline (in.) (in.) (in.) (in.) (in.) line 3 2.62 1 0.706 80.7 16 3.78 4 2.69 1 0.727 83 16 3.78 5 2.68 1 0.726 82.9 16 3.77 6 2.68 1 0.724 82.7 16 3.78 4 screw 48 1 2.97 1 0.719 81.7 15.9 4.03 0 0 0 12 3 1 <1:10 1 4 4 holes (0.5” 8 0.5 0.5 0 0 0 0 0 0 dia) 2 2.98 1 0.718 81.6 15.9 4.04 3 2.98 1 0.718 81.6 15.9 4.04 4 2.87 1 0.695 79 15.9 4.03 5 2.86 1 0.695 79 15.9 4.02 6 2.88 1 0.695 79 15.9 4.03 4 screw 49 1 2.48 2 0.609 69.5 16 3.96 0 20.75 0 4 5 1 <1:10 1 1 4 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 2 2.48 2 0.608 69.4 16 3.96 3 2.49 2 0.611 69.8 16 3.96 4 2.42 2 0.591 67.6 16 3.97 5 2.42 2 0.592 67.7 16 3.97 6 2.41 2 0.596 68.1 16 3.94 4 screw 0.2 50 1 1.88 4 0.576 65.8 16 3.54 0 8.75 0 4 5 1 <1:10 1 2 6 holes (0.5” 18 0.25 0 0 0 0 0 0 5 dia) 2 1.88 4 0.576 65.8 16 3.55 3 1.89 4 0.578 66 16 3.54 4 1.78 4 0.545 62.2 16 3.54 5 1.79 4 0.545 62.2 16 3.56 6 1.79 4 0.547 62.4 16 3.55 0 1 <1:10 1 4 screw 0. 51 1 1.43 4 0.505 57.7 16 3.3 0 9.25 0 3 0 10 holes (0.5” 0 0 0 0 0 0 9 0.5 5 dia) 2 1.43 4 0.506 57.8 16 3.3 3 1.43 4 0.505 57.7 16 3.3 4 1.47 4 0.518 59.2 16 3.31 5 1.47 4 0.519 59.3 16 3.31 97 Table 6.4 (Cont’d) KNOTS NAIL HOLES (1/8 in.) DAMAGE Sampl Run SHAKE/ END SLOPE e E Gra Weight Length Freq. Wide Gra Wide Numbe SG Narrow Wide face CHECK SPLIT OF Grade Numbe [Mpsi] de [lbs] [ft] [Hz] face de Narrow face Wide face Wide face Wide face Edge r face Centerline (in.) (in.) GRAIN Narrow face (in.) r Edge face Center Edge Centerline (in.) (in.) (in.) (in.) (in.) line 6 1.47 4 0.518 59.2 16 3.31 0 7.3 4 screw 52 1 2.1 3 0.593 67.8 16 3.69 0 6 0 1 <1:10 1 0 14 holes (0.5” 64 1 1.5 0 0 0 0 0 0 dia) 2 2.1 4 0.593 67.8 16 3.69 3 2.09 4 0.591 67.6 16 3.69 4 2.34 3 0.665 75.9 16 3.68 5 2.35 3 0.666 76 16 3.69 6 2.34 3 0.664 75.8 16 3.68 4 screw 0. 53 1 1.74 4 0.541 61.6 15.9 3.54 0 0 0 8 5.5 1 <1:10 1 3 9 holes (0.5” 0 0 0 0 0 0 5 1.5 5 dia) 2 1.75 4 0.544 62 15.9 3.54 3 1.74 4 0.542 61.7 15.9 3.54 4 1.7 4 0.523 59.5 15.9 3.57 5 1.7 4 0.523 59.5 15.9 3.57 6 1.7 4 0.523 59.5 15.9 3.56 4 screw 0.2 0. 54 1 1.67 4 0.654 74.1 15.8 3.19 0 0 0 45 3 1 <1:10 1 4 16 holes (0.5” 1.5 0.5 0 0 0 14 0.5 5 5 dia) 2 1.68 4 0.657 74.3 15.8 3.19 3 1.67 4 0.654 74.1 15.8 3.19 4 1.65 4 0.646 73.1 15.8 3.19 5 1.66 4 0.648 73.4 15.8 3.2 6 1.65 4 0.646 73.1 15.8 3.19 4 screw 55 1 2.47 2 0.649 74.2 16 3.82 0 0 0 65 1.5 1 <1:10 1 2 9 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 2 2.46 2 0.649 74.2 16 3.82 3 2.46 2 0.649 74.2 16 3.82 4 2.62 1 0.698 79.8 16 3.8 5 2.61 1 0.697 79.7 16 3.8 6 2.62 1 0.698 79.8 16 3.8 98 Table 6.4 (Cont’d) KNOTS NAIL HOLES (1/8 in.) DAMAGE Sampl Run SHAKE/ END SLOPE e E Gra Weight Length Freq. Wide Gra Wide Numbe SG Narrow Wide face CHECK SPLIT OF Grade Numbe [Mpsi] de [lbs] [ft] [Hz] face de Narrow face Wide face Wide face Wide face Edge r face Centerline (in.) (in.) GRAIN Narrow face (in.) r Edge face Center Edge Centerline (in.) (in.) (in.) (in.) (in.) line 4 screw 56 1 2.42 2 0.663 75.7 16 3.75 0 1 0 17 5 1 <1:10 1 2 10 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 2 2.42 2 0.664 75.8 16 3.75 3 2.42 2 0.663 75.7 16 3.75 4 2.33 3 0.635 72.6 16 3.75 5 2.47 2 0.638 72.9 16 3.86 6 2.33 3 0.635 72.6 16 3.76 4 screw 0. 57 1 1.84 4 0.61 70.5 16 3.43 0 0 0 5 3 1 <1:10 1 1 6 holes (0.5” 0 0 0 0 0 0 42 0.25 5 dia) 0. 2 1.84 4 0.61 70.5 16 3.43 8 0.5 5 3 1.84 4 0.609 70.4 16 3.43 4 1.76 4 0.577 66.7 16 3.45 5 1.76 4 0.577 66.7 16 3.45 6 1.75 4 0.577 66.7 16 3.44 4 screw 0. 58 1 2.03 4 0.674 77 16 3.43 0 9.5 2.75 5 2.5 1 <1:10 1 0 7 holes (0.5” 0 0 0 0 0 0 1.5 0.5 5 dia) 2 2.03 4 0.672 76.7 16 3.43 3 2.03 4 0.674 77 16 3.43 4 1.93 4 0.634 72.4 16 3.45 5 1.92 4 0.634 72.4 16 3.44 6 1.92 4 0.635 72.5 16 3.43 4 screw 59 1 1.99 4 0.644 73.6 16 3.47 0 4.5 0 17 2.5 1 <1:10 1 0 7 holes (0.5” 0 0 0 2 0.5 0.5 0 0 0 dia) 2 1.98 4 0.644 73.6 16 3.47 3 1.99 4 0.644 73.6 16 3.47 4 1.94 4 0.629 71.8 16 3.47 5 1.95 4 0.631 72 16 3.47 6 1.95 4 0.63 71.9 16 3.47 4 screw 0. 60 1 2.27 3 0.578 66 16 3.92 0 8 0 70 4 1 <1:10 1 6 13 holes (0.5” 0 0 0 0 0 0 3 0.5 75 dia) 2 2.28 3 0.576 65.7 16 3.93 10 1 1 99 Table 6.4 (Cont’d) KNOTS NAIL HOLES (1/8 in.) DAMAGE Sampl Run SHAKE/ END SLOPE e E Gra Weight Length Freq. Wide Gra Wide Numbe SG Narrow Wide face CHECK SPLIT OF Grade Numbe [Mpsi] de [lbs] [ft] [Hz] face de Narrow face Wide face Wide face Wide face Edge r face Centerline (in.) (in.) GRAIN Narrow face (in.) r Edge face Center Edge Centerline (in.) (in.) (in.) (in.) (in.) line 3 2.28 3 0.578 66 16 3.93 4 2.35 3 0.605 69 16 3.9 5 2.35 3 0.605 69 16 3.9 6 2.36 3 0.607 69.2 16 3.9 0 1 <1:10 1 4 screw 61 1 2.47 2 0.69 78.1 15.8 3.81 0 4.25 0 84 3 8 holes (0.5” 0 0 0 3 1.5 0.25 0 0 0 dia) 2 2.46 2 0.688 77.9 15.8 3.81 3 2.46 2 0.688 77.9 15.8 3.81 4 2.33 3 0.652 73.8 15.8 3.8 5 2.33 3 0.652 73.8 15.8 3.81 6 2.36 3 0.656 74.3 15.8 3.82 4 screw 0. 62 1 1.75 4 0.499 57 16 3.7 0 13.2 0 1.5 0 1 <1:10 1 2 8 holes (0.5” 0 0 0 0 0 0 13.5 1.5 75 dia) 0. 3 1.75 4 0.498 56.9 16 3.7 19 0.75 25 0. 4 1.74 4 0.498 56.9 16 3.7 5 0.25 25 0. 5 1.8 4 0.514 58.7 16 3.7 4 0.3 5 6 1.8 4 0.513 58.6 16 3.7 4 screw 0. 63 1 1.62 4 0.583 66.4 16 3.31 0 11 0 0 10 1 <1:10 1 2 8 holes (0.5” 0 0 0 0 0 0 6 0.5 5 dia) 2 1.63 4 0.583 66.4 16 3.31 3 1.62 4 0.581 66.3 16 3.31 4 1.59 4 0.575 65.6 16 3.29 5 1.6 4 0.577 65.9 16 3.29 6 1.6 4 0.577 65.9 16 3.29 4 screw 65 1 1.58 4 0.65 74.3 16 3.08 0 19.25 0 0 0 1 <1:10 1 4 7 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 100 Table 6.4 (Cont’d) KNOTS NAIL HOLES (1/8 in.) DAMAGE Sampl Run SHAKE/ END SLOPE e E Gra Weight Length Freq. Wide Gra Wide Numbe SG Narrow Wide face CHECK SPLIT OF Grade Numbe [Mpsi] de [lbs] [ft] [Hz] face de Narrow face Wide face Wide face Wide face Edge r face Centerline (in.) (in.) GRAIN Narrow face (in.) r Edge face Center Edge Centerline (in.) (in.) (in.) (in.) (in.) line 2 1.58 4 0.649 74.2 16 3.08 3 1.58 4 0.649 74.2 16 3.08 4 1.47 4 0.604 69 16 3.08 5 1.47 4 0.603 68.9 16 3.08 6 1.47 4 0.602 68.8 16 3.08 4 screw 67 1 2.03 4 0.638 72.9 16 3.52 0 0.5 0 0 0 1 <1:10 1 0 4 holes (0.5” 0 0 0 0 0 0 0 0 0 dia) 2 2.03 4 0.637 72.7 16 3.53 3 2.03 4 0.638 72.9 16 3.52 4 2.04 4 0.637 72.7 16 3.54 5 2.04 4 0.636 72.6 16 3.54 6 2.03 4 0.636 72.6 16 3.53 101 APPENDIX E MOE values of salvaged samples from Metriguard 102 Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 1 2.18 3 0.548 10 8 2 2.16 3 0.548 10 8 3 2.17 3 0.548 10 8 1 4 2.16 3 0.541 9.8 8 5 2.15 3 0.539 9.8 8 6 2.15 3 0.539 9.8 8 1 2.13 3 0.535 9.7 8 2 2.14 3 0.534 9.7 8 3 2.14 3 0.534 9.7 8 2 4 2.17 3 0.542 9.8 8 5 2.18 3 0.542 9.8 8 6 2.18 3 0.542 9.8 8 1 1.77 4 0.511 9.3 8 2 1.77 4 0.51 9.3 8 3 1.78 4 0.511 9.3 8 3 4 1.87 4 0.532 9.7 8 5 1.86 4 0.53 9.6 8 6 1.87 4 0.53 9.6 8 1 2.16 3 0.573 10.4 8 2 2.16 3 0.573 10.4 8 3 2.16 3 0.573 10.4 8 4 4 2.09 4 0.558 10.1 8 5 2.09 4 0.558 10.1 8 6 2.08 4 0.56 10.2 8 1 2.2 3 0.6 10.9 8 2 2.19 3 0.601 10.9 8 3 2.21 3 0.601 10.9 8 5 4 2.07 4 0.56 10.2 8 5 2.07 4 0.558 10.1 8 6 2.07 4 0.558 10.1 8 1 2.2 3 0.557 10.1 8 2 2.21 3 0.558 10.1 8 3 2.21 3 0.557 10.1 8 6 4 2.13 3 0.533 9.7 8 5 2.14 3 0.534 9.7 8 6 2.13 3 0.533 9.7 8 Table 6.5 MOE values of salvaged samples from Metriguard 103 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 1 2.62 1 0.679 12.3 8 2 2.61 1 0.679 12.3 8 3 2.62 1 0.678 12.3 8 7 4 2.68 1 0.697 12.7 8 5 2.67 1 0.697 12.7 8 6 2.67 1 0.697 12.7 8 1 2.71 1 0.707 12.8 8 2 2.7 1 0.707 12.8 8 3 2.69 1 0.707 12.8 8 8 4 2.7 1 0.693 12.6 8 5 2.67 1 0.691 12.6 8 6 2.69 1 0.691 12.6 8 1 2.96 1 0.7 12.7 8 2 2.96 1 0.702 12.8 8 3 2.97 1 0.702 12.8 8 9 4 2.98 1 0.697 12.7 8 5 2.99 1 0.695 12.6 8 6 2.99 1 0.697 12.7 8 1 2.41 2 0.69 12.5 8 2 2.43 2 0.691 12.6 8 3 2.42 2 0.691 12.6 8 10 4 2.45 2 0.694 12.6 8 5 2.45 2 0.694 12.6 8 6 2.46 2 0.695 12.6 8 1 2.41 2 0.747 13.6 8 2 2.41 2 0.746 13.6 8 3 2.4 2 0.746 13.6 8 11 4 2.27 3 0.707 12.8 8 5 2.28 