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Title: Atomic simulation on chemical-mechanical coupled deformations in complex nano structures
Creator: Liu, Jialin (Graduate of Michigan State University)
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "Nano-structured materials often exhibit very different mechanical properties comparing with their bulk counterpart and are more sensitive and active to chemical interactions with the environments due to the large surface-to-volume ratio. In this thesis, predictive modeling techniques including density functional theory (DFT) and reactive molecular dynamics method (MD) are designed and applied to understand the deformation mechanisms of complex nano-structured material and describe chemical...
Show more"Nano-structured materials often exhibit very different mechanical properties comparing with their bulk counterpart and are more sensitive and active to chemical interactions with the environments due to the large surface-to-volume ratio. In this thesis, predictive modeling techniques including density functional theory (DFT) and reactive molecular dynamics method (MD) are designed and applied to understand the deformation mechanisms of complex nano-structured material and describe chemical-mechanical coupled interactions. Three technologically important materials are investigated, to understanding the high strain rate toughening mechanism in nacre, predicting the formation and fracture of aluminum oxide bifilms in aluminum castings, and revealing the lithium growth morphology as a function of oxygen partial pressure. For nacre, its hierarchical structure and toughening mechanisms have inspired many materials developments. Recently, a new toughening mechanism, deformation twins was observed in nacre after dynamic loading (103 s--1). The deformation twinning tendency and the competition between fracture and deformation twinning were revealed by DFT calculations. We discovered that the ratio of the unstable and the stable stacking fault energy in aragonite is hitherto the highest in a broad range of metallic and oxide materials and the bonding nature for this high ratio is explained. Both aluminum and lithium have high oxygen affinity. Their interaction with the oxygen environment affects the mechanical properties and vice versa. During casting of aluminum, it has long been proposed that the entrapped alumina "bifilms" are detrimental to the fatigue properties of the cast product. However, its properties have never been measured due to experimental limitations. Therefore, a ReaxFF based MD protocol was designed to simulate aging, folding, and fracture of oxide bifilms. The predicted fracture energy, fracture location, and differences between old and young oxides are explained a series of experimental observations. To illustrate the Li-growth mechanism in a solid-state-battery testing platform, we modeled the morphology of Li nano-structure growth in oxygen environment via ReaxFF-based MD. The simulation revealed that the competition of the Li growth rate and oxidation rate leads to the sphere-nanowire-sphere morphology transition with increasing oxygen partial pressure. Understanding the impact of chemical reaction on Li dendrite growth mechanisms and morphology evolution provided insights on the formation of the solid electrolyte interface (SEI) layer in a Li-ion battery. Finally, a shortcoming of the current charge transfer scheme (qEq) used in the ReaxFF MD simulation is discussed. It is demonstrated that qEq method will lead to overductile ionic materials in the MD simulation. A new Force field method and new parameters are proposed to mitigate this problem."--Pages ii-iii.
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Title: Agronomic management of corn using seasonal climate predictions, remote sensing and crop simulation models
Creator: Jha, Prakash Kumar
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Management decisions in corn (Zea mays mays L) production are usually based on specific growth stages. However, because of climate and weather variability, phenological stages vary from season to season across geographic locations. This variability in growth and phenology entails risks and quantifying it will help in managing climate related risks. Crop simulation models can play a significant role in minimizing these risks through designing management strategies; however, they are not always...
