Browsing by Subject "Modeling"
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Item A dynamic model of human respiratory mechanics for use in respiratory mask design and development(2021-11-22) Koeroghlian, Mark M.; Longoria, Raul G.; Beaman, Joseph J; Ezekoye, Ofodike; Lalande, SophieA dynamic model of human respiratory mechanics is developed to aid in the design and development of pressure-compensated oxygen masks worn by combat aircrew. Breathing models of varying complexity are formulated using the bond graph method to convey key elements of the system. A simple respiratory mask model containing inhalation and exhalation check valves is combined with the respiratory mechanics model. The system state equations are derived for each of the models presented and constitutive relations are described. Numerical solution of the system state equations is shown to capture dissipative and energy storage effects in respiratory tract and compliant elements of the system. The inclusion of air flow inertance in the model is shown to simplify the state equations by eliminating a non-linear algebraic loop. Respiratory mask performance metrics are presented and results from several case studies with variations in the lung characteristics and breathing scenarios are presented to demonstrate the effectiveness of the model in predicting key physiological measures, reported in the form of flow-volume loops, work of breathing, and mask cavity pressures.Item A kinematic model of the shoulder complex for estimating shoulder girdle angles without acromial sensing(2017-08-11) Ogden, Evan Michael; Deshpande, Ashish D.The movements of each joint in the shoulder complex is important to measure for studying shoulder function, injuries, and rehabilitation. The current standards for measuring these motions are non-invasive motion capture of surface markers or regression equations from other research studies. Certain environments, such as robotic exoskeletons and spacesuits, are not compatible with motion capture systems because their hardware obscures or precludes these measurement. The existing regression models are generalized across a wide range of subjects and are designed with experimental data that has minimal environmental interaction. So, these methods are insufficient for estimating shoulder girdle motion in an occluded setting and with substantial human-device interaction. The objective of this thesis is to develop and evaluate a novel kinematic shoulder model that estimates shoulder girdle angles without acromial sensors. This model leverages the geometric similarities of the human shoulder and a RRSS spatial linkage to constrain the internal degrees of freedom of the shoulder mechanism. A nonlinear optimization method is used to predict the configuration of the shoulder by matching desired distances between the scapula and the ribcage. This model is validated using experimental measurements of 77 arm movements from five subjects. With ideal inputs, the kinematic model is able to accurately estimate shoulder girdle angles within 2°. The model was also able to outperform two existing shoulder regression models. However, small changes to model geometry or input kinematics result in significant errors in all shoulder angles. This is likely due to the rigidity of the kinematic constraint, which uses an idealized mechanical model to represent a complex biological system with flexible joints. Ultimately, this work shows that the kinematic constraints from this linkage model can be used to predict shoulder angles during a variety of different movements without sensors on the acromion. The model's robustness can be improved by pairing it with a compliant joint model to permit errors in anthropometry and input kinematics.Item Analysis, modeling, and control of highly-efficient hybrid dc-dc conversion systems(2012-12) Zhao, Ruichen; Kwasinski, Alexis; Aristotle, Arapostathis; Grady, William; Akella, Maruthi; Driga, MirceaThis dissertation studies hybrid dc-dc power conversion systems based on multiple-input converters (MICs), or more generally, multiport converters. MICs allow for the integration of multiple distributed generation sources and loads. Thanks to the modular design, an MIC yields a scalable system with independent control in all sources. Additional characteristics of MICs include the improved reliability and reduced cost. This dissertation mainly studies three issues of MICs: efficiency improvement, modeling, and control. First, this work develops a cost-effective design of a highly-efficient non-isolated MIC without additional components. Time-multiplexing (TM) MICs, which are driven by a time-multiplexing switching control scheme, contain forward-conducting-bidirectional-blocking (FCBB) switches. TM-MICs are considered to be subject to low efficiency because of high power loss introduced by FCBB switches. In order to reduce the power loss in FCBB switches, this work adopts a modified realization of the FCBB switch and proposes a novel switching control strategy. The design and experimental verifications are motivated through a multiple-input (MI) SEPIC converter. Through the design modifications, the switching transients are improved (comparing to the switching transients in a conventional MI-SEPIC) and the power loss is significantly reduced. Moreover, this design maintains a low parts-count because of the absence of additional components. Experimental results show that for output power ranging from 1 W to 220 W, the modified MIC presents high efficiency (96 % optimally). The design can be readily extended to a general n-input SEPIC. The same modifications can be applied to an MI-Ćuk