3 0.707 12.8 8 6 2.29 3 0.707 12.8 8 1 2.88 1 0.811 14.7 8 2 2.89 1 0.812 14.8 8 3 2.89 1 0.812 14.8 8 12 4 2.69 1 0.761 13.8 8 5 2.68 1 0.759 13.8 8 6 2.7 1 0.761 13.8 8 1 2.18 3 0.613 11.1 8 13 2 2.2 3 0.614 11.2 8 104 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.2 3 0.614 11.2 8 4 2.25 3 0.626 11.4 8 5 2.25 3 0.624 11.3 8 6 2.23 3 0.624 11.3 8 1 2.35 3 0.639 11.6 8 2 2.34 3 0.639 11.6 8 3 2.35 3 0.641 11.6 8 14 4 2.36 3 0.638 11.6 8 5 2.38 3 0.639 11.6 8 6 2.38 3 0.641 11.6 8 1 2.51 2 0.628 11.4 8 2 2.51 2 0.628 11.4 8 3 2.51 2 0.628 11.4 8 15 4 2.41 2 0.603 11 8 5 2.4 2 0.601 10.9 8 6 2.39 3 0.601 10.9 8 1 1.45 4 0.629 11.4 8 2 1.44 4 0.629 11.4 8 3 1.44 4 0.629 11.4 8 16 4 1.44 4 0.627 11.4 8 5 1.44 4 0.627 11.4 8 6 1.44 4 0.627 11.4 8 1 2.58 2 0.627 11.4 8 2 2.6 2 0.628 11.4 8 3 2.58 2 0.628 11.4 8 17 4 2.66 1 0.642 11.7 8 5 2.65 1 0.639 11.6 8 6 2.65 1 0.641 11.6 8 1 1.81 4 0.48 8.7 8 2 1.81 4 0.48 8.7 8 3 1.82 4 0.48 8.7 8 18 4 1.92 4 0.504 9.2 8 5 1.92 4 0.504 9.2 8 6 1.92 4 0.502 9.1 8 1 1.87 4 0.511 9.3 8 2 1.87 4 0.51 9.3 8 19 3 1.87 4 0.51 9.3 8 4 1.82 4 0.495 9 8 5 1.81 4 0.495 9 8 105 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.82 4 0.495 9 8 1 1.65 4 0.495 9 8 2 1.64 4 0.494 9 8 3 1.65 4 0.495 9 8 20 4 1.64 4 0.487 8.9 8 5 1.63 4 0.487 8.9 8 6 1.64 4 0.487 8.9 8 1 2.22 3 0.527 9.6 8 2 2.21 3 0.528 9.6 8 3 2.22 3 0.528 9.6 8 21 4 2.24 3 0.535 9.7 8 5 2.26 3 0.535 9.7 8 6 2.25 3 0.534 9.7 8 1 2.01 4 0.51 9.3 8 2 2.01 4 0.51 9.3 8 3 2.01 4 0.51 9.3 8 22 4 2.05 4 0.52 9.5 8 5 2.06 4 0.52 9.5 8 6 2.04 4 0.52 9.5 8 1 2.06 4 0.533 9.7 8 2 2.06 4 0.533 9.7 8 3 2.06 4 0.533 9.7 8 23 4 2.13 3 0.549 10 8 5 2.14 3 0.551 10 8 6 2.13 3 0.551 10 8 1 2.19 3 0.559 10.1 8 2 2.19 3 0.559 10.1 8 3 2.19 3 0.559 10.1 8 24 4 2.13 3 0.548 9.9 8 5 2.13 3 0.546 9.9 8 6 2.13 3 0.546 9.9 8 1 2.29 3 0.565 10.3 8 2 2.29 3 0.565 10.3 8 3 2.29 3 0.565 10.3 8 25 4 2.32 3 0.575 10.4 8 5 2.32 3 0.574 10.4 8 6 2.32 3 0.574 10.4 8 1 2.33 3 0.546 9.9 8 26 2 2.33 3 0.545 9.9 8 106 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.34 3 0.545 9.9 8 4 2.32 3 0.545 9.9 8 5 2.32 3 0.546 9.9 8 6 2.33 3 0.546 9.9 8 1 2.28 3 0.572 10.4 8 2 2.29 3 0.573 10.4 8 3 2.29 3 0.573 10.4 8 27 4 2.3 3 0.574 10.4 8 5 2.3 3 0.574 10.4 8 6 2.3 3 0.573 10.4 8 1 2.34 3 0.613 11.1 8 2 2.34 3 0.615 11.2 8 3 2.35 3 0.615 11.2 8 28 4 2.37 3 0.69 12.5 8 5 2.36 3 0.616 11.2 8 6 2.36 3 0.616 11.2 8 1 1.93 4 0.61 11.1 8 2 1.93 4 0.61 11.1 8 3 1.94 4 0.611 11.1 8 29 4 1.91 4 0.608 11 8 5 1.94 4 0.611 11.1 8 6 1.93 4 0.61 11.1 8 1 1.97 4 0.589 10.7 8 2 1.97 4 0.59 10.7 8 3 1.98 4 0.59 10.7 8 30 4 2.06 4 0.609 11.1 8 5 2.06 4 0.608 11 8 6 2.05 4 0.608 11 8 1 1.77 4 0.625 11.4 8 2 1.77 4 0.624 11.3 8 3 1.77 4 0.625 11.4 8 31 4 1.87 4 0.662 12 8 5 1.87 4 0.663 12.1 8 6 1.87 4 0.663 12.1 8 1 1.96 4 0.579 10.5 8 2 1.97 4 0.581 10.6 8 32 3 1.96 4 0.58 10.5 8 4 1.96 4 0.58 10.5 8 5 1.97 4 0.582 10.6 8 107 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.96 4 0.581 10.6 8 1 2.01 4 0.546 9.8 7.9 2 2.02 4 0.545 9.8 7.9 3 2.02 4 0.545 9.8 7.9 33 4 2.01 4 0.545 9.8 7.9 5 2.02 4 0.545 9.8 7.9 6 2.02 4 0.545 9.8 7.9 1 1.75 4 0.593 10.8 8 2 1.75 4 0.593 10.8 8 3 1.75 4 0.593 10.8 8 34 4 1.78 4 0.601 10.9 8 5 1.78 4 0.6 10.9 8 6 1.79 4 0.601 10.9 8 1 2.12 3 0.55 10 8 2 2.13 3 0.551 10 8 3 2.13 3 0.55 10 8 35 4 2.16 3 0.562 10.2 8 5 2.17 3 0.563 10.2 8 6 2.17 3 0.563 10.2 8 1 1.58 4 0.556 10.1 8 2 1.57 4 0.556 10.1 8 3 1.57 4 0.556 10.1 8 36 4 1.47 4 0.516 9.3 8 5 1.48 4 0.517 9.4 8 6 1.47 4 0.517 9.4 8 1 1.45 4 0.531 9.6 8 2 1.44 4 0.53 9.6 8 3 1.46 4 0.531 9.6 8 37 4 1.45 4 0.532 9.7 8 5 1.45 4 0.531 9.6 8 6 1.46 4 0.531 9.6 8 1 1.65 4 0.531 9.6 8 2 1.65 4 0.531 9.6 8 3 1.65 4 0.531 9.6 8 38 4 1.63 4 0.521 9.5 8 5 1.63 4 0.521 9.5 8 6 1.62 4 0.521 9.5 8 1 1.19 4 0.492 8.9 8 39 2 1.19 4 0.492 8.9 8 108 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 1.19 4 0.492 8.9 8 4 1.15 4 0.478 8.7 8 5 1.15 4 0.477 8.7 8 6 1.15 4 0.477 8.7 8 1 1.29 4 0.565 10.3 8 2 1.28 4 0.565 10.3 8 3 1.29 4 0.565 10.3 8 40 4 1.26 4 0.551 10 8 5 1.27 4 0.553 10.1 8 6 1.26 4 0.551 10 8 1 1.73 4 0.546 9.9 8 2 1.74 4 0.548 10 8 3 1.74 4 0.546 9.9 8 41 4 1.58 4 0.502 9.1 8 5 1.58 4 0.501 9.1 8 6 1.57 4 0.501 9.1 8 1 1.8 4 0.538 9.8 8 2 1.8 4 0.538 9.8 8 3 1.81 4 0.538 9.8 8 42 4 1.78 4 0.528 9.6 8 5 1.77 4 0.528 9.6 8 6 1.8 4 0.53 9.6 8 1 2.04 4 0.553 10 8 2 2.04 4 0.552 10 8 3 2.04 4 0.552 10 8 43 4 2.03 4 0.551 10 8 5 2.03 4 0.551 10 8 6 2.04 4 0.552 10 8 1 2.27 3 0.563 10.2 8 2 2.28 3 0.563 10.2 8 3 2.27 3 0.563 10.2 8 44 4 2.27 3 0.565 10.2 8 5 2.27 3 0.563 10.2 8 6 2.26 3 0.563 10.2 8 1 2.5 2 0.576 10.3 7.9 2 2.52 2 0.576 10.3 7.9 45 3 2.52 2 0.574 10.3 7.9 4 2.38 3 0.551 9.8 7.9 5 2.4 2 0.552 9.9 7.9 109 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.39 3 0.552 9.9 7.9 1 2.4 3 0.569 10.2 7.9 2 2.42 2 0.57 10.2 7.9 3 2.4 3 0.57 10.2 7.9 46 4 2.33 3 0.56 10 7.9 5 2.33 3 0.56 10 7.9 6 2.31 3 0.559 10 7.9 1 2.04 4 0.56 10 7.9 2 2.04 4 0.56 10 7.9 3 2.04 4 0.56 10 7.9 47 4 2.09 4 0.55 9.8 7.9 5 2.1 3 0.549 9.8 7.9 6 2.11 3 0.549 9.8 7.9 1 2.64 1 0.64 11.6 8 2 2.68 1 0.643 11.7 8 3 2.67 1 0.641 11.7 8 48 4 2.69 1 0.648 11.8 8 5 2.69 1 0.648 11.8 8 6 2.69 1 0.648 11.8 8 1 2.48 2 0.666 12.1 8 2 2.48 2 0.666 12.1 8 3 2.47 2 0.666 12.1 8 49 4 2.36 3 0.631 11.5 8 5 2.37 3 0.632 11.5 8 6 2.37 3 0.632 11.5 8 1 2.75 1 0.655 11.9 8 2 2.72 1 0.653 11.9 8 3 2.74 1 0.655 11.9 8 50 4 2.75 1 0.653 11.9 8 5 2.74 1 0.652 11.9 8 6 2.75 1 0.652 11.9 8 1 2.81 1 0.6 10.9 8 2 2.81 1 0.598 10.9 8 3 2.79 1 0.6 10.9 8 51 4 2.84 1 0.612 11.1 8 5 2.85 1 0.612 11.1 8 6 2.85 1 0.612 11.1 8 1 2.62 1 0.587 10.7 8 52 2 2.62 1 0.587 10.7 8 110 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.6 1 0.586 10.7 8 4 2.67 1 0.607 11 8 5 2.68 1 0.607 11 8 6 2.68 1 0.607 11 8 1 2.74 1 0.616 11.2 8 2 2.75 1 0.616 11.2 8 3 2.76 1 0.619 11.3 8 53 4 2.82 1 0.631 11.5 8 5 2.8 1 0.629 11.4 8 6 2.81 1 0.63 11.5 8 1 1.88 4 0.516 9.4 8 2 1.88 4 0.516 9.4 8 3 1.87 4 0.516 9.4 8 54 4 1.89 4 0.522 9.5 8 5 1.91 4 0.522 9.5 8 6 1.91 4 0.521 9.5 8 1 1.73 4 0.52 9.4 8 2 1.73 4 0.521 9.5 8 3 1.73 4 0.521 9.5 8 55 4 1.73 4 0.521 9.5 8 5 1.73 4 0.521 9.5 8 6 1.72 4 0.52 9.4 8 1 1.82 4 0.532 9.7 8 2 1.82 4 0.532 9.7 8 3 1.8 4 0.531 9.6 8 56 4 1.81 4 0.531 9.6 8 5 1.82 4 0.532 9.7 8 6 1.82 4 0.532 9.7 8 1 1.88 4 0.511 9.1 7.9 2 1.88 4 0.511 9.1 7.9 3 1.89 4 0.512 9.2 7.9 57 4 1.86 4 0.51 9.1 7.9 5 1.87 4 0.511 9.1 7.9 6 1.87 4 0.511 9.1 7.9 1 1.79 4 0.52 9.3 7.9 2 1.8 4 0.52 9.3 7.9 58 3 1.8 4 0.52 9.3 7.9 4 1.75 4 0.568 10.1 7.9 5 1.79 4 0.52 9.3 7.9 111 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.8 4 0.52 9.3 7.9 1 1.71 4 0.538 9.6 7.9 2 1.71 4 0.538 9.6 7.9 3 1.71 4 0.539 9.6 7.9 59 4 1.79 4 0.541 9.7 7.9 5 1.8 4 0.543 9.7 7.9 6 1.81 4 0.543 9.7 7.9 1 1.22 4 0.539 9.8 8 2 1.22 4 0.537 9.8 8 3 1.22 4 0.537 9.8 8 60 4 1.22 4 0.539 9.8 8 5 1.22 4 0.537 9.8 8 6 1.22 4 0.537 9.8 8 1 1.42 4 0.541 9.8 8 2 1.42 4 0.541 9.8 8 3 1.42 4 0.542 9.8 8 61 4 1.41 4 0.541 9.8 8 5 1.42 4 0.542 9.8 8 6 1.41 4 0.541 9.8 8 1 1.44 4 0.53 9.6 8 2 1.44 4 0.53 9.6 8 3 1.44 4 0.532 9.7 8 62 4 1.45 4 0.533 9.7 8 5 1.45 4 0.533 9.7 8 6 1.45 4 0.533 9.7 8 1 1.19 4 0.511 9.3 8 2 1.19 4 0.513 9.3 8 3 1.2 4 0.511 9.3 8 63 4 1.18 4 0.501 9.1 8 5 1.18 4 0.5 9.1 8 6 1.17 4 0.5 9.1 8 1 1.66 4 0.523 9.5 8 2 1.65 4 0.521 9.5 8 3 1.66 4 0.523 9.5 8 64 4 1.71 4 0.529 9.6 8 5 1.71 4 0.529 9.6 8 6 1.71 4 0.529 9.6 8 1 2.23 3 0.548 10 8 65 2 2.22 3 0.549 10 8 112 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.22 3 0.548 10 8 4 2.11 3 0.515 9.4 8 5 2.11 3 0.518 9.4 8 6 2.11 3 0.515 9.4 8 1 2.58 2 0.579 10.5 8 2 2.6 2 0.579 10.5 8 3 2.58 2 0.579 10.5 8 66 4 2.52 2 0.571 10.4 8 5 2.51 2 0.571 10.4 8 6 2.53 2 0.572 10.4 8 1 2.25 3 0.56 10.2 8 2 2.25 3 0.558 10.1 8 3 2.25 3 0.558 10.1 8 67 4 2.25 3 0.552 10 8 5 2.24 3 0.551 10 