Show moreManagement decisions in corn (Zea mays mays L) production are usually based on specific growth stages. However, because of climate and weather variability, phenological stages vary from season to season across geographic locations. This variability in growth and phenology entails risks and quantifying it will help in managing climate related risks. Crop simulation models can play a significant role in minimizing these risks through designing management strategies; however, they are not always accurate. Remote sensing observations and climate predictions can improve the accuracy in managing time bound climate-sensitive decisions at larger spatiotemporal scale. However, there is also a disconnect between climate forecasts and crop models. The unavailability of downscaling tool that can downscale rainfall and temperature forecasts simultaneously make this task more challenging. To address these knowledge gaps, this dissertation consists of three studies focused on interdisciplinary approaches to agronomic management of corn.In the first study, we calibrated and validated genetic coefficients of CERES-Maize using field data from the Michigan corn performance trials. Multiple methods of estimating genetic coefficients GENCALC (Genotype Coefficient Calculator), GLUE (Generalized Likelihood Uncertainty Estimate), and NMCGA (Noisy Monte Carlo Genetic Algorithm) were evaluated and ensembled to estimate more reliable genetic coefficients. The calibrations were done under irrigated conditions and validation under rainfed conditions. The results suggested that ensembled genetic coefficients performed best among all, with d-index of 0.94 and 0.96 in calibration and validation for anthesis and maturity dates, and yield.In the second study, simulated growth stages from the calibrated crop model were used to develop site-specific crop coefficients (kc) using ensembled ET and reference ET from the nearest weather station. ET from multiple models were ensembled and validated with the measured ET from eddy-covariance flux towers for 2010 - 2017. Results suggest that the ensembled ET performed best among all ET models used, with highest d-index of 0.94. Likewise, the performance of the newly derived kc-curve was compared with FAO-kc curve using a soil water balance model. Then, the derived region-specific Kc-curve was used to design irrigation scheduling and results suggest that it performed better than FAO Kc-curve in minimizing the amount irrigation while maintaining a prescribed allowable water stress.The third study used the calibrated crop model to simulate anthesis using downscaled seasonal climate forecasts. The predicted anthesis and downscaled seasonal climate forecasts were used to develop risk analysis model for ear rot disease management in corn. In this study an innovative downscaling tool, called FResamplerPT, was introduced to downscale rainfall and temperature simultaneously. The results suggest that temperature and relative humidity are better predictors (combined) as compared to temperature and rainfall (combined). With this risk analysis model, growers can evaluate and assess the future climatic conditions in the season before planting the crops. The seasonal climate information with the lead-time of 3 months can help growers to prepare integrated management strategies for ear rot disease management in maize.
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Title: Experiments and model development of a dual mode, turbulent jet ignition engine
Creator: Tolou, Sedigheh
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "The number of vehicles powered by a source of energy other than traditional petroleum fuels will increase as time passes. However, based on current predictions, vehicles run on liquid fuels will be the major source of transportation for decades to come. Advanced combustion technologies can improve fuel economy of internal combustion (IC) engines and reduce exhaust emissions. The Dual Mode, Turbulent Jet Ignition (DM-TJI) system is an advanced, distributed combustion technology which can...
Show more"The number of vehicles powered by a source of energy other than traditional petroleum fuels will increase as time passes. However, based on current predictions, vehicles run on liquid fuels will be the major source of transportation for decades to come. Advanced combustion technologies can improve fuel economy of internal combustion (IC) engines and reduce exhaust emissions. The Dual Mode, Turbulent Jet Ignition (DM-TJI) system is an advanced, distributed combustion technology which can achieve high diesel-like thermal efficiencies at medium to high loads and potentially exceed diesel efficiencies at low-load operating conditions. The DM-TJI strategy extends the mixture flammability limits by igniting lean and/or highly dilute mixtures, leading to low-temperature combustion (LTC) modes in spark ignition (SI) engines. A novel, reduced order, and physics-based model was developed to predict the behavior