Browsing by Subject "Modeling"

Now showing 1 - 20 of 50

An Agent-Based Model of Origin Destination Estimation (ABODE)
(Journal of Transport and Land Use, 2013) Tilahun, Nebiyou; Levinson, David
This paper proposes and tests an agent-based model of worker and job matching. The model takes residential locations of workers and the locations of employers as exogenous and deals specifically with the interactions between firms and workers in creating a job-worker match and the commute outcomes. It is meant to illustrate that by explicitly modeling the search and hiring process, origins and destinations (ODs) can be linked at a disaggregate level. The model is tested on a toy-city as well as using data from the Twin Cities area. The toy-city model illustrates that the model predicts reasonable commute outcomes, with agents selecting the closest work place when wage and skill differentiation is absent in the labor market. The introduction of wage dispersion and skill differentiation in the model increases the the average home to work distances considerably. Using data from Twin Cities area of Minneapolis-St. Paul, aggregate commute and wage outcomes from the model are shown to capture the trends in the observed data. Overall, the results suggest that the behavior rules as implemented lead to reasonable patterns. Future directions are also discussed.
Anticipating land-use impacts of self-driving vehicles in the Austin, Texas, region
(Journal of Transport and Land Use, 2020) Wellik, Tyler; Kockelman, Kara
This paper used an implementation of the land-use model SILO in Austin, Texas, over a 27-year period with an aim to understand the impacts of the full adoption of self-driving vehicles on the region's residential land use. SILO was integrated with MATSim for the Austin region. Land-use and travel results were generated for a business-as-usual case (BAU) of 0% self-driving or "autonomous" vehicles (AVs) over the model timeframe versus a scenario in which households’ value of travel time savings (VTTS) was reduced by 50% to reflect the travel-burden reductions of no longer having to drive. A third scenario was also compared and examined against BAU to understand the impacts of rising vehicle occupancy (VO) and/or higher roadway capacities due to dynamic ride-sharing (DRS) options in shared AV (SAV) fleets. Results suggested an 8.1% increase in average work-trip times when VTTS fell by 50% and VO remained unaffected (the 100% AV scenario) and a 33.3% increase in the number of households with "extreme work-trips" (over 1 hour, each way) in the final model year (versus BAU of 0% AVs). When VO was raised to 2.0 and VTTS fell instead by 25% (the "Hi-DRS" SAV scenario), average work-trip times increased by 3.5% and the number of households with "extreme work-trips" increased by 16.4% in the final model year (versus BAU of 0% AVs). The model also predicted 5.3% fewer households and 19.1% more available, developable land in the city of Austin in the 100% AV scenario in the final model year relative to the BAU scenario’s final year, with 5.6% more households and 10.2% less developable land outside the city. In addition, the model results predicted 5.6% fewer households and 62.9% more available developable land in the city of Austin in the Hi-DRS SAV scenario in the final model year relative to the BAU scenario’s final year, with 6.2% more households and 9.9% less developable land outside the city.
Characterization of 3D ultrastructure of plant biomass and development of a transport-reaction model for the pretreatment process
(2021-05) Ramanna, Sahana
The complex network of fibers and pore spaces in porous materials such as paper, wood etc., affect their structure, physical properties, and transport characteristics. In the case of wood or plant biomass, the system consists of cellulose fibers enclosed in a matrix of lignin and cellulose with some void spaces enclosed. Biomass is renewable and can be converted to a wide variety of bio-based products including biofuels, biochemicals, bioplastics, paper, wood plastic composites etc. The 3D internal structure of biomass can be related to their material properties. The biomass ultrastructure and how they change during various treatments may play a critical role in influencing the biomass conversion processes. Hence, it is essential to have an overall understanding of the 3D ultrastructure of plant cell walls and its relationship to the properties and how their change influences biomass conversion processes. The first step in biomass conversion processes is the pretreatment which is crucial in terms of the changes it brings to the cell wall architecture which in turn influences the reaction path forward. During this step, degradation of one or more of the cell wall components occur thereby, potentially altering the cell wall architecture. This is achieved with the help of several reagents such as alkali, acid, hot water, ammonia, enzymes, etc. and paves way for further treatment and conversion processes. While most of the previous work in this regard focuses mainly on 2D structure characterization using techniques such as optical and scanning electron microscopy, Fourier transform infra-red spectroscopy, atomic force microscopy, etc., it is vital that 3D structure characterization techniques are employed to fully explore the ultrastructure in a non-intrusive manner. This is possible with the advent of techniques such as Computed Tomography (CT) using either X-rays or Transmission Electron Microscopy (TEM). The current work uses TEM-CT to visualize the structural evolution of plant biomass and determine changes in properties such as porosity, pore size distribution and surface area, due to pretreatment. The cell wall structure was disrupted during pretreatment which resulted in a more porous structure and greater surface area which made it suitable for further