8 6 2.25 3 0.552 10 8 1 1.64 4 0.53 9.6 8 2 1.65 4 0.532 9.7 8 3 1.64 4 0.53 9.6 8 68 4 1.58 4 0.513 9.3 8 5 1.59 4 0.514 9.3 8 6 1.59 4 0.514 9.3 8 1 1.49 4 0.534 9.7 8 2 1.5 4 0.534 9.7 8 3 1.5 4 0.534 9.7 8 69 4 1.52 4 0.537 9.8 8 5 1.53 4 0.538 9.8 8 6 1.52 4 0.538 9.8 8 1 1.43 4 0.483 8.8 8 2 1.42 4 0.483 8.8 8 3 1.43 4 0.485 8.8 8 70 4 1.45 4 0.485 8.8 8 5 1.44 4 0.485 8.8 8 6 1.45 4 0.483 8.8 8 1 2.49 2 0.639 11.6 8 2 2.48 2 0.639 11.6 8 71 3 2.5 2 0.641 11.6 8 4 2.39 3 0.614 11.2 8 5 2.38 3 0.614 11.2 8 113 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.38 3 0.613 11.1 8 1 2.11 3 0.593 10.8 8 2 2.13 3 0.595 10.8 8 3 2.12 3 0.595 10.8 8 72 4 2.11 3 0.59 10.7 8 5 2.12 3 0.591 10.7 8 6 2.12 3 0.591 10.7 8 1 2.19 3 0.593 10.8 8 2 2.21 3 0.593 10.8 8 3 2.2 3 0.591 10.7 8 73 4 2.12 3 0.57 10.4 8 5 2.11 3 0.57 10.4 8 6 2.13 3 0.57 10.4 8 4 2.11 3 0.59 10.7 8 5 2.12 3 0.591 10.7 8 6 2.12 3 0.591 10.7 8 74 1 2.19 3 0.593 10.8 8 2 2.21 3 0.593 10.8 8 3 2.2 3 0.591 10.7 8 1 2.7 1 0.647 11.8 8 2 2.69 1 0.646 11.7 8 3 2.71 1 0.646 11.7 8 75 4 2.83 1 0.679 12.3 8 5 2.82 1 0.679 12.3 8 6 2.81 1 0.678 12.3 8 2 1.82 4 0.614 11.2 8 3 1.8 4 0.614 11.2 8 4 1.83 4 0.659 12 8 76 5 1.94 4 0.66 12 8 6 1.93 4 0.657 11.9 8 1 2.24 3 0.684 12.4 8 2 2.24 3 0.684 12.4 8 3 2.24 3 0.683 12.4 8 4 2.2 3 0.676 12.3 8 77 5 2.21 3 0.676 12.3 8 6 2.19 3 0.675 12.3 8 1 3.18 1 0.726 13.2 8 2 3.18 1 0.726 13.2 8 78 3 3.2 1 0.727 13.2 8 114 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 4 3.13 1 0.713 13 8 5 3.13 1 0.713 13 8 6 3.14 1 0.712 12.9 8 1 2.7 1 0.695 12.6 8 2 2.71 1 0.697 12.7 8 3 2.71 1 0.697 12.7 8 4 2.79 1 0.716 13 8 79 5 2.78 1 0.716 13 8 6 2.79 1 0.714 13 8 1 2.49 2 0.643 11.7 8 2 2.48 2 0.643 11.7 8 3 2.49 2 0.642 11.7 8 4 2.52 2 0.659 12 8 80 5 2.53 2 0.657 11.9 8 6 2.52 2 0.657 11.9 8 1 2.72 1 0.622 11.3 8 2 2.74 1 0.623 11.3 8 3 2.74 1 0.623 11.3 8 4 2.74 1 0.624 11.3 8 81 5 2.74 1 0.624 11.3 8 6 2.76 1 0.627 11.4 8 1 3.03 1 0.67 12.2 8 2 3.03 1 0.669 12.2 8 3 3.02 1 0.669 12.2 8 4 3.06 1 0.676 12.3 8 82 5 3.06 1 0.678 12.3 8 6 3.06 1 0.676 12.3 8 1 2.96 1 0.652 11.9 8 2 2.97 1 0.653 11.9 8 3 2.95 1 0.653 11.9 8 4 3.04 1 0.679 12.3 8 83 5 3.06 1 0.679 12.3 8 6 3.06 1 0.679 12.3 8 1 2.75 1 0.611 11.1 8 2 2.73 1 0.611 11.1 8 3 2.73 1 0.611 11.1 8 84 4 2.75 1 0.611 11.1 8 5 2.75 1 0.611 11.1 8 6 2.75 1 0.61 11.1 8 115 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 1 2.61 1 0.63 11.4 8 2 2.61 1 0.63 11.4 8 3 2.59 2 0.63 11.4 8 4 2.6 1 0.629 11.4 8 85 5 2.61 1 0.63 11.4 8 6 2.62 1 0.63 11.4 8 1 3.15 1 0.669 12.2 8 2 3.16 1 0.67 12.2 8 3 3.15 1 0.67 12.2 8 4 3.19 1 0.75 13.6 8 86 5 3.15 1 0.669 12.2 8 6 3.16 1 0.67 12.2 8 1 2.78 1 0.603 11 8 2 2.8 1 0.601 10.9 8 3 2.83 1 0.601 10.9 8 4 2.66 1 0.575 10.4 8 87 5 2.64 1 0.573 10.4 8 6 2.65 1 0.573 10.4 8 1 2.47 2 0.567 10.3 8 2 2.47 2 0.567 10.3 8 3 2.45 2 0.567 10.3 8 4 2.38 3 0.551 10 8 88 5 2.38 3 0.551 10 8 6 2.38 3 0.549 10 8 1 2.01 4 0.577 10.5 8 2 2 4 0.576 10.5 8 3 2.01 4 0.576 10.5 8 4 1.99 4 0.57 10.4 8 89 5 1.98 4 0.568 10.3 8 6 1.98 4 0.568 10.3 8 1 2.01 4 0.518 9.4 8 2 2.01 4 0.518 9.4 8 3 2.02 4 0.518 9.4 8 4 1.92 4 0.504 9.2 8 90 5 1.92 4 0.504 9.2 8 6 1.92 4 0.504 9.2 8 1 1.93 4 0.529 9.6 8 2 1.94 4 0.53 9.6 8 91 3 1.94 4 0.53 9.6 8 116 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 4 1.91 4 0.518 9.4 8 5 1.91 4 0.518 9.4 8 6 1.9 4 0.518 9.4 8 1 2.12 3 0.558 10.1 8 2 2.12 3 0.558 10.1 8 3 2.12 3 0.558 10.1 8 4 2.08 4 0.549 10 8 92 5 2.08 4 0.549 10 8 6 2.09 4 0.549 10 8 1 2.15 3 0.557 10.1 8 2 2.16 3 0.558 10.1 8 3 2.15 3 0.558 10.1 8 4 2.08 4 0.537 9.8 8 93 5 2.07 4 0.537 9.8 8 6 2.08 4 0.538 9.8 8 1 1.22 4 0.506 9.2 8 2 1.23 4 0.506 9.2 8 3 1.22 4 0.506 9.2 8 4 1.24 4 0.514 9.3 8 94 5 1.24 4 0.513 9.3 8 6 1.24 4 0.513 9.3 8 1 1.2 4 0.542 9.8 8 2 1.2 4 0.539 9.8 8 3 1.2 4 0.541 9.8 8 4 1.22 4 0.548 10 8 95 5 1.21 4 0.547 9.9 8 6 1.21 4 0.547 9.9 8 1 1.25 4 0.505 9.2 8 2 1.25 4 0.505 9.2 8 3 1.24 4 0.504 9.2 8 4 1.29 4 0.52 9.5 8 96 5 1.29 4 0.519 9.4 8 6 1.29 4 0.519 9.4 8 1 1.82 4 0.481 8.7 8 2 1.82 4 0.481 8.7 8 3 1.82 4 0.481 8.7 8 97 4 1.87 4 0.496 9 8 5 1.87 4 0.496 9 8 6 1.86 4 0.496 9 8 117 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 1 1.72 4 0.514 9.3 8 2 1.72 4 0.514 9.3 8 3 1.71 4 0.514 9.3 8 4 1.79 4 0.519 9.4 8 98 5 1.78 4 0.519 9.4 8 6 1.79 4 0.519 9.4 8 1 1.97 4 0.513 9.3 8 2 1.98 4 0.513 9.3 8 3 1.97 4 0.513 9.3 8 4 1.97 4 0.519 9.4 8 99 5 1.97 4 0.519 9.4 8 6 1.97 4 0.519 9.4 8 1 2.27 3 0.575 10.4 8 2 2.29 3 0.575 10.4 8 3 2.29 3 0.575 10.4 8 4 2.37 3 0.579 10.5 8 100 5 2.36 3 0.579 10.5 8 6 2.35 3 0.579 10.5 8 1 2.36 3 0.595 10.8 8 2 2.36 3 0.594 10.8 8 3 2.36 3 0.595 10.8 8 4 2.39 3 0.603 11 8 101 5 2.4 3 0.604 11 8 6 2.4 3 0.604 11 8 1 2.43 2 0.59 10.7 8 2 2.44 2 0.593 10.8 8 3 2.41 2 0.591 10.7 8 4 2.44 2 0.591 10.7 8 102 5 2.44 2 0.591 10.7 8 6 2.43 2 0.59 10.7 8 1 1.96 4 0.598 10.9 8 2 1.95 4 0.598 10.9 8 3 1.95 4 0.596 10.8 8 4 2 4 0.596 10.8 8 103 5 2 4 0.596 10.8 8 6 1.99 4 0.596 10.8 8 1 1.83 4 0.595 10.8 8 2 1.83 4 0.594 10.8 8 104 3 1.84 4 0.595 10.8 8 118 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 4 1.84 4 0.595 10.8 8 5 1.84 4 0.595 10.8 8 6 1.85 4 0.594 10.8 8 1 1.94 4 0.591 10.7 8 2 1.95 4 0.591 10.7 8 3 1.94 4 0.591 10.7 8 4 2.74 1 0.609 11.1 8 105 5 1.96 4 0.586 10.7 8 6 1.95 4 0.586 10.7 8 7 1.97 4 0.585 10.6 8 1 2.21 3 0.562 10.2 8 2 2.2 3 0.562 10.2 8 3 2.21 3 0.563 10.2 8 106 4 2.31 3 0.59 10.7 8 5 2.29 3 0.589 10.7 8 6 2.32 3 0.59 10.7 8 1 2.39 3 0.601 10.9 8 2 2.4 2 0.603 11 8 3 2.4 3 0.601 10.9 8 107 4 2.53 2 0.636 11.6 8 5 2.51 2 0.636 11.6 8 6 2.53 2 0.634 11.5 8 1 2.39 3 0.568 10.3 8 2 2.39 3 0.568 10.3 8 3 2.39 3 0.568 10.3 8 108 4 2.44 2 0.585 10.6 8 5 2.46 2 0.585 10.6 8 6 2.46 2 0.585 10.6 8 1 2.5 2 0.535 9.7 8 2 2.49 2 0.534 9.7 8 3 2.5 2 0.534 9.7 8 109 4 2.5 2 0.535 9.7 8 5 2.5 2 0.535 9.7 8 6 2.5 2 0.535 9.7 8 1 2.44 2 0.561 10.2 8 2 2.44 2 0.561 10.2 8 110 3 2.46 2 0.562 10.2 8 4 2.48 2 0.562 10.2 8 5 2.49 2 0.563 10.2 8 119 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.48 2 0.562 10.2 8 1 2.06 4 0.532 9.7 8 2 2.06 4 0.529 9.6 8 3 2.07 4 0.53 9.6 8 111 4 2.07 4 0.538 9.8 8 5 2.1 4 0.541 9.8 8 6 2.1 3 0.541 9.8 8 1 1.93 4 0.599 10.9 8 2 1.93 4 0.598 10.9 8 3 1.93 4 0.598 10.9 8 112 4 1.94 4 0.596 10.8 8 5 1.95 4 0.596 10.8 8 6 1.94 4 0.595 10.8 8 1 1.74 4 0.601 10.9 8 2 1.74 4 0.601 10.9 8 3 1.74 4 0.599 10.8 8 113 4 1.68 4 0.635 11.5 8 5 1.74 4 0.599 10.8 8 6 1.74 4 0.599 10.8 8 1 1.76 4 0.601 10.9 8 2 1.76 4 0.601 10.9 8 3 1.77 4 0.602 10.9 8 114 4 1.7 4 0.606 11 8 5 1.7 4 0.607 11 8 6 1.71 4 0.608 11 8 1 2.58 2 0.608 11.1 8 2 2.58 2 0.607 11 8 3 2.58 2 0.607 11 8 115 4 2.51 2 0.613 11.2 8 5 2.51 2 0.613 11.2 8 6 2.49 2 0.613 11.2 8 1 2.44 2 0.601 10.9 8 2 2.43 2 0.601 10.9 8 3 2.44 2 0.601 10.9 8 116 4 2.38 3 0.601 10.9 8 5 2.39 3 0.601 10.9 8 6 2.37 3 0.601 10.9 8 1 2.43 2 0.596 10.7 7.9 117 2 2.44 2 0.595 10.7 7.9 120 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.42 2 0.594 10.6 7.9 4 2.43 2 0.595 10.7 7.9 5 2.42 2 0.594 10.6 7.9 6 2.43 2 0.594 10.6 7.9 1 2.11 3 0.631 11.5 8 2 2.11 3 0.631 11.5 8 3 2.12 3 0.632 11.5 8 118 4 1.98 4 0.593 10.8 8 5 2 4 0.595 10.8 8 6 2 4 0.595 10.8 8 1 1.61 4 0.618 11.2 8 2 1.61 4 0.618 11.2 8 3 1.61 4 0.618 11.2 8 119 4 1.51 4 0.579 10.5 8 5 1.51 4 0.579 10.5 8 6 1.5 4 0.577 10.5 8 1 2.43 2 0.637 11.6 8 2 2.43 2 0.637 11.6 8 3 2.44 2 0.639 11.7 8 120 4 2.38 3 0.629 11.5 8 5 2.37 3 0.629 11.5 8 6 2.38 3 0.629 11.5 8 1 1.54 4 0.648 11.8 8 2 1.53 4 0.645 11.7 8 3 1.53 4 0.646 11.7 8 121 4 1.53 4 0.645 11.7 8 5 1.54 4 0.645 11.7 8 6 1.54 4 0.645 11.7 8 1 1.71 4 0.61 11.1 8 2 1.71 4 0.611 11.1 8 3 1.71 4 0.611 11.1 8 122 4 1.71 4 0.646 11.7 8 5 1.77 4 0.645 11.7 8 6 1.77 4 0.646 11.7 8 1 2.44 2 0.675 12.3 8 2 2.44 2 0.675 12.3 8 123 3 2.45 2 0.675 12.3 8 4 2.47 2 0.68 12.4 8 5 2.46 2 0.68 