of a DM-TJI engine with a pre-chamber air valve assembly. The engine model developed was calibrated based on experimental data from a Prototype II DM-TJI engine. This engine was designed, built, and tested at the MSU Energy and Automotive Research Laboratory (EARL). A predictive, generalized model was introduced to obtain a complete engine fuel map for the DM-TJI engine. The engine fuel map was generated in a four-cylinder boosted configuration under highly dilute conditions, up to 40% external exhaust gas recirculation (EGR). A vehicle simulation was then performed to further explore fuel economy gains using the fuel map generated for the DM-TJI engine. The DM-TJI engine was embodied in an industry-based vehicle to examine the behavior of the engine over the U.S. Environmental Protection Agency (EPA) driving schedules. The results obtained from the drive cycle analysis of the DM-TJI engine in an industry-based vehicle were compared to the results of the same vehicle with its original engine. The vehicle equipped with the DM-TJI system was observed to benefit from 103033% improvement in fuel economy and 103031% reduction in CO2 emission over the EPA combined city/high driving schedules. Potential improvements were discussed, as these results of the drive cycle analysis are the first-ever reported results for a DM-TJI engine embodied in an industry-based vehicle. The resulting fuel economy and CO2 emission were used to conduct a cost-benefit analysis of a DM-TJI engine. The cost-benefit analysis followed the economic and key inputs used by the U.S. EPA in a Proposed Determination prepared by that agency. The outcomes of the cost-benefit analysis for the vehicle equipped with the DM-TJI system were reported in comparison with the same vehicle with its base engine. The extra costs of a DM-TJI engine were observed to be compensated over the first three years of the vehicle's life time. The results projected maximum savings of approximately 2400 in 2019 dollars. This includes the lifetime-discounted present value of the net benefits of the DM-TJI technology, compared to the base engine examined. In this dollar saving estimate, the societal effects of CO2 emission were calculated based on values by the interagency working group (IWG) at 3% discount rate."--Pages ii-iii.
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Title: Monte-Carlo simulations of the (d,²He) reaction in inverse kinematics
Creator: Carls, Alexander B.
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Charge-exchange reactions offer an indirect method for the testing of theoretical models for Gamow-Teller strengths that are used to calculate electron-capture rates on medium-heavy nuclei, which play important roles in astrophysical phenomena. Many of the relevant nuclei are unstable. However, a good general probe for performing charge-exchange reactions in inverse kinematics in the (n,p) reaction has not yet been established. The (d,2He) reaction in inverse kinematics is being developed as...
Show moreCharge-exchange reactions offer an indirect method for the testing of theoretical models for Gamow-Teller strengths that are used to calculate electron-capture rates on medium-heavy nuclei, which play important roles in astrophysical phenomena. Many of the relevant nuclei are unstable. However, a good general probe for performing charge-exchange reactions in inverse kinematics in the (n,p) reaction has not yet been established. The (d,2He) reaction in inverse kinematics is being developed as a potential candidate for this probe. This method uses the Active-Target Time Projection Chamber (AT-TPC) to detect the two protons from the unbound 2He system, and the S800 spectrograph to detect the heavy recoil. The feasibility of this method is demonstrated through Monte-Carlo simulations. The ATTPCROOTv2 code is the framework which allows for simulation of reactions within the AT-TPC as well as digitization of the results in the pad planes for realistic simulated data. The analysis performed on this data using the ATTPCROOTv2 code shows the techniques that can be done in experiment to track the scattered protons through the detector using Random Sampling Consensus (RANSAC) algorithms.
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Title: Improving the representation of irrigation and groundwater in global land surface models to advance the understanding of hydrology-human-climate interactions
Creator: Felfelani, Farshid
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Hydrological models and satellite observations have been widely used to study the variations in the Earth's hydrology and climate over multitude of scales, especially in relation to natural and human-induced changes in the terrestrial water cycle. Yet, both satellite products and model results suffer from inherent uncertainties, calling for the need to improve the representation of critical processes in the models and to make a combined use of satellite data and models to examine the...