hydrolysis. Additionally, topochemical distribution obtained from Raman spectroscopy was correlated with the TEM-CT structural evolution data in order to provide a complete understanding of the pretreatment process. In this context, a 3D transport-reaction model was then developed based on stochastic principles and reaction kinetics for lignin dissolution during pretreatment.The simultaneous transport-reaction occurring within the biomass cell wall structure is modeled using a hybrid random walk process. In our model, the structure and topochemical distribution of the untreated biomass sample obtained using Confocal Laser Scanning Raman Microscopy was used as the initial biomass sample. The diffusion and reaction model, using the actual biomass structure, begins in the cell wall lumen where the reagent particles diffuse through the lumen and other enclosed pore spaces based on a hybrid random walk. Diffusion continues in the pore phase until the fiber phase is encountered, upon which either reaction or further diffusion occurs based on the reaction probability. The reaction probability is determined from the Thiele modulus which encompasses both diffusive and reactive behavior of the system. The changes in lignin concentration in the cell wall is determined by local pseudo first order kinetics where the rate of reaction depends on the lignin concentration. The reagent used for pretreatment is assumed to be available in abundance compared to the lignin in the cell wall. The extent of conversion and thereby the efficiency of the pretreatment process is determined by the rate of transport of the reagents both in the pore and fiber phases, reaction probability, local kinetics, and ratio of diffusivity between the pore and fiber phases. Both the spatial and bulk concentration profiles of lignin as a function of reaction time were determined from the diffusion-reaction simulation. It was shown that the effective rate constant Keff considering both transport and reaction during biomass conversion is a function of biomass composition and, in some cases, also the reaction time. This is in correspondence with prior work reported in the biomass conversion literature. In addition, an overall transport rate co-efficient KT considering only the bulk and internal diffusion of the reagent in the cell wall system during pretreatment was determined based on walker’s survival time. The transport and reaction model results for different biomass species and pretreatment processes were compared with experimental data and appropriate local transport and reaction rate constants were determined. The relative effects of diffusion and reaction during biomass conversion for a given biomass species was then studied using various Thiele moduli over an appropriate range. Interestingly, it was found that diffusive transport, in general, played a critical role in the overall biomass dissolution. However, the relative effect of diffusion was found to be more significant at a lower Thiele modulus than at a higher Thiele modulus for the same local rate constant. The critical Thiele modulus may also depend on the biomass species and the biomass treatment conditions. These results indicate that approaches to opening the cell wall prior to any chemical/biochemical treatment, thus increasing their diffusive transport characteristics, may help with improving the efficiency of biomass pretreatment processes and, hence, further conversion. The results from the transport and reaction model may provide additional insights on the relative benefits of thermal, mechanical, and chemical pretreatment processes prior to further biomass conversion. This may help to select appropriate pretreatment processes for effective biomass conversion. The 3D structure visualization, characterization and the transport-reaction model using actual biomass structure developed here can help provide fundamental insights into the structure-property relationships during biomass pretreatment as well gain additional insight in developing improved biomass conversion strategies.
Comparison of Evapotranspiration Estimation Methods and Implications for Water Balance Model Parameterization in the Midwestern United States
(2019-12) Talbot, Michael
Evapotranspiration is the second most dominant component of the global water cycle behind precipitation, yet it remains one of the most difficult to measure and model. The numerous methods that have been developed for estimating evapotranspiration (ET) rates using climatological data vary in both complexity and spatiotemporal robustness. While the Penman-Monteith method has continually been shown to compare better with observed ET rates across more geographies and timescales than any other method, its high data requirements remain a barrier to use in many areas, and it is often desirable or necessary to make use of an alternative method. Daily reference ET estimates from the Penman-Monteith method were compared to ET estimates from seven alternative methods, which were generated using 14 years of observed weather records at five locations across the Midwestern United States. Then, a one-dimensional water balance model, DRAINMOD, was run at 362 locations across the Midwest using 50 years of synthetic climate data and three distinct sets ET inputs: 1) reference ET from the Penman-Monteith method, 2) potential ET generated from the Penman-Monteith reference ET and location-specific crop coefficient curves, and 3) potential ET from the Thornthwaite method. Results suggest that the best alternative method to Penman-Monteith varies by location, application, and timescale of interest, and that the misapplication of ET estimates for water balance model parameterization could have a dramatic impact on the accuracy of model predictions.
Comprehensive study of the chemical reactions resulting from the decomposition of chloroform in alkaline aqueous solution.