converter. Second, this dissertation examines the modeling of TM-MICs. In the dynamic equations of a TM-MIC, a state variable from one input leg is possible to be affected by state variables and switching functions associated with other input legs. In this way, inputs are coupled both topologically and in terms of control actions through switching functions. Coupling among the state variable and the time-multiplexing switching functions complicate TM-MICs’ behavior. Consequently, substantial modeling errors may occur when a classical averaging approach is used to model an MIC even with moderately high switching frequencies or small ripples. The errors may increase with incremental number of input legs. In addition to demonstrating the special features on MIC modeling, this dissertation uses the generalized averaging approach to generate a more accurate model, which is also used to derive a small-signal model. The proposed model is an important tool that yields better results when analyzing power budgeting, performing large-signal simulations, and designing controllers for TM-MICs via a more precise representation than classical averaging methods. Analyses are supported by simulations and experimental results. Third, this dissertation studies application of a decentralized controller on an MI-SEPIC. For an MIC, a multiple-input-multiple-output (MIMO) state-space representation can be derived by an averaging method. Based on the averaged MIMO model, an MIMO small-signal model can be generated. Both conventional method and modern multivariable frequency analysis are applied to the small-signal model of an MI-SEPIC to evaluate open-loop and closed-loop characteristics. In addition to verifying the nominal stability and nominal performance, this work evaluates robust stability and robust performance with the structured singular value. The robust performance test shows that a compromised performance may be expected under the decentralized control. Simulations and experimental results verify the theoretical analysis on stability and demonstrate that the decentralized PI controller could be effective to regulate the output of an MIC under uncertainties. Finally, this work studies the control of the MIMO dc-dc converter serving as an active distribution node in an intelligent dc distribution grid. The unified model of a MIMO converter is derived, enabling a systematical analysis and control design that allows this converter to control power flow in all its ports and to act as a power buffer that compensates for mismatches between power generation and consumption. Based on the derived high-order multivariable model, a robust controller is designed with disturbance-attenuation and pole-placement constraints via the linear matrix inequality (LMI) synthesis. The closed-loop robust stability and robust performance are tested through the structured singular value synthesis. Again, the desirable stability and performance are verified by simulations and experimental results.Item Analysis-ready models of tortuous, tightly packed geometries(2013-08) Edwards, John Martin; Bajaj, ChandrajitComplex networks of cells called neurons in the brain enable human learning and memory. The topology and electrophysiological function of these networks are affected by nano and microscale geometries of neurons. Understanding of these structure-function relationships in neurons is an important component of neuroscience in which simulation plays a fundamental role. This thesis addresses four specific geometric problems raised by modeling and simulation of intricate neuronal structure and behavior at the nanoscale. The first two problems deal with 3D surface reconstruction: neurons are geometrically complex structures that are tightly intertwined in the brain, presenting great challenges in reconstruction. We present the first algorithm that reconstructs surface meshes from polygonal contours that provably guarantees watertight, manifold, and intersection-free forests of densely packed structures. Many algorithms exist that produce surfaces from cross-sectional contours, but all either use heuristics in fitting the surface or they fail when presented with tortuous objects in close proximity. Our algorithm reconstructs surfaces that are not only internally correct, but are also free of intersections with other reconstructed objects in the same region. We also present a novel surface remeshing algorithm suitable for models of neuronal dual space. The last two problems treated by this thesis deal with producing derivative models from surface meshes. A range of neuronal simulation methodologies exist and we offer a framework to derive appropriate models for each from surface meshes. We present two specific algorithms that yield analysis-ready 1D cable models in one case, and proposed "aligned cell" models in the other. In the creation of aligned cells we also present a novel adaptive distance transform. Finally, we present a software package called VolRoverN in which we have implemented many of our algorithms and which we expect will serve as a repository of important tools for the neuronal modeling community. Our algorithms are designed to meet the immediate needs of the neuroscience community, but as we show in this thesis, they are general and suitable for a variety of applications.Item Analyzing and improving MAESTRO's analytical modeling(2021-05-09) Kumari, Aparna; Lin, Yun CalvinDeep learning accelerators efficiently execute deep learning applications through customization. However, designing specialized hardware takes considerable time and engineering effort. Design space exploration (DSE) tools automate the