Show moreHydrological models and satellite observations have been widely used to study the variations in the Earth's hydrology and climate over multitude of scales, especially in relation to natural and human-induced changes in the terrestrial water cycle. Yet, both satellite products and model results suffer from inherent uncertainties, calling for the need to improve the representation of critical processes in the models and to make a combined use of satellite data and models to examine the variations in the terrestrial hydrology. The representation of irrigation and groundwater-two major hydrologic processes with complex reciprocal interplay-in large-scale hydrological models is rather poorly parameterized and heavily simplified, hindering our ability to realistically simulate groundwater-human-climate interactions. This dissertation advances the physical basis for irrigation and groundwater parameterizations in global land surface models, leveraging the potential of emerging satellite data (i.e., data from GRACE and SMAP satellite missions) toward a more realistic quantification of the impacts of human activities on the hydrological cycle. A comprehensive global analysis is developed to examine the historical spatial patterns and long-term temporal response, i.e., the terrestrial water storage (TWS), of two models to natural and human-induced drivers. Human-induced changes in TWS are then quantified in the highly managed global regions to identify the uncertainties arising from a simplistic representation of irrigation and groundwater. The potential of improving irrigation representation in the Community Land Model version 4.5 (CLM4.5) is then investigated by assimilating the soil moisture data from SMAP satellite mission using 1-D Kalman Filter assimilation approach. The new irrigation scheme is then tested over the heavily irrigated central U.S. Next, the existing groundwater module of CLM5 is broadly evaluated over conterminous U.S. and a new prognostic groundwater module is implemented in CLM5 to account for lateral groundwater flow, pumping, and conjunctive water use for irrigation. In particular, an explicit parameterization for the steady-state well equation is introduced for the first time in large-scale hydrological modeling. Finally, the impacts of climate change on global TWS variabilities and the implications on sea level change are examined for the entire 21st century using multi-model hydrological simulations. The key findings and conclusions from the aforementioned multi-scale analysis and model developments are: (1) in terms of TWS, notable differences exist not only between simulations of hydrological models and GRACE but also among different GRACE products, therefore, TWS variations from a single model cannot be reliably used for global analyses; (2) these differences significantly increase in projections of TWS under climate change, however, models agree in sign of change for most global areas; (3) TWS is expected to decline in many regions in southern hemisphere, but increase in northern high latitudes, projected to accelerate sea level rise by the mid- and late-21st century; (4) constraining the target soil moisture in CLM4.5 using SMAP data assimilation with 1-D Kalman Filter reduces the bias in the simulated irrigation water by up to 60% on average, improving irrigation and soil moisture simulations in CLM4.5; (5) the new groundwater model significantly improves the simulation of groundwater level change and promisingly captures most of the hotspots of groundwater depletion across the U.S. overexploited aquifers; and (6) the simulation with the lateral groundwater flow substantially enhances the TWS trends relative to the default CLM5. These results and findings could provide a basis for improved large-scale irrigation and groundwater modeling and improve our understanding of hydrology-human-climate interactions.
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Title: Investigating the impact of manmade reservoirs on large-scale hydrology and water resources using high-resolution modeling
Creator: Shin, Sanghoon
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Manmade reservoirs are important components of the terrestrial hydrologic system. Dam installments fragment river systems, and reservoir operations alter flow regimes. The total storage capacity of existing global reservoirs is large enough to hold one sixth of annual continental discharge to global oceans. Due to growing energy demands, hundreds of large dams are being built and planned around the world, especially in the developing countries. Therefore, there is an urgent need to develop a...