(2009-11) Mews, Jorge Estevez
Chloroform (CHCl3) is a volatile liquid, which has a rather slow rate of decomposition in ground water. It is a known carcinogen and one of the most common contaminants found at toxic waste sites. The dominant degradation process for chloroform in both the atmosphere and the groundwater is the reaction with the hydroxyl radical or hydroxide ion. This process triggers a sequence of reactions which ultimately yield carbon monoxide, hydrogen chloride, and formic acid. The rate of chloroform degradation is considerably larger in solution than that in the gas phase and it increases dramatically with increasing pH. However, only one of the viable reactions had been studied previously at a high level of theory in solution. It is of great interest to gain a deeper understanding of the decomposition reaction mechanism. Quantum mechanical methods are well suited for studying the mechanism of organic reactions. However, a full quantum mechanical treatment of the entire fluid system is not computationally feasible. In this work, combined quantum mechanical and molecular mechanical (QM/MM) methods are used for studying chemical reactions in condensed phases. In these calculations, the solute molecules are treated quantum mechanically (QM), whereas the solvent molecules are approximated by empirical (MM) potential energy functions. The use of quantum mechanics and statistical sampling simulation is necessary to determine the reaction free energy profile. In the present study, the ab initio Hartree-Fock theory along with the 3-21G basis set was used in the quantum mechanical calculations to elucidate the reaction pathways of chloroform decomposition, with a focus on basic reaction conditions. Statistical mechanical Monte Carlo approach was then applied in molecular mechanical simulations, employing the empirical TIP3P model for water. We employed state-of-the-art electronic structure methods to determine the gas-phase inter-nuclear potential energy profile for all the relevant reactions. Each gas-phase potential energy profile obtained at a high level of theory was used as a post-correction of the corresponding reaction free energy profile in aqueous solution. A detailed picture of the actual mechanism driving the decomposition pathway of chloroform has emerged from these simulations.
Contributing to meaning making: facilitating discourse in the high school physics classroom
(2014-05) Hovan, Scot Alan
The Next Generation Science Standards (NGSS) identify eight practices as essential to science and engineering, and these practices include asking students to construct explanations, to engage in argumentation, and to communicate scientific information. However, few teacher-training programs instruct teachers how to facilitate such discourse in the classroom. Modeling Instruction is one movement in physics education that organizes high school physics content around a small number of student-derived scientific models, and it relies on student discourse for the design, development, and deployment of these models. This research is a self-study of one high school physics teacher's experience facilitating large group discourse in the high school modeling physics classroom. Whiteboard meetings and graded discussions were examined by applying the analytical framework created by Mortimer and Scott (2003) to characterize the classroom talk and the discourse facilitation moves that I employed. In addition, elements of discourse analysis were used to examine some of the tensions that I experienced in the facilitation of this discourse. The findings suggest that deliberate identification of the teaching purposes for the discussion can help determine the scaffolding needed for students to enter the Discourse (Gee, 2011) of being a participant in these large group conversations. In addition, connecting the dialogic dimension of exploring student ideas with the authoritative dimension of introducing the scientific view and supporting the internalization of that view is necessary to contribute to meaning making in the science classroom.
Convection-Enhanced Evaporation: Modeling and Optimal Control for Modular Cost-Effective Brine Management
(2022-11) Kaddoura, Mustafa
This dissertation proposes mathematical modeling and novel cost-optimal control methods for Convection-Enhanced Evaporation (CEE) systems. CEE is the approach of evaporating water from saline films (brine) on packed evaporation surfaces by air convection, and actively controlling the operation variables to minimize the process cost. The developed approach represents a modular, cost-effective solution for brine management in decentralized and/or small scale desalination plants and industrial processes which currently lack safe and effective brine management options. Forced convection across packed, wetted evaporation surfaces is induced either by means of a fan, natural wind, or a combination of both (hybrid approach). As air flows over the liquid films, the difference in vapor pressure between the air and liquid surfaces induces evaporation. The work contains three major parts. The first part develops a generalized mathematical model of CEE systems to simulate the heat and mass transfer associated with convection-driven evaporation of saline films. The model is derived from the fundamental conservation equations of mass and energy, solved numerically using the finite difference method to predict the evaporation rate and the spatial distribution of humidity, temperature and salinity along the evaporation surfaces based on ambient condition, liquid (brine) inlet condition, and design configuration. The model-predicted performance is in good agreement with experimental pilot CEE system performance and with values published in the literature. The developed model is used to explore and compare the performance of three design aspects: (1) the liquid-air flow configuration (cross-flow vs parallel-flow), (2) the alignment and wetting of the surfaces (vertically aligned with double-sided wet surfaces vs horizontally aligned with single-sided wet surfaces), and (3) hybrid wind-fan operation, a novel operation model aimed at reducing the electrical energy demand of the fan by harnessing the natural drying power of the wind. The second part of this dissertation focuses on cost optimization. It proposes a method for formulating objective functions using cost ratios to generalize the optimization results to applications with varying material and energy prices and scenarios. The problem of identifying the cost-optimal operating settings was then solved as a multi-objective optimization using the genetic algorithm. The optimization revealed and characterized two distinct operation modes: "all-electric" mode, and "heating" mode. Finally, the last part of this dissertation proposes a data-driven optimal control method. The controller is based on a large dataset consisting of Pareto fronts, obtained in advance by solving a set of optimization problems. The method allows three optimal operation strategies: (1) real-time selection of operating variables, (2) predictive scheduled operation, and (3) hybrid wind-fan operation. The effectiveness of the proposed strategies was assessed through two case studies with distinct geographical locations and weathers. The results showed significant costsaving potential relative to static operation. The presented control strategies enable CEE to adjust its operation under various weather conditions. The models and methods developed in this dissertation are conducive to study and control of other configurations of CEE systems. They have the potential to be applied to other desalination and renewable energy systems, particularly those involving a trade-off between thermal and electric energy demand.