12.4 8 121 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.46 2 0.68 12.4 8 1 2.35 3 0.521 9.5 8 2 2.35 3 0.521 9.5 8 3 2.34 3 0.521 9.5 8 124 4 2.36 3 0.524 9.5 8 5 2.36 3 0.525 9.5 8 6 2.35 3 0.525 9.5 8 1 2.29 3 0.567 10.3 8 2 2.3 3 0.566 10.3 8 3 2.29 3 0.566 10.3 8 125 4 2.28 3 0.563 10.2 8 5 2.27 3 0.562 10.2 8 6 2.27 3 0.562 10.2 8 1 1.66 4 0.521 9.5 8 2 1.67 4 0.52 9.5 8 3 1.67 4 0.521 9.5 8 126 4 1.71 4 0.535 9.7 8 5 1.71 4 0.534 9.7 8 6 1.71 4 0.535 9.7 8 1 2.2 3 0.594 10.8 8 2 2.2 3 0.593 10.8 8 3 2.2 3 0.593 10.8 8 127 4 2.13 3 0.576 10.5 8 5 2.13 3 0.577 10.5 8 6 2.14 3 0.577 10.5 8 1 1.83 4 0.613 11.1 8 2 1.83 4 0.613 11.1 8 3 1.83 4 0.613 11.1 8 128 4 1.82 4 0.605 11 8 5 1.81 4 0.606 11 8 6 1.82 4 0.605 11 8 1 1.54 4 0.553 10.1 8 2 1.54 4 0.553 10.1 8 3 1.54 4 0.554 10.1 8 129 4 1.59 4 0.573 10.4 8 5 1.59 4 0.572 10.4 8 6 1.6 4 0.572 10.4 8 1 2.4 2 0.594 10.8 8 130 2 2.4 2 0.594 10.8 8 122 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.41 2 0.595 10.8 8 4 2.41 2 0.598 10.9 8 5 2.41 2 0.596 10.8 8 6 2.42 2 0.598 10.9 8 1 2.35 3 0.648 11.8 8 2 2.34 3 0.646 11.7 8 3 2.36 3 0.647 11.8 8 131 4 2.34 3 0.646 11.7 8 5 2.35 3 0.647 11.8 8 6 2.34 3 0.647 11.8 8 1 2.16 3 0.646 11.7 8 2 2.16 3 0.645 11.7 8 3 2.16 3 0.646 11.7 8 132 4 2.13 3 0.634 11.5 8 5 2.14 3 0.633 11.5 8 6 2.14 3 0.633 11.5 8 1 2.52 2 0.646 11.7 8 2 2.74 1 0.645 11.7 8 3 2.64 1 0.645 11.7 8 133 4 2.81 1 0.674 12.2 8 5 2.8 1 0.674 12.2 8 6 2.8 1 0.672 12.2 8 1 2.15 3 0.673 12.2 8 2 2.13 3 0.672 12.2 8 3 2.16 3 0.673 12.2 8 134 4 2.2 3 0.672 12.2 8 5 2.14 3 0.678 12.3 8 6 2.14 3 0.677 12.3 8 1 1.56 4 0.653 11.9 8 2 1.56 4 0.652 11.9 8 3 1.56 4 0.652 11.9 8 135 4 1.52 4 0.636 11.6 8 5 1.52 4 0.634 11.5 8 6 1.53 4 0.634 11.5 8 1 2.49 2 0.596 10.8 8 2 2.48 2 0.598 10.9 8 136 3 2.49 2 0.596 10.8 8 4 2.47 2 0.591 10.7 8 5 2.48 2 0.593 10.8 8 123 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.46 2 0.591 10.7 8 1 2.3 3 0.605 11 8 2 2.3 3 0.605 11 8 3 2.3 3 0.606 11 8 137 4 2.26 3 0.6 10.9 8 5 2.26 3 0.598 10.9 8 6 2.25 3 0.599 10.9 8 1 1.77 4 0.628 11.4 8 2 1.76 4 0.627 11.4 8 3 1.77 4 0.628 11.4 8 138 4 1.78 4 0.628 11.4 8 5 1.77 4 0.629 11.4 8 6 1.77 4 0.629 11.4 8 1 2.4 3 0.62 11.3 8 2 2.4 3 0.62 11.3 8 3 2.39 3 0.62 11.3 8 139 4 2.34 3 0.612 11.1 8 5 2.35 3 0.612 11.1 8 6 2.34 3 0.612 11.1 8 1 2.24 3 0.601 10.9 8 2 2.25 3 0.603 11 8 3 2.26 3 0.604 11 8 140 4 2.12 3 0.577 10.5 8 5 2.12 3 0.577 10.5 8 6 2.12 3 0.579 10.5 8 1 2.33 3 0.618 11.2 8 2 2.33 3 0.618 11.2 8 3 2.33 3 0.618 11.2 8 141 4 2.26 3 0.609 11.1 8 5 2.27 3 0.609 11.1 8 6 2.28 3 0.61 11.1 8 1 1.87 4 0.513 9.3 8 2 1.9 4 0.513 9.3 8 3 1.85 4 0.513 9.3 8 142 4 1.85 4 0.502 9.1 8 5 1.85 4 0.502 9.1 8 6 1.85 4 0.501 9.1 8 1 2.1 3 0.506 9.2 8 143 2 2.11 3 0.508 9.2 8 124 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.11 3 0.508 9.2 8 4 2.13 3 0.513 9.3 8 5 2.14 3 0.513 9.3 8 6 2.14 3 0.513 9.3 8 1 1.77 4 0.561 10.2 8 2 1.78 4 0.561 10.2 8 3 1.78 4 0.561 10.2 8 144 4 1.67 4 0.541 9.8 8 5 1.69 4 0.542 9.8 8 6 1.69 4 0.542 9.8 8 1 1.17 4 0.614 11.2 8 2 1.17 4 0.615 11.2 8 3 1.17 4 0.615 11.2 8 145 4 1.04 4 0.546 9.9 8 5 1.03 4 0.546 9.9 8 6 1.04 4 0.546 9.9 8 1 2.01 4 0.547 9.9 8 2 2.01 4 0.547 9.9 8 3 2 4 0.547 9.9 8 146 4 1.99 4 0.546 9.9 8 5 2 4 0.546 9.9 8 6 1.99 4 0.544 9.9 8 1 1.3 4 0.562 10.2 8 2 1.29 4 0.561 10.2 8 3 1.3 4 0.561 10.2 8 147 4 1.24 4 0.537 9.8 8 5 1.24 4 0.537 9.8 8 6 1.23 4 0.535 9.7 8 1 0.9 8 0.537 9.8 8 2 0.9 8 0.535 9.7 8 3 0.9 8 0.537 9.8 8 148 4 0.86 8 0.513 9.3 8 5 0.86 8 0.511 9.3 8 6 0.86 8 0.51 9.3 8 1 1.3 4 0.562 10.2 8 2 1.29 4 0.561 10.2 8 149 3 1.3 4 0.561 10.2 8 4 1.24 4 0.537 9.8 8 5 1.24 4 0.537 9.8 8 125 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.23 4 0.535 9.7 8 1 1.33 4 0.468 8.5 8 2 1.33 4 0.468 8.5 8 3 1.34 4 0.469 8.5 8 150 4 1.31 4 0.458 8.3 8 5 1.31 4 0.458 8.3 8 6 1.31 4 0.458 8.3 8 1 1.16 4 0.448 8.1 8 2 1.15 4 0.447 8.1 8 3 1.16 4 0.448 8.1 8 151 4 1.2 4 0.461 8.4 8 5 1.2 4 0.459 8.3 8 6 1.2 4 0.461 8.4 8 1 1.18 4 0.425 7.7 8 2 1.19 4 0.425 7.7 8 3 1.18 4 0.425 7.7 8 152 4 1.21 4 0.431 7.8 8 5 1.21 4 0.431 7.8 8 6 1.21 4 0.431 7.8 8 1 1.12 4 0.547 9.9 8 2 1.12 4 0.547 9.9 8 3 1.12 4 0.546 9.9 8 153 4 1.11 4 0.546 9.9 8 5 1.12 4 0.547 9.9 8 6 1.12 4 0.547 9.9 8 1 1.01 4 0.554 10.1 8 2 1.01 4 0.554 10.1 8 3 1.01 4 0.554 10.1 8 154 4 0.97 8 0.539 9.8 8 5 0.97 8 0.538 9.8 8 6 0.97 8 0.538 9.8 8 1 1.2 4 0.537 9.7 8 2 1.19 4 0.534 9.7 8 3 1.2 4 0.535 9.7 8 155 4 1.19 4 0.533 9.7 8 5 1.19 4 0.533 9.7 8 6 1.19 4 0.534 9.7 8 1 2.12 3 0.505 9 7.9 156 2 2.11 3 0.505 9 7.9 126 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.12 3 0.505 9 7.9 4 2.17 3 0.587 10.5 7.9 5 2.11 3 0.506 9.1 7.9 6 2.12 3 0.505 9 7.9 1 1.67 4 0.51 9.1 7.9 2 1.67 4 0.51 9.1 7.9 3 1.68 4 0.51 9.1 7.9 157 4 1.65 4 0.511 9.2 7.9 5 1.65 4 0.511 9.2 7.9 6 1.66 4 0.511 9.2 7.9 1 1.95 4 0.514 9.2 7.9 2 1.95 4 0.514 9.2 7.9 3 1.95 4 0.514 9.2 7.9 158 4 2.04 4 0.541 9.7 7.9 5 2.04 4 0.541 9.7 7.9 6 2.05 4 0.541 9.7 7.9 1 1.61 4 0.485 8.8 8 2 1.61 4 0.485 8.8 8 3 1.61 4 0.485 8.8 8 159 4 1.59 4 0.478 8.7 8 5 1.59 4 0.478 8.7 8 6 1.59 4 0.478 8.7 8 1 1.46 4 0.636 11.6 8 2 1.46 4 0.636 11.6 8 3 1.45 4 0.636 11.6 8 160 4 1.44 4 0.631 11.5 8 5 1.44 4 0.632 11.5 8 6 1.44 4 0.631 11.5 8 1 1.91 4 0.511 9.3 8 2 1.92 4 0.511 9.3 8 3 1.91 4 0.511 9.3 8 161 4 2 4 0.529 9.6 8 5 2 4 0.528 9.6 8 6 2 4 0.528 9.6 8 1 1.51 4 0.519 9.4 8 2 1.51 4 0.518 9.4 8 162 3 1.51 4 0.518 9.4 8 4 1.5 4 0.515 9.4 8 5 1.51 4 0.515 9.4 8 127 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.51 4 0.514 9.3 8 1 2 4 0.567 10.3 8 2 1.98 4 0.566 10.3 8 3 2 4 0.567 10.3 8 163 4 1.94 4 0.543 9.9 8 5 1.94 4 0.543 9.9 8 6 1.95 4 0.544 9.9 8 1 1.41 4 0.48 8.7 8 2 1.41 4 0.48 8.7 8 3 1.41 4 0.48 8.7 8 164 4 1.44 4 0.485 8.8 8 5 1.44 4 0.483 8.8 8 6 1.44 4 0.485 8.8 8 1 1.63 4 0.627 11.2 7.9 2 1.63 4 0.627 11.2 7.9 3 1.61 4 0.627 11.2 7.9 165 4 1.62 4 0.626 11.2 7.9 5 1.63 4 0.627 11.2 7.9 6 1.63 4 0.627 11.2 7.9 1 1.47 4 0.577 10.5 8 2 1.44 4 0.577 10.5 8 3 1.44 4 0.577 10.5 8 166 4 1.46 4 0.581 10.6 8 5 1.46 4 0.581 10.6 8 6 1.46 4 0.579 10.5 8 1 2.02 4 0.587 10.7 8 2 2.02 4 0.588 10.7 8 3 2.01 4 0.588 10.7 8 167 4 2.07 4 0.597 10.9 8 5 2.06 4 0.596 10.8 8 6 2.07 4 0.596 10.8 8 1 2.16 3 0.567 10.1 7.9 2 2.18 3 0.565 10.1 7.9 3 2.17 3 0.564 10.1 7.9 168 4 2.16 3 0.576 10.3 7.9 5 2.16 3 0.576 10.3 7.9 6 2.16 3 0.574 10.3 7.9 1 1.76 4 0.553 10.1 8 169 2 1.77 4 0.555 10.1 8 128 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 1.77 4 0.554 10.1 8 4 1.77 4 0.555 10.1 8 5 1.76 4 0.553 10.1 8 6 1.77 4 0.555 10.1 8 1 2.07 4 0.56 10.2 8 2 2.07 4 0.559 10.2 8 3 2.06 4 0.56 10.2 8 170 4 2.1 4 0.57 10.4 8 5 2.12 3 0.57 10.4 8 6 2.08 4 0.57 10.4 8 1 2.04 4 0.524 9.5 8 2 2.04 4 0.524 9.5 8 3 2.04 4 0.524 9.5 8 171 4 2.04 4 0.524 9.5 8 5 2.04 4 0.524 9.5 8 6 2.04 4 0.524 9.5 8 1 1.8 4 0.48 8.7 8 2 1.8 4 0.48 8.7 8 3 1.8 4 0.48 8.7 8 172 4 1.8 4 0.48 8.7 8 5 1.8 4 0.48 8.7 8 6 1.8 4 0.48 8.7 8 1 2.05 4 0.528 9.6 8 2 2.05 4 0.528 9.6 8 3 2.05 4 0.528 9.6 8 173 4 2.06 4 0.528 9.6 8 5 2.06 4 0.528 9.6 8 6 2.06 4 0.528 9.6 8 1 1.92 4 0.578 10.5 8 2 1.92 4 0.577 10.5 8 3 1.92 4 0.577 10.5 8 174 4 1.86 4 0.559 10.2 8 5 1.86 4 0.559 10.2 8 6 1.85 4 0.56 10.2 8 1 1.43 4 0.54 9.8 8 2 1.42 4 0.539 9.8 8 175 3 1.44 4 0.54 9.8 8 5 1.35 4 0.511 9.3 8 6 1.35 4 0.51 9.3 8 129 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 7 1.35 4 0.51 9.3 8 1 1.66 4 0.553 10.1 8 2 1.66 4 0.554 10.1 8 3 1.66 4 0.553 10.1 8 176 4 1.64 4 0.546 9.9 8 5 1.64 4 0.546 9.9 8 6 1.65 4 0.545 9.9 8 1 2.57 2 0.627 11.4 8 2 2.57 2 0.627 11.4 8 3 2.57 2 0.627 11.4 8 177 4 2.55 2 0.625 11.4 8 5 2.56 2 0.627 11.4 8 6 2.56 2 0.627 11.4 8 1 2.36 3 0.635 11.6 8 2 2.36 3 0.634 11.5 8 3 2.34 3 0.632 11.5 8 178 4 2.53 2 0.678 12.3 8 5 2.54 2 0.679 12.4 8 6 2.53 2 0.678 12.3 8 1 2.29 3 0.636 11.6 8 2 2.31 3 0.637 