design of specialized accelerators by automatically evaluating designs in this vast design space. A core component of DSE tools is an analytical model, which allows the DSE tool to filter out invalid or sub-optimal candidates at a coarse granularity before resorting to synthesis, which is more accurate but time-consuming. The MAESTRO analytical model has been used in existing DSE tools because it strikes a good balance between detail and speed. In this thesis, we improve the MAESTRO analytical model by identifying and fixing three limitations, namely (1) we consider buffer sizes in the memory energy and area model, (2) we add support for differentiating between a unified buffer and partitioned buffer, and (3) we add support for exploring bit-precision. Next, we detail future directions for improving the MAESTRO analytical model. First, we do a component-wise area and power analysis on a commercial accelerator, Nvidia Deep Learning Accelerator (NVDLA) [4], to gain insights about sub-components not modeled by the analytical model. Next, to understand the impact of compute organization, we do a component-wise area analysis of two compute organizations executing matrix-vector multiplication.Item Assessing and controlling concentrations of volatile organic compounds in the retail environment(2014-05) Nirlo, Éléna Laure; Corsi, Richard L.; Siegel, Jeffrey A.Retail buildings have potential for both short-term (customer) and long-term (occupational) exposure to indoor pollutants. A multitude of sources of volatile organic compounds (VOCs) are common to the retail environment. Volatile organic compounds can be odorous, irritating or carcinogenic. Through a field investigation and modeling study, this dissertation investigates exposure to, and control of, VOCs in retail buildings. Fourteen U.S. retail stores were tested one to four times each over a period of a year, for a total of twenty-four test visits. Over a hundred parameters were investigated to characterize each of the buildings, including ventilation system parameters, and airborne pollutants both indoors and outdoors. Concentrations of VOCs were simultaneously measured using five different methods: Summa canisters, sorbent tubes, 2,4-dinitrophenylhydrazine (DNPH) tubes, a photoionization detector (PID), and a colorimetric real-time formaldehyde monitor (FMM). The resulting dataset was analyzed to evaluate underlying trends in the concentrations and speciation of VOCs, identify influencing factors, and determine contaminants of concern. A parametric framework based on a time-averaged mass balance was then developed to compare strategies to reduce formaldehyde concentrations in retail stores. Mitigation of exposure to formaldehyde through air cleaning (filtration), emission control (humidity control), and targeted dilution (local ventilation) were assessed. Results of the field study suggested that formaldehyde was the most important contaminant of concern in the retail stores investigated, as all 14 stores exceeded the most conservative health guideline for formaldehyde (OEHHA TWA REL = 7.3 ppb) during at least one sampling event. Formaldehyde monitors were strongly correlated with DNPH tube results. The FMM showed promising characteristics, supporting further consideration as real-time indicators to control ventilation and/or environmental parameters. The vast majority of the remaining VOCs were present at low concentrations, but episodic activities such as cooking and cleaning led to relatively high indoor concentrations for ethanol, acetaldehyde, and terpenoids. Results of the modeling effort demonstrated that local ventilation caused the most uniform improvements to indoor formaldehyde concentrations across building characteristics, but humidity control appeared to have a very limited impact. Filtration used under specific conditions could lead to larger decreases in formaldehyde concentrations than all other strategies investigated, and was the least energy-intensive.Item Atomic-scale modeling and experimental studies for dopants and defects in Si and SiGe nano-scale CMOS devices(2010-05) Kim, Yonghyun; Banerjee, Sanjay; Kirichenko, Taras A.; Lee, Jack Chung-Yeung; Register, Leonard F.; Tutuc, Emanuel; Henkelman, GraemeContinued scaling of CMOS devices with Si and SixGe1-x down to 22 nm design node or beyond will require the formation of ever shallower and more abrupt junctions with higher doping levels in order to manage the short channel effects. With the increasing importance of surface proximity and stress effects, the lateral diffusion in gate-extension overlap region strongly influences both threshold voltage roll-off degradation and DIBL increase by requiring an optimized abruptness and diffusion for better device performance. Therefore, the detailed understanding of defect-dopant interactions in the disordered and/or strained systems is essential to develop a predictive kinetic model for the evolution of dopant concentration and electrical activation profiles. Our density functional theory calculations provide the guidance for experimental designs to realize ultra-shallow junction formation required for future generations of nano-scale CMOS devices. Few systematic studies in epitaxially-grown SixGe1-x channel CMOS have been reported. The physical mechanisms of boron diffusion in strained SixGe1-x/Si heterojunction layers with different SixGe1-x layer thicknesses and Ge content (>50%) are addressed, especially with high temperature annealing. In addition, the effects of the fluorine incorporated during BF2 implant on boron diffusion are investigated to provide more insight into short channel device design. In this study, we