Development of Advanced Traffic Flow Models and Implementation in Parallel Processing, Phase II (9/15/92-9/15/93)
(Center for Transportation Studies, University of Minnesota, 1994-02) Lyrintzis, Anastasios S.; Michalopoulos, Panos G.; Liu, Guoqing; Rangiah, Raja P.
In this report, five high-order continuum traffic flow models are compared: Payne's model; Papageorgiou's model; the semi-viscous model and the viscous model as well as a proposed high-order model, and the simple continuum model. The stability of the high-order models is analyzed and the shock structure investigated in all models. In addition, the importance of the proper choice of finite-difference method is addressed. For this reason, three explicit finite-difference methods for numerical implementation, namely, the Lax method, the explicit Euler method and the upwind scheme with flux vector splitting, are discussed. The test with hypothetical data and the comparison of numerical results with field data suggest that high-order models implemented through the upwind method are better than the simple continuum model. The proposed high-order model appears to be more accurate than the other high-order models.
Discriminability of simple and complex haptic vibrations in single-cell computational and human psychophysical settings
(2017-07) Theis, Nicholas
A multiscale, multiphysics model of the Pacinian Corpuscle (PC) was used to study the neurophysiological response to haptic vibrations in the 100-200Hz range. The computational results were compared to human psychophysical experiments, emulating the pairing of psychophysics with in vivo electrophysiology in PC research. A first assessment of this approach was made by examining the discriminability (dꞌ) of pairs of vibrotactile stimuli. The discrimination task was performed psychophysically and in silico for both one- and two-frequency stimuli. Both firing rate and inter-spike interval neural decoding schemes were used to calculate dꞌ from simulation data. Human subjects discriminated between frequencies with two components (complex stimuli) more effectively than isolated frequencies (simple stimuli), possibly due to the presence of beat frequencies in dissonant stimuli. Over a given stimulus set, in silico dꞌ values correlated well with the psychophysical data (R2 > 0.6), but when the simple and complex data were combined the model did not match the experiment (R2 < 0.1). Firing rate resulted in better predictions than inter-spike interval, and was more robust to noise. Results suggest that a single simulated PC can capture some but not all of the observed psychophysical response to a vibrotactile stimulus.
Electrostatic Assist of Liquid Transfer in Printing Processes
(2018-07) Huang, Chung-Hsuan
Printing processes are being explored for the large-scale manufacture of electronic de- vices. Transfer of liquid from one surface to another plays a key role in most printing processes. During liquid transfer, a liquid bridge is formed and then undergoes sig- nificant extensional motion. Incomplete liquid transfer can produce defects that can be detrimental to device operation. One important printing process is gravure, which involves transfer of liquid from micron-scale cavities at high speeds. Electric fields are sometimes used to enhance liquid transfer, a technique known as electrostatic assist (ESA). However, its underlying physical mechanisms remain a mystery. This thesis uses a combination of theory and experiment to understand the fundamental mechanisms by which electrostatic forces influence liquid transfer. Liquid transfer without electric fields and cavities must be understood before study- ing the mechanism of ESA. We develop one-dimensional (1D) slender-jet and two- dimensional (2D) axisymmetric models of this phenomenon and compare the resulting predictions with previously published experimental data. At relatively low stretching speeds, predictions from both models of the amount of liquid transferred agree well with the experimental data. When the stretching speed is high enough, the models predict that each surface receives half the liquid, in agreement with experimental observations. For intermediate values of the stretching speed, predictions from each model can deviate substantially from the experimental data, which we speculate is due to the influence of surface defects that are not included in the models. The 1D and 2D model are modified to include electrostatic effects. The liquid be- haves like a perfect (non-conducting), or leaky dielectric (poorly conducting) material. The liquid is confined between two plates, with the top plate having a constant electro- static potential while the bottom plate is grounded. For perfect dielectrics, application of an electric field enhances liquid transfer to the more wettable surface because it slows the surface-tension-driven breakup of the bridge, thereby allowing more time for the con- tact line to retract on the less-wettable surface. For leaky dielectrics, application of an electric field can augment or oppose the influence of wettability differences, depending on the direction of the electric field and the sign of the interfacial charge. Experimental results confirm the enhancement of the amount of liquid transferred when the electric field is present, and the measured values are in good agreement with the predictions of the 1D perfect dielectric model. When one of the plate is replaced by a cavity, the presence of the cavity causes the contact line on the cavity wall to effectively pin and inhibits the liquid transfer. For perfect dielectrics, application of an electric field unpins the contact line on the cavity and leads to improvement of cavity emptying. For the leaky dielectrics, the presence of the surface charge does not further improve liquid transfer because of nearly zero electric tangential stress near the contact line on each surface.