Show moreManmade reservoirs are important components of the terrestrial hydrologic system. Dam installments fragment river systems, and reservoir operations alter flow regimes. The total storage capacity of existing global reservoirs is large enough to hold one sixth of annual continental discharge to global oceans. Due to growing energy demands, hundreds of large dams are being built and planned around the world, especially in the developing countries. Therefore, there is an urgent need to develop a better understanding of the impact of the existing and new dams on hydrological, ecological, agricultural, and socio-economic systems. Owing to increasing computational power and needs to understand and simulate processes in small-scale, hydrological models are advancing towards hyper-resolution global hydrological models. One of benefits of the increased spatial resolution is that the dynamics of surface water inundation over natural river-floodplain systems and manmade reservoirs can be explicitly represented; however, existing global models are not capable of simulating the river-floodplain-reservoir inundation dynamics in an integrated manner. This dissertation addresses this important standing issue by developing a high-resolution, continental-scale model to simulate the spatial and temporal dynamics of reservoir storage and release, thus paving pathways toward hyper-resolution surface water modeling in continental- to global-scale hydrological and climate models. The newly developed model is applied to simulate reservoirs within the contiguous United States (CONUS) and the Mekong River Basin (MRB) in Southeast Asia. With respect to the model development, the following advances are made over the previous global reservoir modeling studies: (1) an existing algorithm for reservoir operation is improved by conducting analytical analysis and numerical experiments and by introducing new calibration features for reservoir operation; (2) the spatial extent and its seasonal dynamics of reservoirs are explicitly simulated and reservoirs are treated as an integral part of river-floodplain routing, thus reservoir storage is no longer isolated from river and floodplain storages; and (3) a novel approach for processing and integrating high-resolution digital elevation models (DEMs) in river-floodplain-reservoir routing is introduced. The newly developed reservoir scheme is integrated within the river-floodplain routing scheme of a continental hydrological model, LEAF-Hydro-Flood, which is set for the CONUS, where abundant data are available for model validation. Then, the reservoir scheme is integrated into a global hydrodynamics model, CaMa-Flood, to investigate the historical impact of manmade reservoirs in the MRB that is experiencing an unprecedented boom in hydropower dam construction. Using the new scheme, the role of flood dynamics in modulating the hydrology of the MRB and the potential impact of flow regulation by the dams on the inundation dynamics are investigated. The significance of hydrologic effect of increasing dams is compared with that of climate variability. The fully coupled river-reservoir-floodplain storage simulation approach presented in this dissertation provides an advancement in hydrological modeling in terms of the representation of surface water dynamics, which is indispensable for better attribution of the observed changes in the water cycle, prediction of changes in water resources, and the understanding of the continually changing environmental and ecological systems.
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Title: Computational modeling of cardiac mechanics : microstructual modeling & pulmonary arterial hypertension
Creator: Xi, Ce
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Heart diseases, which approximately account for 31% of all human mortality every year, are the leading cause of death worldwide. Computational cardiac models have gained increasing popularity and become an indispensable and powerful tool in elucidating the pathological process of different heart diseases. They can be used to estimate important physiological and clinically relevant quantities that are difficult to directly measure in experiments. The broad goals of this thesis were to develop...
Show moreHeart diseases, which approximately account for 31% of all human mortality every year, are the leading cause of death worldwide. Computational cardiac models have gained increasing popularity and become an indispensable and powerful tool in elucidating the pathological process of different heart diseases. They can be used to estimate important physiological and clinically relevant quantities that are difficult to directly measure in experiments. The broad goals of this thesis were to develop 1) a microstructure-based constitutive model of the heart and 2) patient-specific computational models that would ultimately help medical scientists to diagnose and treat heart diseases.Heart diseases such as heart failure with preserved ejection fraction (HFpEF) are characterized by abnormalities of ventricular function that can be attributed to, changes in geometry, impaired myocyte (LV) relaxation, cardiac fibrosis and myocyte passive stiffening. Understanding how LV filling is affected by each of the many microstructural pathological features in heart diseases is very important and may help in the development of appropriate treatments. To address this need, we have developed and validated a microstructure-based computational model of the myocardium to investigate the role of tissue constituents and their ultrastructure in affecting the heart function. The model predicted that the LV filling function is sensitive to the collagen ultrastructure and the load taken up by the tissue constituents varies depending on the LV transmural location. This finding may have implications in the development of new pharmaceutical treatments targeting individual cardiac tissue constituents to normalize LV filling function in HFpEF.Pulmonary arterial hypertension (PAH) is a life-threatening disease characterized by elevated pulmonary artery pressure (PAP) and pulmonary artery vascular resistance, with limited survival rate and can affect patients of all ages. The increased pressure or afterload in the right ventricle (RV) can result in pathological changes in RV mechanics, which are currently not well-understood. To FB01ll this void, we have developed patient-specific computational models to investigate effects of PAH on ventricular mechanics. SpeciFB01cally, we have quantified regional ventricular myoFB01ber stress, myoFB01ber strain, contractility, and passive tissue stiffness in PAH patients, and compare them to those found in age- and gender-matched normal controls. Our results showed that RV longitudinal, circumferential and radial strain were depressed in PAH patients compared with controls; RV passive stiffness increased progressively with the degree of remodeling as indexed by the RV and LV end-diastolic volume ratio (RVEDV/LVEDV); Peak contractility of the RV was found to be strongly correlated, and had an inverse relationship with RVEDV/LVEDV. These results provide the mechanical basis of using RVEDV/LVEDV as a clinical index for delineating disease severity and estimating RVFW contractility in PAH patients.