11.6 8 3 2.31 3 0.637 11.6 8 179 4 2.3 3 0.636 11.6 8 5 2.3 3 0.639 11.6 8 6 2.31 3 0.637 11.6 8 1 2.35 3 0.697 12.7 8 2 2.35 3 0.696 12.7 8 3 2.35 3 0.694 12.6 8 180 4 2.36 3 0.698 12.7 8 5 2.36 3 0.697 12.7 8 6 2.36 3 0.696 12.7 8 1 1.9 4 0.749 13.6 8 2 1.9 4 0.749 13.6 8 3 1.89 4 0.749 13.6 8 181 4 1.9 4 0.75 13.6 8 5 1.9 4 0.749 13.6 8 6 1.9 4 0.749 13.6 8 1 1.68 4 0.667 12.1 8 182 2 1.7 4 0.669 12.2 8 130 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 1.7 4 0.669 12.2 8 4 1.7 4 0.669 12.2 8 5 1.69 4 0.667 12.1 8 6 1.7 4 0.668 12.2 8 1 2.57 2 0.673 12.1 7.9 2 2.57 2 0.674 12.1 7.9 3 2.57 2 0.674 12.1 7.9 183 4 2.52 2 0.66 11.9 7.9 5 2.52 2 0.662 11.9 7.9 6 2.52 2 0.66 11.9 7.9 1 1.91 4 0.617 11.1 7.9 2 1.89 4 0.616 11.1 7.9 3 1.91 4 0.617 11.1 7.9 184 4 1.99 4 0.645 11.6 7.9 5 1.99 4 0.645 11.6 7.9 6 1.98 4 0.644 11.6 7.9 1 1.91 4 0.617 11.1 7.9 2 1.89 4 0.616 11.1 7.9 3 1.91 4 0.617 11.1 7.9 185 4 1.99 4 0.645 11.6 7.9 5 1.99 4 0.645 11.6 7.9 6 1.98 4 0.644 11.6 7.9 1 2.45 2 0.591 10.7 8 2 2.45 2 0.589 10.7 8 3 2.38 3 0.574 10.4 8 186 4 2.38 3 0.575 10.5 8 5 2.38 3 0.574 10.4 8 6 2.38 3 0.574 10.4 8 1 2.18 3 0.577 10.5 8 2 2.19 3 0.575 10.5 8 3 2.19 3 0.575 10.5 8 187 4 2.2 3 0.586 10.7 8 5 2.21 3 0.588 10.7 8 6 2.21 3 0.587 10.7 8 1 2.76 1 0.616 11.2 8 2 2.78 1 0.617 11.2 8 188 3 2.78 1 0.617 11.2 8 4 2.74 1 0.613 11.2 8 5 2.73 1 0.612 11.1 8 131 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.74 1 0.612 11.1 8 1 3.7 1 0.763 13.9 8 2 3.7 1 0.763 13.9 8 3 3.72 1 0.761 13.9 8 189 4 3.44 1 0.732 13.3 8 5 3.46 1 0.732 13.3 8 6 3.45 1 0.731 13.3 8 1 3.42 1 0.729 13.3 8 2 3.44 1 0.729 13.3 8 3 3.42 1 0.727 13.2 8 190 4 3.5 1 0.751 13.7 8 5 3.52 1 0.75 13.6 8 6 3.52 1 0.75 13.6 8 1 3.5 1 0.711 12.9 8 2 3.49 1 0.711 12.9 8 3 3.52 1 0.713 13 8 191 4 3.03 1 0.718 13.1 8 5 3.54 1 0.732 13.3 8 6 3.54 1 0.732 13.3 8 1 3.63 1 0.75 13.6 8 2 3.64 1 0.75 13.6 8 3 3.6 1 0.749 13.6 8 192 4 3.69 1 0.759 13.8 8 5 3.67 1 0.759 13.8 8 6 3.7 1 0.759 13.8 8 1 3.75 1 0.778 14.2 8 2 3.74 1 0.779 14.2 8 3 3.76 1 0.778 14.2 8 193 4 3.67 1 0.779 14.2 8 5 3.68 1 0.78 14.2 8 6 3.69 1 0.78 14.2 8 1 3.58 1 0.758 13.8 8 2 3.58 1 0.758 13.8 8 3 3.58 1 0.758 13.8 8 194 4 3.57 1 0.759 13.8 8 5 3.55 1 0.759 13.8 8 6 3.58 1 0.758 13.8 8 1 2.08 4 0.54 9.8 8 195 2 2.08 4 0.54 9.8 8 132 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.08 4 0.54 9.8 8 4 2.09 4 0.54 9.8 8 5 1.99 4 0.54 9.8 8 6 2.01 4 0.54 9.8 8 1 2.14 3 0.551 10 8 2 2.14 3 0.551 10 8 3 2.14 3 0.551 10 8 196 4 2.09 3 0.551 10 8 5 2.09 3 0.551 10 8 6 2.09 3 0.551 10 8 1 2.5 2 0.583 10.6 8 2 2.5 2 0.583 10.6 8 3 2.5 2 0.583 10.6 8 197 4 2.38 2 0.583 10.6 8 5 2.38 2 0.583 10.6 8 6 2.38 2 0.583 10.6 8 1 2.79 1 0.631 11.5 8 2 2.81 1 0.634 11.5 8 3 2.8 1 0.634 11.5 8 198 4 2.86 1 0.649 11.8 8 5 2.89 1 0.65 11.8 8 6 2.89 1 0.65 11.8 8 1 2.49 2 0.597 10.9 8 2 2.48 2 0.598 10.9 8 3 2.49 2 0.597 10.9 8 199 4 2.6 2 0.625 11.4 8 5 2.61 1 0.625 11.4 8 6 2.61 1 0.624 11.3 8 1 2.34 3 0.575 10.5 8 2 2.33 3 0.575 10.5 8 3 2.35 3 0.577 10.5 8 200 4 2.42 2 0.6 10.9 8 5 2.43 2 0.596 10.8 8 6 2.44 2 0.596 10.8 8 1 2.13 3 0.693 12.6 8 2 2.13 3 0.693 12.6 8 201 3 2.13 3 0.693 12.6 8 4 2 4 0.655 11.9 8 5 2 4 0.657 11.9 8 133 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.99 4 0.655 11.9 8 1 2.32 3 0.738 13.4 8 2 2.33 3 0.736 13.4 8 3 2.33 3 0.736 13.4 8 202 4 2.2 3 0.684 12.4 8 5 2.2 3 0.683 12.4 8 6 2.2 3 0.683 12.4 8 1 2.2 3 0.602 11 8 2 2.22 3 0.603 11 8 3 2.2 3 0.603 11 8 203 4 2.19 3 0.601 10.9 8 5 2.18 3 0.601 10.9 8 6 2.19 3 0.601 10.9 8 1 2.25 3 0.616 11.2 8 2 2.25 3 0.615 11.2 8 3 2.24 3 0.615 11.2 8 204 4 2.25 3 0.624 11.3 8 5 2.23 3 0.622 11.3 8 6 2.25 3 0.624 11.3 8 1 2.49 2 0.615 11.2 8 2 2.5 2 0.615 11.2 8 3 2.49 2 0.615 11.2 8 205 4 2.53 2 0.627 11.4 8 5 2.54 2 0.627 11.4 8 6 2.54 2 0.627 11.4 8 1 1.89 4 0.597 10.8 8 2 1.87 4 0.596 10.8 8 3 1.89 4 0.597 10.8 8 206 4 1.97 4 0.626 11.4 8 5 1.96 4 0.626 11.4 8 6 1.98 4 0.626 11.4 8 1 2.05 4 0.706 12.8 8 2 2.05 4 0.705 12.8 8 3 2.05 4 0.703 12.8 8 207 4 1.98 4 0.675 12.3 8 5 1.98 4 0.675 12.3 8 6 1.99 4 0.675 12.3 8 1 1.87 4 0.713 13 8 208 2 1.87 4 0.712 13 8 134 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 1.87 4 0.713 13 8 4 1.76 4 0.67 12.2 8 5 1.76 4 0.672 12.2 8 6 1.75 4 0.67 12.2 8 1 2.42 2 0.687 12.5 8 2 2.42 2 0.688 12.5 8 3 2.41 2 0.687 12.5 8 209 4 2.4 3 0.682 12.4 8 5 2.4 3 0.682 12.4 8 6 2.4 3 0.682 12.4 8 1 3.04 1 0.707 12.9 8 2 3.04 1 0.707 12.9 8 3 3.05 1 0.706 12.8 8 210 4 2.95 1 0.684 12.4 8 5 2.95 1 0.686 12.5 8 6 2.95 1 0.684 12.4 8 1 2.58 2 0.72 13.1 8 2 2.58 2 0.72 13.1 8 3 2.59 2 0.718 13.1 8 211 4 2.42 2 0.675 12.3 8 5 2.41 2 0.675 12.3 8 6 2.42 2 0.674 12.3 8 1 2.5 2 0.694 12.6 8 2 2.49 2 0.693 12.6 8 3 2.5 2 0.693 12.6 8 212 4 2.48 2 0.688 12.5 8 5 2.48 2 0.688 12.5 8 6 2.48 2 0.688 12.5 8 1 2.06 4 0.588 10.7 8 2 2.08 4 0.588 10.7 8 3 2.08 4 0.589 10.7 8 213 4 2.13 3 0.602 10.9 8 5 2.12 3 0.601 10.9 8 6 2.12 3 0.601 10.9 8 1 2.14 3 0.588 10.7 8 2 2.13 3 0.588 10.7 8 214 3 2.14 3 0.588 10.7 8 4 2.2 3 0.603 11 8 5 2.19 3 0.603 11 8 135 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.2 3 0.603 11 8 1 2.26 3 0.541 9.8 8 2 2.27 3 0.54 9.8 8 3 2.26 3 0.54 9.8 8 215 4 2.34 3 0.554 10.1 8 5 2.34 3 0.555 10.1 8 6 2.35 3 0.555 10.1 8 1 2.22 3 0.534 9.7 8 2 2.23 3 0.532 9.7 8 3 2.23 3 0.532 9.7 8 216 4 2.33 3 0.558 10.1 8 5 2.33 3 0.558 10.1 8 6 2.32 3 0.559 10.2 8 1 2.44 2 0.548 10 8 2 2.43 2 0.548 10 8 3 2.41 2 0.546 9.9 8 217 4 2.49 2 0.562 10.2 8 5 2.48 2 0.562 10.2 8 6 2.48 2 0.56 10.2 8 1 2.01 4 0.508 9.2 8 2 2.01 4 0.508 9.2 8 3 2.01 4 0.508 9.2 8 218 4 2.03 4 0.511 9.3 8 5 2.03 4 0.511 9.3 8 6 2.01 4 0.51 9.3 8 1 2.12 3 0.53 9.6 8 2 2.11 3 0.527 9.6 8 3 2.14 3 0.529 9.6 8 219 4 2.18 3 0.544 9.9 8 5 2.19 3 0.543 9.9 8 6 2.19 3 0.544 9.9 8 1 2.26 3 0.526 9.6 8 2 2.27 3 0.525 9.6 8 3 2.27 3 0.525 9.6 8 220 4 2.29 3 0.527 9.6 8 5 2.27 3 0.527 9.6 8 6 2.3 3 0.529 9.6 8 1 2.4 2 0.56 10.2 8 221 2 2.4 2 0.56 10.2 8 136 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.38 3 0.559 10.2 8 4 2.38 3 0.559 10.2 8 5 2.39 3 0.56 10.2 8 6 2.4 3 0.56 10.2 8 1 2.31 3 0.581 10.5 8 2 2.32 3 0.579 10.5 8 3 2.31 3 0.581 10.5 8 222 4 2.24 3 0.568 10.3 8 5 2.23 3 0.567 10.3 8 6 2.25 3 0.567 10.3 8 1 2.04 4 0.559 10.1 8 2 2.03 4 0.558 10.1 8 3 2.03 4 0.559 10.1 8 223 4 2.03 4 0.559 10.1 8 5 2.02 4 0.559 10.1 8 6 2.03 4 0.559 10.1 8 1 2.14 3 0.563 10.2 8 2 2.15 3 0.564 10.2 8 3 2.15 3 0.564 10.2 8 224 4 2.04 4 0.541 9.8 8 5 2.05 4 0.541 9.8 8 6 2.03 4 0.541 9.8 8 1 2.19 3 0.616 11.2 8 2 2.19 3 0.617 11.2 8 3 2.19 3 0.617 11.2 8 225 4 2.17 3 0.61 11.1 8 5 2.17 3 0.608 11.1 8 6 2.17 3 0.608 11.1 8 1 1.92 4 0.62 11.3 8 2 1.92 4 0.62 11.3 8 3 1.92 4 0.62 11.3 8 226 4 1.87 4 0.607 11 8 5 1.87 4 0.607 11 8 6 1.87 4 0.607 11 8 1 2.45 2 0.621 11.3 8 2 2.46 2 0.622 11.3 8 227 3 2.46 2 0.622 11.3 8 4 2.42 2 0.617 11.2 8 5 2.41 2 0.615 11.2 8 137 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.43 2 0.615 11.2 8 1 1.63 4 0.5 9.1 8 2 1.63 4 0.5 9.1 8 3 1.63 4 0.5 9.1 8 228 4 1.58 4 0.483 8.8 8 5 1.58 4 0.484 8.8 8 6 1.58 4 0.484 8.8 8 1 2 4 0.53 9.6 8 2 2.01 4 0.53 9.6 8 3 2.01 4 0.53 9.6 8 229 4 1.87 4 0.506 9.2 8 5 1.89 4 0.506 9.2 8 6 1.89 4 0.506 9.2 8 1 2.15 3 0.515 9.4 8 2 2.17 3 0.516 9.4 8 3 2.17 3 0.516 9.4 8 230 4 2.1 3 0.502 9.1 8 5 2.11 3 0.502 9.1 8 6 2.11 3 0.502 9.1 8 1 2.29 3 0.546 9.9 8 2 2.29 3 0.546 9.9 8 3 2.28 3 0.546 9.9 8 231 4 2.23 3 0.539 9.8 8 5 2.23 3 0.538 9.8 8 6 2.24 3 0.538 9.8 8 1 1.81 4 0.549 10 8 2 1.82 4 0.548 10 8 3 1.81 4 0.548 10 8 232 4 1.76 4 0.534 9.7 8 5 1.77 4 0.535 9.7 8 6 1.76 4 0.535 9.7 8 1 1.95 4 0.524 9.5 8 2 1.96 4 0.522 9.5 8 3 1.96 4 0.524 9.5 8 233 4 1.88 4 0.503 9.2 8 5 1.89 4 0.505 9.2 8 6 1.89 4 0.505 9.2 8 1 1.73 4 0.636 11.6 8 234 2 1.72 4 0.635 11.5 8 138 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 1.73 4 0.636 11.6 8 