Electrostatic effects in coating and printing processes
(2015-01) Ramkrishnan, Aruna
Coating and printing are interfacial processes that are highly relevant in industry. Precision coatings impart functionalities and boost the performance of products. On the other hand, high-resolution roll-to-roll printing is being increasingly explored for creating dense and flexible printed electronics at high speeds. Electrostatic effects often significantly influence both these processes. However, in industry, much of the current understanding of these effects is empirical and has not received a rigorous treatment. This thesis discusses how electrostatics and hydrodynamics couple in coating and printing applications, and presents different modes of investigation: simplified thin-film models and flow visualization experiments, to understand the underlying physics of these processes. Throughout this work, the electric response of liquids has been described by the perfect (non-conducting) and leaky dielectric (partially conducting) models, which are representative of many liquids used in industry. In coating processes, electrostatic charges are known to accumulate on the substrate due to various upstream operations (e.g. corona treatment, friction in roll-to-roll equipment). This leads to the buildup of an electric field in the subsequently coated film, which in turn causes the formation of defects due to electrostatically driven flows. Thus, in order to obtain high quality coatings, it is desirable to keep them resistant to electrostatic destabilization. We have carried out a systematic study via the construction of electrohydrodynamic lubrication models to understand the influence of charged substrates and charged interfaces on the leveling of liquid coatings. Based on our findings, we develop simple heuristics that can be used to design coatings that are stable to substrate charging and charge contamination. Electric fields are also present in some printing processes. Developed in the late1960s, electrostatic assist (ESA) has been long used to remove printing defects and enhance image quality in gravure printing, a high-resolution roll to-roll process. ESA involves the application of an electric field to pull ink out of cavities and transfer it onto the desired substrate. However, there is limited understanding of how this process works, which hinders its development as a tool for printed electronics. In order to address this issue, we develop a model for electrostatically assisted meniscus deformation near a cavity (this describes the first stage of electrostatic assist). Our calculations show that electric fields pull up the ink meniscus either at the edges or at the center of the cavity, depending on the ink conductivity. This suggests that ink contact with the substrate will be improved during ESA but air entrapment occurs for a certain range of conductivities, which would be detrimental to print quality. Our model also enables us to investigate the effect of cavity shape and spacing on the mode of deformation of the ink surface. In order to validate the findings from our electrohydrodynamic model, we have carried out flow visualization experiments to track the deformation of liquids contained in cavities, and these corroborate the qualitative trends of meniscus deformation predicted by the model.
Evaluating bias caused by screening in observational risk-factor studies of lung cancer nested in the PLCO randomized screening trial.