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Title: Regional climate response to land use and land cover change in contiguous United States
Creator: Nikolić, Jovanka
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Future land use and land cover (LULC) pattern in the Contiguous United States (CONUS) is expected to be significantly different from that of the present, and as an important surface forcing for earth's climate system, the potential changes in LULC will contribute to climate change at all scales (local, regional to global). While numerous studies have examined how the earth's climate will respond to the anthropogenic increase of greenhouse gas concentrations in the earth's atmosphere, this...
Show moreFuture land use and land cover (LULC) pattern in the Contiguous United States (CONUS) is expected to be significantly different from that of the present, and as an important surface forcing for earth's climate system, the potential changes in LULC will contribute to climate change at all scales (local, regional to global). While numerous studies have examined how the earth's climate will respond to the anthropogenic increase of greenhouse gas concentrations in the earth's atmosphere, this research aims to quantify the response of several climate variables to the expected LULC change in the CONUS using simulations from a regional climate model. The research is composed of three individual studies. The first study assesses the sensitivity of simulated low-level jet (LLJ) characteristics on changes in LULC pattern. As a prominent weather and climate process responsible for transport of moisture from the Gulf of Mexico northward into central CONUS, LLJ plays an important role in the hydrological cycle and wind energy generation over the Great Plains. Therefore, it is important to quantify the potential changes in jet characteristics, such as jet speed, height and frequency, under the influence of LULC change. The second study investigates the impact of LULC change on frost indices - the dates of last spring frost and first fall frost and the length of frost free seasons. Frost is one of the major factors affecting the growth and development of plants and crop production. Future changes in LULC could make some regions more beneficial, while others more harmful to agricultural practice. Finally, the third study examines the potential impact of the changes in LULC pattern on future wind energy resources. As a zero carbon energy resource, wind energy helps limit greenhouse gasses emissions and mitigate climate change. Knowledge gained on where in the CONUS wind power class would likely to change from unsuitable or marginal to suitable, and vice versa, as a result of LULC change can be useful for future wind farm sitting and for making better informed energy policies.
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Title: Network-wide traffic state analysis : estimation, characterization, and evaluation
Creator: Saedi Germi, Ramin
Date: 2020
Collection: Electronic Theses & Dissertations
Description: The Network Fundamental Diagram (NFD) represents dynamics of traffic flow at the network level. It is exploited to design various network-wide traffic control and pricing strategies to improve mobility and mitigate congestion. This study presents a framework to estimate NFD and incorporates it for three specific applications in large-scale urban networks. Primarily, a resource allocation problem is formulated to find the optimal location of fixed measurement points and optimal sampling of...