4 1.72 4 0.636 11.6 8 5 1.72 4 0.636 11.6 8 6 1.72 4 0.635 11.5 8 1 2.11 3 0.663 12 8 2 2.11 3 0.663 12 8 3 2.12 3 0.663 12 8 235 4 2.03 4 0.635 11.5 8 5 2.03 4 0.635 11.5 8 6 2.03 4 0.635 11.5 8 1 2.66 1 0.655 11.9 8 2 2.66 1 0.655 11.9 8 3 2.66 1 0.655 11.9 8 236 4 2.68 1 0.651 11.8 8 5 2.68 1 0.651 11.8 8 6 2.67 1 0.653 11.9 8 1 2.45 2 0.612 11.1 8 2 2.44 2 0.612 11.1 8 3 2.44 2 0.613 11.2 8 237 4 2.42 2 0.603 11 8 5 2.41 2 0.602 11 8 6 2.41 2 0.602 11 8 1 2.44 2 0.619 11.3 8 2 2.46 2 0.62 11.3 8 3 2.45 2 0.62 11.3 8 238 4 2.55 2 0.64 11.6 8 5 2.55 2 0.64 11.6 8 6 2.55 2 0.64 11.6 8 1 2.53 2 0.606 11 8 2 2.53 2 0.607 11 8 3 2.52 2 0.606 11 8 239 4 2.64 1 0.635 11.6 8 5 2.67 1 0.637 11.6 8 6 2.66 1 0.636 11.6 8 1 2.16 3 0.62 11.3 8 2 2.17 3 0.619 11.3 8 240 3 2.18 3 0.619 11.3 8 4 2.13 3 0.608 11.1 8 5 2.14 3 0.61 11.1 8 139 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.14 3 0.61 11.1 8 1 1.3 4 0.659 12 8 2 1.31 4 0.66 12 8 3 1.3 4 0.662 12 8 241 4 1.31 4 0.667 12.1 8 5 1.31 4 0.668 12.2 8 6 1.31 4 0.668 12.2 8 1 1.5 4 0.587 10.7 8 2 1.49 4 0.587 10.7 8 3 1.5 4 0.588 10.7 8 242 4 1.51 4 0.592 10.8 8 5 1.51 4 0.591 10.7 8 6 1.51 4 0.589 10.7 8 1 2.13 3 0.564 10.2 8 2 2.15 3 0.564 10.2 8 3 2.11 3 0.564 10.2 8 243 4 2.22 3 0.582 10.6 8 5 2.23 3 0.582 10.6 8 6 2.23 3 0.582 10.6 8 1 1.5 4 0.575 10.4 8 2 1.49 4 0.574 10.4 8 3 1.48 4 0.574 10.4 8 244 4 1.55 4 0.593 10.8 8 5 1.55 4 0.592 10.7 8 6 1.55 4 0.592 10.7 8 1 2.16 3 0.565 10.3 8 2 2.16 3 0.565 10.3 8 3 2.15 3 0.565 10.3 8 245 4 2.22 3 0.581 10.5 8 5 2.23 3 0.581 10.5 8 6 2.23 3 0.581 10.5 8 1 1.89 4 0.478 8.7 8 2 1.89 4 0.478 8.7 8 3 1.89 4 0.478 8.7 8 246 4 1.96 4 0.496 9 8 5 1.96 4 0.496 9 8 6 1.95 4 0.496 9 8 1 1.61 4 0.488 8.9 8 247 2 1.6 4 0.487 8.9 8 140 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 1.6 4 0.487 8.9 8 4 1.58 4 0.484 8.8 8 5 1.59 4 0.483 8.8 8 6 1.59 4 0.484 8.8 8 1 1.79 4 0.478 8.7 8 2 1.77 4 0.478 8.7 8 3 1.79 4 0.478 8.7 8 248 4 1.75 4 0.472 8.6 8 5 1.76 4 0.474 8.6 8 6 1.76 4 0.473 8.6 8 1 2.12 3 0.506 9.2 8 2 2.15 3 0.507 9.2 8 3 2.15 3 0.508 9.3 8 249 4 2.1 3 0.502 9.1 8 5 2.11 3 0.502 9.1 8 6 2.1 3 0.501 9.1 8 1 1.85 4 0.496 9 8 2 1.86 4 0.496 9 8 3 1.86 4 0.496 9 8 250 4 1.89 4 0.511 9.3 8 5 1.9 4 0.51 9.3 8 6 1.89 4 0.51 9.3 8 1 1.89 4 0.506 9.2 8 2 1.89 4 0.506 9.2 8 3 1.9 4 0.506 9.2 8 251 4 1.83 4 0.497 9 8 5 1.82 4 0.495 9 8 6 1.83 4 0.496 9 8 1 1.8 4 0.519 9.4 8 2 1.79 4 0.519 9.4 8 3 1.8 4 0.52 9.5 8 252 4 1.73 4 0.502 9.1 8 5 1.73 4 0.5 9.1 8 6 1.72 4 0.5 9.1 8 1 1.75 4 0.546 9.9 8 2 1.73 4 0.543 9.9 8 253 3 1.75 4 0.545 9.9 8 4 1.74 4 0.544 9.9 8 5 1.74 4 0.543 9.9 8 141 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.74 4 0.544 9.9 8 1 2.3 3 0.565 10.3 8 2 2.31 3 0.563 10.2 8 3 2.31 3 0.564 10.3 8 254 4 2.24 3 0.548 10 8 5 2.26 3 0.55 10 8 6 2.25 3 0.55 10 8 1 2.25 3 0.62 11.3 8 2 2.25 3 0.622 11.3 8 3 2.26 3 0.622 11.3 8 255 4 2.28 3 0.626 11.4 8 5 2.29 3 0.627 11.4 8 6 2.29 3 0.626 11.4 8 1 2.32 3 0.673 12.2 8 2 2.32 3 0.672 12.2 8 3 2.33 3 0.672 12.2 8 256 4 2.32 3 0.67 12.2 8 5 2.32 3 0.672 12.2 8 6 2.31 3 0.672 12.2 8 1 2.68 1 0.655 11.9 8 2 2.67 1 0.654 11.9 8 3 2.68 1 0.654 11.9 8 257 4 2.67 1 0.656 11.9 8 5 2.67 1 0.655 11.9 8 6 2.68 1 0.654 11.9 8 1 3.18 1 0.698 12.7 8 2 3.18 1 0.698 12.7 8 3 3.18 1 0.698 12.7 8 258 4 3.17 1 0.698 12.7 8 5 3.15 1 0.697 12.7 8 6 3.15 1 0.697 12.7 8 1 2.15 3 0.653 11.9 8 2 2.15 3 0.651 11.9 8 3 2.15 3 0.653 11.9 8 259 4 2.14 3 0.653 11.9 8 5 2.16 3 0.653 11.9 8 6 2.16 3 0.651 11.9 8 1 2.13 3 0.668 12.2 8 260 2 2.12 3 0.668 12.2 8 142 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.13 3 0.669 12.2 8 4 2.09 4 0.659 12 8 5 2.08 4 0.656 11.9 8 6 2.08 4 0.658 12 8 1 2.84 1 0.672 12.2 8 2 2.82 1 0.67 12.2 8 3 2.83 1 0.67 12.2 8 261 4 2.83 1 0.67 12.2 8 5 2.83 1 0.672 12.2 8 6 2.84 1 0.672 12.2 8 1 3.05 1 0.711 12.9 8 2 3.04 1 0.713 13 8 3 3.05 1 0.712 13 8 262 4 2.98 1 0.691 12.6 8 5 2.96 1 0.688 12.5 8 6 2.98 1 0.691 12.6 8 1 3.1 1 0.688 12.5 8 2 3.08 1 0.686 12.5 8 3 3.12 1 0.687 12.5 8 263 4 3.16 1 0.702 12.8 8 5 3.17 1 0.705 12.8 8 6 3.16 1 0.702 12.8 8 1 2.59 2 0.581 10.6 8 2 2.6 2 0.582 10.6 8 3 2.59 2 0.581 10.6 8 264 4 2.6 1 0.583 10.6 8 5 2.58 2 0.582 10.6 8 6 2.59 2 0.583 10.6 8 1 2.35 3 0.608 11.1 8 2 2.35 3 0.606 11 8 3 2.37 3 0.607 11 8 265 4 2.28 3 0.593 10.8 8 5 2.3 3 0.596 10.8 8 6 2.3 3 0.596 10.8 8 1 2.41 2 0.591 10.7 8 2 2.4 3 0.591 10.7 8 266 3 2.41 2 0.591 10.7 8 4 2.42 2 0.592 10.8 8 5 2.42 2 0.592 10.8 8 143 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.42 2 0.592 10.8 8 1 2.49 2 0.55 10 8 2 2.49 2 0.55 10 8 3 2.48 2 0.55 10 8 267 4 2.48 2 0.549 10 8 5 2.49 2 0.55 10 8 6 2.47 2 0.55 10 8 1 2.44 2 0.568 10.3 8 2 2.46 2 0.569 10.3 8 3 2.45 2 0.569 10.3 8 268 4 2.52 2 0.582 10.6 8 5 2.53 2 0.581 10.5 8 6 2.51 2 0.581 10.5 8 1 2.31 3 0.574 10.4 8 2 2.31 3 0.573 10.4 8 3 2.31 3 0.573 10.4 8 269 4 2.3 3 0.577 10.5 8 5 2.32 3 0.578 10.5 8 6 2.33 3 0.578 10.5 8 1 1.75 4 0.57 10.4 8 2 1.75 4 0.568 10.3 8 3 1.74 4 0.568 10.3 8 270 4 1.75 4 0.57 10.4 8 5 1.74 4 0.567 10.3 8 6 1.75 4 0.568 10.3 8 1 1.8 4 0.538 9.8 8 2 1.79 4 0.536 9.8 8 3 1.8 4 0.538 9.8 8 271 4 1.81 4 0.543 9.9 8 5 1.82 4 0.543 9.9 8 6 1.81 4 0.541 9.8 8 1 1.43 4 0.51 9.3 8 2 1.44 4 0.511 9.3 8 3 1.44 4 0.511 9.3 8 272 4 1.36 4 0.517 9.4 8 5 1.43 4 0.51 9.3 8 6 1.44 4 0.51 9.3 8 1 1.19 4 0.506 9.2 8 273 2 1.19 4 0.506 9.2 8 144 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 1.19 4 0.505 9.2 8 4 1.2 4 0.51 9.3 8 5 1.2 4 0.51 9.3 8 6 1.2 4 0.508 9.3 8 1 1.33 4 0.525 9.6 8 2 1.33 4 0.525 9.6 8 3 1.34 4 0.526 9.6 8 274 4 1.34 4 0.529 9.6 8 5 1.34 4 0.529 9.6 8 6 1.34 4 0.529 9.6 8 1 2.56 2 0.681 12.4 8 2 2.54 2 0.681 12.4 8 3 2.55 2 0.681 12.4 8 275 4 2.47 2 0.662 12 8 5 2.46 2 0.662 12 8 6 2.46 2 0.662 12 8 1 2.09 4 0.622 11.3 8 2 2.1 4 0.621 11.3 8 3 2.09 4 0.621 11.3 8 276 4 1.97 4 0.586 10.7 8 5 1.95 4 0.583 10.6 8 6 1.96 4 0.584 10.6 8 1 2 4 0.589 10.7 8 2 1.99 4 0.589 10.7 8 3 2 4 0.589 10.7 8 277 4 1.98 4 0.581 10.6 8 5 1.97 4 0.581 10.6 8 6 1.98 4 0.581 10.6 8 1 1.54 4 0.515 9.4 8 2 1.54 4 0.514 9.3 8 3 1.54 4 0.514 9.3 8 278 4 1.52 4 0.506 9.2 8 5 1.52 4 0.503 9.2 8 6 1.52 4 0.505 9.2 8 1 1.53 4 0.479 8.7 8 2 1.52 4 0.478 8.7 8 279 3 1.53 4 0.478 8.7 8 4 1.56 4 0.481 8.7 8 5 1.56 4 0.482 8.8 8 145 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.56 4 0.482 8.8 8 1 1.88 4 0.52 9.5 8 2 1.88 4 0.52 9.5 8 3 1.88 4 0.521 9.5 8 280 4 2.02 4 0.524 9.5 8 5 2.01 4 0.524 9.5 8 6 2.01 4 0.524 9.5 8 1 1.87 4 0.544 9.9 8 2 1.87 4 0.543 9.9 8 3 1.87 4 0.544 9.9 8 281 4 1.78 4 0.52 9.5 8 5 1.79 4 0.52 9.5 8 6 1.8 4 0.521 9.5 8 1 1.79 4 0.52 9.5 8 2 1.79 4 0.519 9.4 8 3 1.79 4 0.519 9.4 8 282 4 1.72 4 0.505 9.2 8 5 1.72 4 0.505 9.2 8 6 1.73 4 0.505 9.2 8 1 1.74 4 0.543 9.9 8 2 1.74 4 0.543 9.9 8 3 1.74 4 0.543 9.9 8 283 4 1.69 4 0.532 9.7 8 5 1.69 4 0.532 9.7 8 6 1.69 4 0.532 9.7 8 1 1.54 4 0.593 10.8 8 2 1.54 4 0.593 10.8 8 3 1.54 4 0.592 10.8 8 284 4 1.57 4 0.606 11 8 5 1.57 4 0.606 11 8 6 1.57 4 0.606 11 8 1 1.17 4 0.62 11.3 8 2 1.17 4 0.621 11.3 8 3 1.17 4 0.621 11.3 8 285 4 1.16 4 0.619 11.3 8 5 1.17 4 0.62 11.3 8 6 1.16 4 0.62 11.3 8 1 1.5 4 0.65 11.8 8 286 2 1.5 4 0.65 11.8 8 146 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 1.5 4 0.65 11.8 8 4 1.45 4 0.63 11.4 8 5 1.45 4 0.629 11.4 8 6 1.46 4 0.63 11.4 8 1 2.59 2 0.66 12 8 2 2.6 2 0.66 12 8 3 2.6 2 0.66 12 8 287 4 2.5 2 0.688 12.5 8 5 2.5 2 0.687 12.5 8 6 2.5 2 0.687 12.5 8 1 2.35 3 0.688 12.5 8 2 2.37 3 0.691 12.6 8 3 2.37 3 0.689 12.5 8 288 4 2.45 2 0.717 13 8 5 2.45 2 0.715 13 8 6 2.45 2 0.715 13 8 1 2.7 1 0.682 12.4 8 2 2.71 1 0.682 12.4 8 3 2.7 1 0.682 12.4 8 289 4 2.85 1 0.717 13 8 5 2.84 1 0.717 13 8 6 2.88 1 0.717 13 8 1 2 4 0.612 11.1 8 2 2.01 4 0.613 11.1 8 3 2.02 4 0.614 11.2 8 290 4 1.98 4 0.603 11 8 5 1.98 4 0.605 11 8 6 1.99 4 0.604 11 8 1 1.98 4 0.605 11 8 2 