(2009-09) Jansen, Ricky Jeffrey
It is well-known that bias such as lead-time and length distort studies of screening efficacy whether survival or incidence is of interest. A third bias, usually called overdiagnosis bias, occurs when an individual is only diagnosed with disease before death from a different cause because he/she is screened. These forms of bias can also arise in observational studies where the proportion screened and screening rates vary by risk-factor strata. This difference in screening behaviors influences corresponding case ascertainment or case enrollment probabilities which can lead to erroneous conclusions about the size of the risk-factor effect on the disease. It has been suggested that classic confounding occurs in such risk-factor studies when screening is efficacious; therefore, it can be addressed by conventional analyses such as stratification or confounder adjustment in regression models. However, even if the test is not efficacious, screening creates changes in case ascertainment probabilities which must be addressed using alternative methods. Recurrence-time models, long used for screening programs, can be adapted to model the affect screening use has on risk-factor studies. These models can be used to study the magnitude of potential bias, but may also be adapted to provide an analytic approach to correct estimates for such bias. The risk-factor studies nested in the PLCO trial are potentially affected by such bias, and this randomized study also provides a structure within which models of screening bias may be tested and validated. To validate our model, a variety of nested case-control studies will be developed that measure the effect smoking has on lung cancer and the degree to which the bias affecting those estimates change based on the study design will be determined. This process will include a) expanding a previously developed lead-time bias model to incorporate length and overdiagnosis; b) incorporating a more flexible and realistic model of screening that can incorporate the patterns documented in the PLCO trial; c) exploring if the mathematical model is valid using varied nested study designs within PLCO and comparing resulting logistic regression estimates to simulated results; and d) using the validated models to produce correction factors for use in other nested risk-factor studies. Results indicate that the mathematical model is highly sensitive to overdiagnosis as increasing rates increase expected bias, but relatively insensitive to using different screening test sensitivities. Increasing screening behavior differential during the study, preclinical duration length, and selecting from the intervention group are associated with increasing expected screening bias. Increasing screening behavior before the study and selecting from the usual-care group are associated with a decreasing expected screening bias. Although the mathematical model couldn't be validated as a correction factor here, the results suggest using a shorter preclinical duration distribution for the model may produce more accurate screening bias values. The focus of this work was to identify if chest x-ray screening could modify the estimated risk of smoking on lung cancer diagnosis. An additional goal was to develop a usable method for adjusting observational studies of lung cancer for the bias arising from differential chest x-ray screening between ever and never smoking groups. In a boarder sense, this work has provided an explanation of the effect screening use may have on an observational risk-factor study and an example of how to implement the mathematical technique. Additionally, this project has provided a more general method for doing sensitivity analyses on the screening related assumptions involved with these studies, whether nested in a randomized trial or sampled from the population at large.
Factors Contributing to Rigidity Expression and Response to Pallidal Deep Brain Stimulation in People with Parkinson’s Disease
(2021-09) Linn-Evans, Maria
Parkinson’s disease (PD) is a neurodegenerative disorder characterized by the loss of dopaminergic cells in the substantia nigra, buildup of alpha-synuclein in specific regions of the brain, and the emergence of cardinal motor symptoms including rigidity, slowness of movement, tremor, and gait dysfunction. Despite these shared characteristics, there is a great deal of heterogeneity in symptom presentation and response to therapies within the population of individuals with PD. Understanding the driving factors behind this heterogeneity is crucial for developing targeted and effective therapies for the disease and improving outcomes for those living with Parkinson’s disease. In this dissertation, two studies are described: 1) an investigation into the effects of rapid eye movement (REM) sleep without atonia (RSWA) on the presentation of rigidity in a population of individuals with mild-to-moderate Parkinson’s disease and 2) the development and implementation of a computational model of pallidal deep brain stimulation (GP-DBS) to identify neural pathways associated with rigidity suppression in individuals with PD. Both studies utilize a quantitative measure of rigidity as a tool to assess symptom severity. In the first study, our findings demonstrate that people with mild to moderate PD and RSWA have dysfunctional regulation of muscle tone during both sleep and wakefulness. The results show that the presence of RSWA is associated with increased forearm rigidity magnitude and symmetry. In the second study, a patient-specific computational model of GP-DBS was developed and implemented. By combining pathway activation estimates from the model with quantitative measurements of rigidity, the analyses identified the internal capsule as an important pathway for reducing parkinsonian rigidity. In particular, profound decreases in rigidity were associated with activation of internal capsule fibers projecting from Brodmann’s area 6, which contains axons from premotor cortex and supplementary motor area. The results of these studies reveal the importance of understanding factors like RSWA that may drive heterogeneity in PD, while also identifying potential pipelines for developing symptom-specific targets for treatment.
Integrated land use and transportation modelling and planning: A South African journey
(Journal of Transport and Land Use, 2020) Waldeck, Louis; van Heerden, Quintin; Holloway, Jenny
Confronted by poverty, income disparities and mounting demands for basic services such as clean water, sanitation and health care, urban planners in developing countries like South Africa, face daunting challenges. This paper explores the role of Integrated land use and transportation modelling in metropolitan planning processes aimed at improving the spatial efficiency of urban form and ensuring that public sector investments in social and economic infrastructure contribute to economic growth and the reduction of persistent poverty and inequality. The value of such models is not in accurately predicting the future but in providing participants in the (often adversarial) planning process with a better understanding of cause and effect between different components of the urban system and in discovering common ground that could lead to compromise. This paper describes how an Urban Simulation Model was developed by adapting one of the leading microsimulation models (UrbanSim) originating from the developed world to South African conditions and how the requirements for microscopic data about the base year of a simulation were satisfied in a sparse data environment by introducing various typologies. A sample of results from three case studies in the cities of Tshwane, Ekurhuleni and Nelson Mandela Bay between 2013 and 2017 are then presented to illustrate how modelling supports the planning process by adding elements of rational analysis and hypothesis testing to the evaluation of proposed policies.