Show moreThe Network Fundamental Diagram (NFD) represents dynamics of traffic flow at the network level. It is exploited to design various network-wide traffic control and pricing strategies to improve mobility and mitigate congestion. This study presents a framework to estimate NFD and incorporates it for three specific applications in large-scale urban networks. Primarily, a resource allocation problem is formulated to find the optimal location of fixed measurement points and optimal sampling of probe trajectories to estimate NFD accounting for limited resources for data collection, network traffic heterogeneity and asymmetry in OD demand in a real-world network. Using a calibrated simulation-based dynamic traffic assignment model of Chicago downtown network, a successful application of the proposed model and solution algorithm to estimate NFD is presented. The proposed model, then, is extended to take into account the stochasticity of day-to-day fluctuations of OD demand in NFD estimation.Three main applications of NFD are also shown in this research: network-wide travel time reliability estimation, network-wide emission estimation, and real-time traffic state estimation for heterogenous networks experiencing inclement weather impact. The main objective of the travel time reliability estimation application is to improve estimation of this network-wide measure of effectiveness using network partitioning. To this end, a heterogeneous large-scale network is partitioned into homogeneous regions (clusters) with well-defined NFDs using directional and non-directional partitioning approaches. To estimate the network travel time reliability, a linear relationship is estimated that relates the mean travel time with the standard deviation of travel time per unit of distance at the network level. Partitioning and travel time reliability estimation are conducted for both morning and afternoon peak periods to demonstrate the impacts of travel demand pattern variations.This study also proposes a network-level emission modeling framework via integrating NFD properties with an existing microscopic emission model. The NFDs and microscopic emission models are estimated using microscopic and mesoscopic traffic simulation tools at different scales for various traffic compositions. The major contribution is to consider heterogenous vehicle types with different emission generation rates in the network-level model. Non-linear and support vector regression models are developed using simulated trajectory data of thirteen simulated scenarios. The results show a satisfactory calibration and successful validation with acceptable deviations from underlying microscopic emission model, regardless of the simulation tool that is used to calibrate the network-level emission model.Finally, the NFD application for real-time traffic state estimation in a network experiencing inclement weather conditions is explored. To this end, the impacts of weather conditions on the NFD and travel time reliability relation are illustrated through a scenario-based analysis using traffic simulation. Then, the real-time traffic state prediction framework in the literature is adjusted to capture weather conditions as a key parameter. The extended Kalman filter algorithm is employed as an estimation engine to predict the real-time traffic state. The results highlight the importance of considering weather conditions in the traffic state prediction model.
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Title: Still learning : introducing the learning transfer model, a formal model of transfer
Creator: Olenick, Jeffrey David
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Although training has been a key topic of study in organizational psychology for over a century, a century which has seen great progress in our understanding of what a quality training program entails, a substantial gap persists between what is trained and what is transferred to the job. Reduction of the training-transfer gap has driven research on transfer-focused interventions which have proven effective. However, although we know a lot regarding how individuals learn new material, and...
Show moreAlthough training has been a key topic of study in organizational psychology for over a century, a century which has seen great progress in our understanding of what a quality training program entails, a substantial gap persists between what is trained and what is transferred to the job. Reduction of the training-transfer gap has driven research on transfer-focused interventions which have proven effective. However, although we know a lot regarding how individuals learn new material, and correlates of whether they transfer that material back to their work environment, we know very little about how individuals go about choosing whether to apply their new knowledge to, typically, previously-encountered situations in their work environment and how those decisions unfold over time. Improving our knowledge regarding how individuals transfer learned material will lead to new insights on how to support the transfer of organizationally directed training, or any learning event, back to the work environment. Thus, the present paper introduces a formal model of the transfer process, the Learning Transfer Model (LTM), which proposes a process for how transfer unfolds over time and gives rise to many of the findings we have accumulated in the transfer literature. This is accomplished by reconceptualizing transfer as its own learning process which is affected by the dual nature of human cognitive systems, the learner's social group, and their self-regulatory processes. The LTM was then instantiated in a series of computational models for virtual experimentation. Findings and implications for research and practice are discussed throughout.
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