1.99 4 0.606 11 8 3 1.99 4 0.605 11 8 291 4 2.01 4 0.625 11.4 8 5 2.04 4 0.621 11.3 8 6 2.04 4 0.621 11.3 8 1 1.98 4 0.569 10.4 8 2 1.99 4 0.57 10.4 8 292 3 1.98 4 0.57 10.4 8 4 2.09 4 0.594 10.8 8 5 2.08 4 0.594 10.8 8 147 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.1 4 0.594 10.8 8 1 2.51 2 0.616 11.2 8 2 2.51 2 0.615 11.2 8 3 2.51 2 0.616 11.2 8 293 4 2.47 2 0.612 11.1 8 5 2.46 2 0.611 11.1 8 6 2.48 2 0.612 11.1 8 1 2.19 3 0.662 12 8 2 2.19 3 0.662 12 8 3 2.19 3 0.664 12 8 294 4 2.19 3 0.664 12 8 5 2.18 3 0.662 12 8 6 2.18 3 0.662 12 8 1 2.58 2 0.703 12.7 8 2 2.59 2 0.704 12.7 8 3 2.58 2 0.704 12.7 8 295 4 2.58 2 0.703 12.7 8 5 2.57 2 0.706 12.8 8 6 2.59 2 0.706 12.8 8 1 1.33 4 0.559 10.2 8 2 1.33 4 0.56 10.2 8 3 1.33 4 0.559 10.2 8 296 4 1.33 4 0.559 10.2 8 5 1.33 4 0.559 10.2 8 6 1.32 4 1 1.5 4 0.554 10.1 8 2 1.47 4 0.554 10.1 8 3 1.45 4 0.527 9.6 8 297 4 1.4 4 0.527 9.6 8 5 1.4 4 0.526 9.6 8 6 1.4 4 1 1.77 4 0.541 9.8 8 2 1.77 4 0.54 9.8 8 3 1.76 4 0.557 10.1 8 298 4 1.8 4 0.559 10.2 8 5 1.81 4 0.557 10.1 8 6 1.8 4 1 2.04 4 0.67 12.2 8 299 2 2.04 4 0.669 12.2 8 148 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.04 4 0.64 11.6 8 4 1.96 4 0.64 11.6 8 5 1.96 4 0.64 11.6 8 6 1.95 4 1 1.37 4 0.617 11.2 8 2 1.36 4 0.617 11.2 8 3 1.36 4 0.616 11.2 8 300 4 1.36 4 0.616 11.2 8 5 1.36 4 0.616 11.2 8 6 1.36 4 1 1.76 4 0.672 12.2 8 2 1.76 4 0.672 12.2 8 3 1.75 4 0.677 12.3 8 301 4 1.77 4 0.678 12.3 8 5 1.77 4 0.677 12.3 8 6 1.76 4 1 2.38 3 0.637 11.4 7.9 2 2.37 3 0.637 11.4 7.9 3 2.38 3 0.636 11.4 7.9 302 4 2.36 3 0.636 11.4 7.9 5 2.35 3 0.636 11.4 7.9 6 2.35 3 1 2.11 3 0.581 10.6 8 2 2.11 3 0.581 10.6 8 3 2.1 3 0.582 10.6 8 303 4 2.11 3 0.581 10.6 8 5 2.11 3 0.581 10.6 8 6 2.11 3 1 1.99 4 0.584 10.6 8 2 1.99 4 0.586 10.7 8 3 2 4 0.583 10.6 8 304 4 1.99 4 0.583 10.6 8 5 2 4 0.583 10.6 8 6 2 4 1 1.73 4 0.594 10.8 8 2 1.72 4 0.594 10.8 8 305 3 1.73 4 0.582 10.6 8 4 1.66 4 0.579 10.5 8 5 1.65 4 0.581 10.6 8 149 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.66 4 1 1.58 4 0.64 11.6 8 2 1.59 4 0.64 11.6 8 3 1.59 4 0.593 10.8 8 306 4 1.46 4 0.591 10.7 8 5 1.43 4 0.593 10.8 8 6 1.43 4 1 1.46 4 0.584 10.6 8 2 1.46 4 0.586 10.7 8 3 1.47 4 0.589 10.7 8 307 5 1.44 4 0.588 10.7 8 6 1.44 4 1 2.1 3 0.578 10.5 8 2 2.11 3 0.578 10.5 8 3 2.11 3 0.593 10.8 8 4 2.08 4 0.592 10.8 8 308 5 2.15 3 0.592 10.8 8 6 2.15 3 1 2.3 3 0.578 10.5 8 2 2.3 3 0.579 10.5 8 3 2.3 3 0.606 11 8 4 2.4 2 0.606 11 8 309 5 2.41 2 0.606 11 8 6 2.41 2 1 2.82 1 0.6 10.9 8 2 2.81 1 0.602 11 8 3 2.82 1 0.596 10.8 8 4 2.78 1 0.594 10.8 8 310 5 2.78 1 0.594 10.8 8 6 2.79 1 1 2.7 1 0.659 12 8 2 2.7 1 0.66 12 8 3 2.69 1 0.629 11.4 8 4 2.57 2 0.629 11.4 8 311 5 2.57 2 0.627 11.4 8 6 2.56 2 1 2.27 3 0.665 12.1 8 2 2.28 3 0.664 12.1 8 312 3 2.28 3 0.664 12.1 8 150 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 4 2.28 3 0.664 12.1 8 5 2.28 3 0.664 12.1 8 6 2.26 3 1 1.62 4 0.472 8.5 8 2 1.63 4 0.472 8.5 8 3 1.63 4 0.472 8.5 8 4 1.63 4 0.472 8.5 8 313 5 1.62 4 0.472 8.5 8 6 1.63 4 1 1.58 4 0.532 9.7 8 2 1.58 4 0.532 9.7 8 3 1.58 4 0.543 9.9 8 4 1.61 4 0.543 9.9 8 314 5 1.61 4 0.543 9.9 8 6 1.62 4 1 1.92 4 0.491 8.9 8 2 1.94 4 0.491 8.9 8 3 1.94 4 0.489 8.9 8 4 1.93 4 0.489 8.9 8 315 5 1.92 4 0.491 8.9 8 6 1.93 4 1 1.67 4 0.449 8.2 8 2 1.69 4 0.448 8.1 8 3 1.67 4 0.452 8.2 8 4 1.69 4 0.45 8.2 8 316 5 1.71 4 0.45 8.2 8 6 1.7 4 0.452 8.2 8 7 1.72 4 1 1.51 4 0.491 8.9 8 2 1.5 4 0.492 8.9 8 3 1.52 4 0.497 9 8 317 4 1.53 4 0.499 9.1 8 5 1.53 4 0.499 9.1 8 6 1.53 4 1 1.74 4 0.466 8.3 7.8 2 1.74 4 0.466 8.3 7.8 318 3 1.74 4 0.461 8.2 7.8 4 1.71 4 0.46 8.2 7.8 5 1.7 4 0.46 8.2 7.8 151 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.71 4 1 2.1 4 0.529 9.6 8 2 2.1 3 0.527 9.6 8 3 2.1 3 0.532 9.7 8 319 4 2.08 4 0.527 9.6 8 5 2.09 4 0.527 9.6 8 6 2.09 4 1 1.41 4 0.632 11.5 8 2 1.42 4 0.632 11.5 8 3 1.41 4 0.634 11.5 8 320 4 1.42 4 0.632 11.5 8 5 1.41 4 0.632 11.5 8 6 1.41 4 1 1.93 4 0.526 9.6 8 2 1.93 4 0.526 9.6 8 3 1.94 4 0.517 9.4 8 321 4 1.92 4 0.516 9.4 8 5 1.92 4 0.516 9.4 8 6 1.91 4 1 2.39 3 0.608 11 8 2 2.39 3 0.606 11 8 3 2.39 3 0.594 10.8 8 322 4 2.35 3 0.593 10.8 8 5 2.35 3 0.593 10.8 8 6 2.34 3 1 2.22 3 0.626 11.4 8 2 2.22 3 0.626 11.4 8 3 2.21 3 0.614 11.2 8 323 4 2.17 3 0.613 11.1 8 5 2.17 3 0.614 11.2 8 6 2.17 3 1 2.65 1 0.622 11.3 8 2 2.66 1 0.622 11.3 8 3 2.66 1 0.61 11.1 8 324 4 2.6 1 0.609 11.1 8 5 2.6 2 0.609 11.1 8 6 2.6 2 1 2 4 0.699 12.7 8 325 2 2 4 0.699 12.7 8 152 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2 4 0.661 12 8 4 1.91 4 0.66 12 8 5 1.9 4 0.66 12 8 6 1.91 4 1 2.24 3 0.61 11.1 8 2 2.24 3 0.611 11.1 8 3 2.24 3 0.61 11.1 8 326 4 2.24 3 0.612 11.1 8 5 2.24 3 0.61 11.1 8 6 2.23 3 1 1.39 4 0.568 10.3 8 2 1.38 4 0.567 10.3 8 3 1.39 4 0.555 10.1 8 327 4 1.36 4 0.554 10.1 8 5 1.35 4 0.555 10.1 8 6 1.37 4 1 1.47 4 0.564 10.3 8 2 1.46 4 0.564 10.3 8 3 1.47 4 0.563 10.2 8 328 4 1.47 4 0.564 10.3 8 5 1.46 4 0.563 10.2 8 6 1.46 4 1 2.12 3 0.525 9.6 8 2 2.11 3 0.525 9.6 8 3 2.12 3 0.526 9.6 8 329 4 2.12 3 0.525 9.6 8 5 2.11 3 0.525 9.6 8 6 2.12 3 1 1.95 4 0.523 9.5 8 2 1.95 4 0.523 9.5 8 3 1.95 4 0.542 9.8 8 330 4 2.03 4 0.542 9.8 8 5 2.04 4 0.541 9.8 8 6 2.02 4 1 1.58 4 0.492 8.9 8 2 1.58 4 0.492 8.9 8 331 3 1.59 4 0.507 9.2 8 4 1.63 4 0.508 9.2 8 5 1.64 4 0.507 9.2 8 153 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 1.63 4 1 2.04 4 0.512 9.3 8 2 2.05 4 0.512 9.3 8 3 2.05 4 0.524 9.5 8 332 4 2.12 3 0.523 9.5 8 5 2.11 3 0.523 9.5 8 6 2.12 3 1 1.81 4 0.5 9.1 8 2 1.81 4 0.5 9.1 8 3 1.82 4 0.517 9.4 8 333 4 1.9 4 0.519 9.4 8 5 1.9 4 0.517 9.4 8 6 1.91 4 1 1.82 4 0.497 9 8 2 1.81 4 0.498 9.1 8 3 1.83 4 0.477 8.7 8 334 4 1.74 4 0.478 8.7 8 5 1.73 4 0.477 8.7 8 6 1.74 4 1 2.13 3 0.569 10.4 8 2 2.11 3 0.57 10.4 8 3 2.12 3 0.573 10.4 8 335 4 2.18 3 0.573 10.4 8 5 2.17 3 0.57 10.4 8 6 2.15 3 1 1.82 4 0.598 10.9 8 2 1.81 4 0.598 10.9 8 3 1.82 4 0.596 10.8 8 336 4 1.75 4 0.598 10.9 8 5 1.82 4 0.6 10.9 8 6 1.82 4 1 1.82 4 0.643 11.7 8 2 1.81 4 0.641 11.7 8 3 1.81 4 0.648 11.8 8 337 4 1.82 4 0.645 11.7 8 5 1.81 4 0.646 11.8 8 6 1.81 4 1 2.48 2 0.61 11.1 8 338 2 2.47 2 0.611 11.1 8 154 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 3 2.48 2 0.601 10.9 8 4 2.51 2 0.601 10.9 8 5 2.51 2 0.601 10.9 8 6 2.51 2 1 2.5 2 0.6 10.9 8 2 2.51 2 0.601 10.9 8 3 2.5 2 0.6 10.9 8 339 4 2.5 2 0.601 10.9 8 5 2.51 2 0.601 10.9 8 6 2.51 2 1 2.21 3 0.616 11.2 8 2 2.21 3 0.616 11.2 8 3 2.22 3 0.626 11.4 8 340 4 2.18 3 0.626 11.4 8 5 2.2 3 0.625 11.3 8 6 2.19 3 1 2.39 3 0.552 10 8 2 2.39 3 0.551 10 8 3 2.4 3 0.543 9.9 8 341 4 2.37 3 0.542 9.8 8 5 2.38 3 0.543 9.9 8 6 2.38 3 1 2.15 3 0.532 9.7 8 2 2.17 3 0.532 9.7 8 3 2.17 3 0.522 9.5 8 342 4 2.11 3 0.521 9.5 8 5 2.12 3 0.521 9.5 8 6 2.12 3 1 2.54 2 0.568 10.1 7.8 2 2.54 2 0.568 10.1 7.8 3 2.52 2 0.574 10.2 7.8 343 4 2.59 2 0.574 10.2 7.8 5 2.6 1 0.574 10.2 7.8 6 2.6 1 1 1.98 4 0.519 9.2 7.8 2 1.97 4 0.521 9.2 7.8 344 3 1.99 4 0.536 9.5 7.8 4 2.08 4 0.538 9.5 7.8 5 2.07 4 0.536 9.5 7.8 155 Table 6.5 (Cont’d) Sample group G Weight Length Sub Samples MOE SG number RADE [lbs] [ft] 6 2.07 4 1 1.98 4 0.544 9.6 7.8 2 1.99 4 0.544 9.6 7.8 3 1.99 4 0.544 9.6 7.8 345 4 1.98 4 0.544 9.6 7.8 5 1.99 4 0.544 9.6 7.8 1.99 4 0.544 9.6 7.8 6 156 APPENDIX F MFL and MOR values of 30 samples with 40% GLSL 157 Extension Maximum Modulus (Young's Specimen Width Thickness at SR NO. Flexure MOR (psi) Flexure stress 2 label (mm) (mm) Max.load load (lbf) mm - 3 mm) (psi) (mm) GLU 40% of salvaged 1 81.28 165.1 13,831.14 38.28 2,455.23 25,167.52 lumber samples -1 GLU 40% of salvaged 2 81.28 165.1 13,737.93 31.14 2,438.69 ----- lumber samples -2 GLU 40% of salvaged 3 81.28 165.1 12,264.25 42.41 2,177.09 11,863.28 lumber samples -3 GLU 40% of salvaged 4 81.28 165.1 12,219.87 27.68 2,169.21 ----- lumber samples -4 GLU 40% of salvaged 5 81.28 165.1 12,663.75 44.37 2,248.00 ----- lumber samples -5 GLU 