An integrated microsimulation approach to land-use and mobility modeling
(Journal of Transport and Land Use, 2018) Zhu, Yi; Diao, Mi; Ferreira, Joseph Jr.; Zegras, P. Christopher
This paper presents an overview of the design and status of a new type of land-use simulation module integrated into SimMobility, an agent-based microsimulation platform. The module, SimMobility Long-Term (LT), is designed to simulate how the interrelations between the transportation and land-use systems manifest themselves in the housing and commercial real estate markets, household and firm location choices, school and workplace choices, and vehicle ownership choices. At the heart of the LT simulator is a housing market module simulating daily dynamics in the residential housing market that (a) “awakens” households that begin searching for new housing; (b) accounts for eligibility, affordability, and screening constraints; (c) constructs plausible choice sets; (d) simulates daily housing market bidding; and (e) represents developer behavior regarding when, where, what type, and how much built space to construct, taking into account market cycle and uncertainty. The LT simulator and SimMobility’s activity-based, mid-term (MT) simulator are integrated in that the agents in the LT module (e.g., individuals in households) are the same agents simulated in the MT module (e.g., activity participation and trip-making), and agents’ simulated behaviors in the MT module provide measures of (utility-based) accessibility that figure into relevant decisions in the LT simulator. This paper describes the SimMobility model and the LT framework, presents estimation results for two component models of the housing supply side, and demonstrates the use of the simulator by comparing housing market outcomes with and without the introduction of one year’s worth of supply of new public housing. Overall, the LT simulator represents an effort to advance urban system modelling by explicitly simulating the dynamic interactions of disaggregated agents in real estate markets and encapsulating the information of agents’ daily activity participation in their long-term mobility-relevant choices.
Integrating urban recharge uncertainty into standard groundwater modeling practice: A case study on water main break predictions for the Barton Springs segment of the Edwards Aquifer, Austin, Texas
(2017-05) Sinner, Kate
Groundwater models serve as integral tools for understanding flow processes and informing stakeholders and policy makers in management decisions. Historically, these models tended toward a deterministic nature, relying on historical data to predict and inform future decisions based on model outputs. This research works toward developing a stochastic method of modeling recharge inputs from pipe main break predictions in an existing groundwater model, which subsequently generates desired outputs incorporating future uncertainty rather than deterministic data. The case study for this research is the Barton Springs segment of the Edwards Aquifer near Austin, Texas. Researchers and water resource professionals have modeled the Edwards Aquifer for decades due to its high water quality, fragile ecosystem, and stakeholder interest. The original case study and model that this research builds upon was developed as a co-design problem with regional stakeholders; the model outcomes are generated specifically for communication with policy makers and managers. Recently, research in the Barton Springs segment demonstrated a significant contribution of urban, or anthropogenic, recharge to the aquifer, particularly during dry periods, using deterministic data sets. Due to social and ecological importance of urban water loss to recharge, this study develops an evaluation method to help predicted pipe breaks and their related recharge contribution within the Barton Springs segment of the Edwards Aquifer. To benefit groundwater management decision processes, the performance measures captured in the model results, such as springflow, head levels, storage, and others, were determined by previous work in elicitation of problem framing to determine stakeholder interests and concerns. Through additional modeling processes, this study compares the results of the previous deterministic model and the stochastic model to determine gains to stakeholder knowledge.
The intersection of climate change, watershed influence, and phytoplankton dynamics in Lake Superior
(2021-06) Reinl, Kaitlin
Climate change is leading to ecological shifts in lakes including altered thermal regimes, nutrient cycles, and food web structure. I explore how climate change is impacting phytoplankton dynamics in Lake Superior. I show that there are clear seasonal patterns in the development and degradation of the deep chlorophyll layer (DCL) and that as water temperatures warm there is a restructuring of the DCL, with a smaller thickness and greater maximum concentration at warmer temperatures. My research also shows that biological loading from rivers to Lake Superior may be an important source of seed populations for cyanobacterial blooms, particularly those characterized by low water temperature and high conductivity. Finally, I present a life cycle model to predict cyanobacterial blooms that integrates monitoring data and cyanobacteria life cycle stages. The model highlights the importance of phosphorus loading in promoting blooms and shows that akinete production may result in a decrease in peak summer vegetative biomass. This work lays the critical groundwork for understanding the impact of climate change on phytoplankton dynamics and their ecological implications.
Intranasal and rectal diazepam for rescue therapy: assessment of pharmacokinetics and tolerability.
(2010-12) Ivaturi, Vijay Deep
The use of rectal diazepam has improved the management of acute repetitive seizures (ARS) outside a health care facility. Two placebo controlled trials have shown that rectal administration of diazepam is safe and effective for treatment of this condition. Diastat® is the only FDA approved treatment for ARS in the United States. Although some older children and adults are willing to use Diastat®, many patients in these age groups as well as physicians and caregivers object to the route of administration and instead use other therapies not approved for this purpose, receive no treatment, or use emergency medical services or acute care systems. We developed and evaluated three nasal spray formulations of diazepam which can be easily administered with rapid absorption characteristics intended as an alternative to rectal administration. One formulation used a supersaturated glycofurol based co-solvent system while the remaining two (Nas-A & Nas-B) used microemulsion based co-solvent systems. These formulations were studied for their pharmacokinetics and tolerability in healthy adult volunteers. Data from these studies were then compared to the pharmacokinetics after rectal administration using both model-based analysis (NONMEM) and graphical methods. The primary finding from this work was that, only the microemulsion-based formulations, particularly Nas-B could be used for further development as the glycofurol formulation was not well tolerated by subjects. The pharmacokinetic profiles after intranasal administration were associated with high variability. However, we are able to show that the dose-normalized partial area under the curve (AUC - an exposure parameter) after nasal administration, at times when the drug concentrations are most important, are 60-80 % of that when given via the rectal route. Given the ease and social acceptability of nasal administration compared to rectal, equivalent exposures can be easily attained by giving a second nasal dose, and we thus conclude that intranasal diazepam is a feasible and preferable alternative to rectal diazepam in the management of ARS outside a hospital. This work also provides some recommendations for future studies in the development of an intranasal product.
Investigation of the thermal parameters of reclaimed asphalt materials with applications to asphalt recycling
(2014-08) DeDene, Christopher D.
Asphalt concrete is the third most widely used resource in the world, next to Portland Cement Concrete and water. In the United States alone, over 550 million tons of hot mix asphalt (HMA) are produced at more than 4,000 asphalt plants across the country. With over 94% of the paved roads in the United States surfaces with asphalt concrete, it's safe to say asphalt pavement is what America drives on. However, a majority of today's pavement projects are geared towards rehabilitation and reconstruction of existing pavements, rather than construction of new roads. While it is true that asphalt pavement is 100% recyclable and it is the most recycled material in America, the reality is most roads contain no more than 20% recycled material. There are many factors that prohibit new road construction in excess of 20% recycled content, and this thesis aims to explore just one of those factors - the thermodynamics of hot mix asphalt pavement recycling. Most research that is investigating the use of high amounts of Reclaimed Asphalt Pavement (RAP) have been based on empirical trials. This work has approached the issue of pavement recycling by measuring the thermal properties of recycled asphalt, examining the thermodynamic limits of asphalt drum mixing, and by modeling asphalt mixing drums using finite element techniques to determine the amount of time required to achieve full melting inside of asphalt drums. It was found that for many different drum configurations, there is insufficient retention time for RAP to reheat. This insufficient heating could cause premature failures in asphalt pavements using high percentages of RAP. A secondary goal of this thesis is to explore the benefits of using the waste mining material, taconite tailings, in new asphalt pavements. This research shows there is thermodynamic benefit gained by using taconite tailings because they can be heated faster than traditional aggregates. This heating supplies more heat to RAP, which in turn, may allow for more of the recycled asphalt pavement to be incorporated into new asphalt pavements.
Light Management in Chiral Optical Metamaterials and Photovoltaic Modules
(2022-06) Cote, Bryan
Engineered design of nanophotonic structures enables exemplary control over the generation and propagation of electromagnetic radiation. This thesis explores two promising applications of nanophotonic design, polarization control and photovoltaic light management. Materials with strong and selective interactions with circularly polarized light have wide ranging applications from document security to biological detection. We show that light emitting metasurfaces can be designed with tailored directionality and polarization state of photoluminescence outcoupling through the judicious placement of light emitters within the metasurface’s unit cell. Additionally, the effects of Mie resonances on the circular dichroism (CD) response of a chiral medium are studied. Large CD and dissymmetry factor enhancements are observed by designing the chiral medium to support spectrally overlapping electric and magnetic dipolar resonances. Lastly, the origin of the strong CD responses generated by chiral, single gyroid metamaterials is studied, a metamaterial design that can be fabricated through block copolymer self-assembly templating. The CD responses are found to be dominated by surface interactions, allowing for double gyroid metamaterials, which are achiral in the bulk, to support strong CD responses. The second half of the thesis examines methods to improve the light management in photovoltaic modules. We find that bifacial photovoltaic modules operate at high temperatures due to their increased absorption of rear-side incident light, decreasing their energy yield and operating lifetime. Spectrally selective photonic mirrors that simultaneously provide above-bandgap antireflection and sub-bandgap increased reflection are found to be a promising passive thermal management strategy for bifacial photovoltaics. A spectrally selective mirror is fabricated for outdoor field testing. Lastly, the optical losses in a four-terminal CdTe/Si tandem module are studied and mitigated though rational nanophotonic design.

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