40% of salvaged 6 81.28 165.1 10,821.68 37.32 1,921.01 ----- lumber samples -6 GLU 40% of salvaged 7 81.28 165.1 15,038.48 32.18 2,669.55 49,104.59 lumber samples -7a GLU 40% of salvaged 8 81.28 165.1 12,521.70 27.28 2,222.79 42,459.98 lumber samples -8a GLU 40% of salvaged 9 81.28 165.1 13,231.90 37.79 2,348.86 32,618.63 lumber samples -9 GLU 40% of salvaged 10 81.28 165.1 12,295.33 41.49 2,182.60 16,253.94 lumber samples -10 GLU 40% of salvaged 11 81.28 165.1 13,120.94 37.51 2,329.16 36,656.09 lumber samples -11 GLU 40% of salvaged 12 81.28 165.1 12,348.60 35.55 2,192.06 20,267.13 lumber samples -12 GLU 40% of salvaged 13 81.28 165.1 14,647.86 44.25 2,600.21 28,871.29 lumber samples -13 GLU 40% of salvaged 14 81.28 165.1 16,982.65 36.69 3,014.67 30,165.05 lumber samples -14 Table 6.6 MFL and MOR values of 40% GLSL 158 Table 6.6 (Cont’d) Extension Maximum Modulus (Young's Specimen Width Thickness at SR NO. Flexure MOR (psi) Flexure stress 2 label (mm) (mm) Max.load load (lbf) mm - 3 mm) (psi) (mm) GLU 40% of salvaged 15 81.28 165.1 12,712.56 30.21 2,256.67 35,301.34 lumber samples -15 GLU 40% of salvaged 16 81.28 165.1 13,316.23 34.76 2,363.83 47,014.84 lumber samples -16 GLU 40% of salvaged 17 81.28 165.1 11,807.08 32.92 2,095.93 27,924.39 lumber samples -17 GLU 40% of salvaged 18 81.28 165.1 12,384.09 37.89 2,198.36 40,085.28 lumber samples -18 GLU 40% of salvaged 19 81.28 165.1 14,678.93 38.81 2,605.73 44,588.70 lumber samples -19 GLU 40% of salvaged 20 81.28 165.1 12,552.77 31.24 2,228.30 37,251.85 lumber samples -20 GLU 40% of salvaged 21 81.28 165.1 12,588.28 41.99 2,234.61 35,098.21 lumber samples -21 GLU 40% of salvaged 22 81.28 165.1 15,189.39 44.96 2,696.34 35,046.22 lumber samples -22 GLU 40% of salvaged 23 81.28 165.1 13,564.80 38.53 2,407.95 11,864.54 lumber samples -23 GLU 40% of salvaged 24 81.28 165.1 12,876.80 32.41 2,285.82 33,770.04 lumber samples -24 GLU 40% of salvaged 25 81.28 165.1 11,274.42 40.3 2,001.38 32,174.43 lumber samples -25 GLU 40% of salvaged 26 81.28 165.1 13,751.24 32.27 2,441.05 38,789.92 lumber samples -26 GLU 40% of salvaged 27 81.28 165.1 10,639.68 40.83 1,888.70 23,878.44 lumber samples -27 GLU 40% of salvaged 28 81.28 165.1 10,724.01 23.64 1,903.67 18,247.66 lumber samples -28 GLU 40% of 29 81.28 165.1 13,143.12 22.09 2,333.10 24,852.85 salvaged 159 Table 6.6 (Cont’d) Extension Maximum Modulus (Young's Specimen Width Thickness at SR NO. Flexure MOR (psi) Flexure stress 2 label (mm) (mm) Max.load load (lbf) mm - 3 mm) (psi) (mm) lumber samples 21 30 GLU V3-22 81.28 165.1 13,267.42 39.73 2,355.16 18,299.38 160 APPENDIX G MFL and MOR values of 30 samples with 60% GLSL 161 Modulus Extension Maximum (Young's Width Thickness at SR NO. Specimen label Flexure load MOR (psi) Flexure stress 2 (mm) (mm) Max.load (lbf) mm - 3 mm) (mm) (psi) GLU 60% of 1 salvaged lumber 81.28 165.1 7,408.28 10.66 1,315.98 41,530.16 samples 1 GLU 60% of 2 salvaged lumber 81.28 165.1 13,356.13 25.52 2,370.92 29,514.55 samples -2 GLU 60% of 3 salvaged lumber 81.28 165.1 13,441.90 35.79 2,348.86 32,688.63 samples -3 GLU 60% of 4 salvaged lumber 81.28 165.1 19,653.65 41.97 3,410.23 33,171.34 samples -4 GLU 60% of 5 salvaged lumber 81.28 165.1 10,058.19 33.14 1,785.48 20,056.53 samples -5 GLU 60% of 6 salvaged lumber 81.28 165.1 13,789.24 34.69 2,145.67 27,987.34 samples -6 GLU 60% of 7 salvaged lumber 81.28 165.1 11,334.59 33.88 2,178.71 43,083.21 samples -7 GLU 60% of 8 salvaged lumber 81.28 165.1 17,620.52 30.16 3,233.34 22,150.34 samples 8 GLU 60% of 9 salvaged lumber 81.28 165.1 13,706.84 40.86 2,433.17 25,030.11 samples 9 GLU 60% of 10 salvaged lumber 81.28 165.1 13,045.48 34.75 2,315.77 3,635.89 samples -10 GLU 60% of 11 salvaged lumber 81.28 165.1 19,361.81 44.68 3,437.01 34,889.79 samples -11 GLU 60% of 12 salvaged lumber 81.28 165.1 12,748.07 38.31 2,262.97 41,959.63 samples -12 GLU 60% of 13 salvaged lumber 81.28 165.1 13,089.86 28.33 2,323.64 21,362.41 samples -13 GLU 60% of 14 salvaged lumber 81.28 165.1 14,989.65 40.01 2,660.88 ----- samples -14 GLU 60% of 15 salvaged lumber 81.28 165.1 14,088.57 40.2 2,500.93 ----- samples -15 GLU 60% of 16 salvaged lumber 81.28 165.1 17,666.21 46.33 3,136.01 ----- samples -16 GLU 60% of 17 salvaged lumber 81.28 165.1 10,111.46 26.24 1,794.93 35,534.36 samples -17 GLU 60% of 18 salvaged lumber 81.28 165.1 12,583.85 33.43 2,233.82 32,867.77 samples -18 Table 6.7 MFL values of 60% of GLSL 162 Table 6.7 (Cont’d) Modulus Extension Maximum (Young's Width Thickness at SR NO. Specimen label Flexure load MOR (psi) Flexure stress 2 (mm) (mm) Max.load (lbf) mm - 3 mm) (mm) (psi) GLU 60% of 19 salvaged lumber 81.28 165.1 12,441.81 31.65 2,208.60 7,376.61 samples -19 GLU 60% of 20 salvaged lumber 81.28 165.1 13,023.28 35.03 2,311.82 37,410.36 samples -20 GLU 60% of 21 salvaged lumber 81.28 165.1 12,650.43 36.54 2,245.64 26,337.79 samples -21 GLU 60% of 22 salvaged lumber 81.28 165.1 12,530.59 34.06 2,224.36 33,936.41 samples -22 GLU 60% of 23 salvaged lumber 81.28 165.1 15,704.28 42.2 2,787.74 42,975.20 samples -23 GLU 60% of 24 salvaged lumber 81.28 165.1 17,213.45 34.68 3,055.64 22,275.60 samples -24 GLU 60% of 25 salvaged lumber 81.28 165.1 14,448.13 37.92 2,564.76 2,465.52 samples -25 GLU 60% of 26 salvaged lumber 81.28 165.1 11,274.42 36.17 2,001.38 30,674.15 samples -26 GLU 60% of 27 salvaged lumber 81.28 165.1 13,356.20 35.29 2,370.92 41,680.43 samples -27 GLU 60% of 28 salvaged lumber 81.28 165.1 12,836.85 35.44 2,278.73 38,142.49 samples -28 GLU 60% of 29 salvaged lumber 81.28 165.1 14,483.62 44.53 2,571.06 39,829.63 samples -29 GLU 60% of 30 salvaged lumber 81.28 165.1 18,296.51 42.82 3,247.90 55,242.18 samples -30 163 APPENDIX H MFL and MOR values of 30 control samples 164 Extension Modulus Maximum Specimen Width Thickness at MOR (Young's Flexure SR NO. Flexure label (mm) (mm) Max.load (psi) stress 2 mm - 3 load (lbf) (mm) mm)(psi) 1 GLU C-1 81.28 165.1 13,973.16 44.27 2,480.44 38,856.18 2 GLU C-2 81.28 165.1 11,633.95 32.27 2,065.20 40,024.09 3 GLU C-3 81.28 165.1 19,210.88 49.61 3,410.22 48,851.52 4 GLU C-4 81.28 165.1 16,396.73 44.86 2,910.66 52,556.35 5 GLU C-5 81.28 165.1 13,547.05 31.34 2,404.80 38,007.41 6 GLU C-6 81.28 165.1 12,770.28 31.58 2,266.91 42,682.83 7 GLU C-7 81.28 165.1 12,233.18 41.21 2,171.57 45,831.12 8 GLU C-8 81.28 165.1 14,403.72 44.04 2,556.87 41,810.19 9 GLU C-9 81.28 165.1 14,812.09 50.93 2,629.36 14,814.45 10 GLU C-10 81.28 165.1 14,141.84 46.86 2,510.39 51,548.98 11 GLU C-11 81.28 165.1 14,341.60 48.68 2,545.85 12,493.60 12 GLU C-12 81.28 165.1 16,920.50 32.17 3,003.64 29,050.53 13 GLU C-13 81.28 165.1 16,228.05 48.23 2,880.72 32,398.16 14 GLU C-14 81.28 165.1 15,335.86 52.6 2,722.34 11,016.72 15 GLU C-15 81.28 165.1 14,261.68 39.75 2,531.66 12,160.29 16 GLU C-16 81.28 165.1 14,860.92 39.73 2,638.03 3,486.19 17 GLU C-17 81.28 165.1 10,808.34 36.72 1,918.64 15,183.46 18 GLU C-18 81.28 165.1 16,236.93 49.99 2,882.30 46,030.36 19 GLU C-19 81.28 165.1 15,238.22 50.69 2,705.01 38,303.16 20 GLU C-20 81.28 165.1 15,304.80 33.08 2,716.83 46,398.41 21 GLU C-21 81.28 165.1 11,540.74 35.28 2,048.65 41,780.91 22 GLU C-22 81.28 165.1 11,731.61 45.54 2,082.53 11,824.33 23 GLU C-23 81.28 165.1 13,307.37 44.08 2,362.25 11,863.69 24 GLU C-24 81.28 165.1 17,355.49 43.71 3,080.86 12,160.29 25 GLU C-25 81.28 165.1 14,599.03 53.26 2,591.54 12,428.64 26 GLU C-26 81.28 165.1 16,343.46 41.76 2,901.21 22,304.56 27 GLU C-27 81.28 165.1 14,550.20 46.23 2,582.88 34,232.24 28 GLU C-28 81.28 165.1 13,391.69 53 2,377.22 37,632.86 29 GLU C-29 81.28 165.1 16,307.94 52.25 2,894.90 35,553.25 30 GLU C-30 81.28 165.1 14,141.84 46.86 2,510.39 51,548.98 Table 6.7 MFL and MOR values of 30 Control samples 165 REFERENCES 166 REFERENCES American Society for Testing and Materials (ASTM). 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