investigate how short channel margins are affected by Ge mole fraction and SixGe1-x layer thickness in a compressively strained SixGe1-x/Si heterojunction PMOS with high temperature annealing. Series resistance characterization in S/D extension region and gate oxide interface trap characterization for Si, SixGe1-x, and Ge nMOSFETs are done. TCAD device simulation is also performed to evaluate which distributions of interface traps will significantly affect the electrical characteristics such as flatband voltage (VFB) shift and threshold voltage (Vth) shift based on capacitance-voltage (CV) and current-voltage (IV) curves. n+/p and p+/n diode structures are studied in order to decouple the electrical characteristics from the gated-diode (GD) MOSFETs. With the extraction of S/D series resistance from various channel lengths, possible reasons for performance degradation in SixGe1-x and Ge nMOSFETs, based on simulations, are proposed.Item Austin's route forward : an exploration of alternative demand estimation and the transit planning process(2015-05) Mosteiro, Jonathan David; Jiao, Junfeng; Machemehl, RandyAlternative demand estimation techniques for transit planning have gained increased attention in recent years. These "sketch planning" models are often faster and easier to use than traditional four-step travel demand models, and can therefore play a significant role in preliminary feasibility analyses for major fixed-guideway transit planning initiatives. This paper uses one such sketch planning tool produced by Transit Cooperative Research Program (TCRP) Report 167 to explore ridership potential along two light rail corridors in the City of Austin. Planners recently completed a planning process for an initial segment of urban rai in central Austin that was ultimately defeated by voters in a 2014 bond election called to fund the project. The ridership results produced by the Report 167 model corroborate some claims made by transit advocates who opposed Proposition 1 that the highest ridership route was not advanced to voters in the election. By using a sketch planning tool to compare ridership along the ill-fated Project Connect route to a route advocated by critics of the process, this paper also provides insight into the role that sketch planning can play in the transit planning process, both generally and in the context of rail planning efforts in Austin.Item Building BRIDGES : combining analogy and category learning to learn relation-based categories(2010-05) Tomlinson, Marc Thomas; Love, Bradley C.; Echols, Catharine H.; Loewenstein, Jeffrey; Markman, Arthur B.; Porter, Bruce W.The field of category learning is replete with theories that detail how similarity and comparison based processes are used to learn categories, but these theories are limited to cases in which item and category representations consist of feature vectors. This precludes these methods from learning relational categories, where membership is determined by the structured relations binding the features of a stimulus together. Fortuitously, researchers within the analogy literature have developed theories of comparison that account for this structure. This thesis bridges the two approaches, describing a theory of category learning that utilizes the representational frameworks provided by the analogy literature to learn categories that may only be described through the appreciation of the structured relations within their members. This theory is formalized in a model, Building Relations through Instance Driven Gradient Error Shifting (BRIDGES), that shows how relational categories can be learned through attention-driven analogies between concrete exemplars. This approach is demonstrated through several simulations that compare similarity-based learning and alternatives, such as rule-based abstractions and re-representation. We then present a series of experiments that explore the reciprocal impact of relational comparison on category structure and category structure on relational comparison. This work provides a theoretical framework and formal model suggesting that feature-based and relation-based categories are a continuum that are learned through selective attention and similarity-based comparison.Item Camouflage detection & signal discrimination : theory, methods & experiments(2022-05-05) Das, Abhranil; Geisler, Wilson S.; Reichl, L. E.; Florin, Ernst-Ludwig; Marder, MichaelCamouflage is an amazing feat of evolution, but also impressive is the ability of biological visual systems to detect them. They are the result of an evolutionary arms race that exposes many detection strategies and their limits. In this thesis, we investigate the principles of human detection of maximally-camouflaged objects, i.e. whose texture exactly mimics the background texture. Chapter 1 introduces and contextualizes the problem. In chapter 2, we develop a theory and model that extracts the relevant information in the image, and uses biologically plausible computations on them for detection. In chapter 3, we present a series of experiments which measured human camouflage detection ability along different dimensions of the task, such as across different textures and shapes. Chapter 5 is a reference on some methods and analysis used in the study. Chapter 6 describes mathematical methods and software on statistical signal discrimination that we developed to solve questions in visual detection, but with wider applications in other fields.Item Clay-based materials for passive control of ozone and reaction byproducts in buildings(2016-05) Darling, Erin Kennedy; Corsi, Richard L.; Brown Wilson, Barbara; Juenger, Maria; Novoselac, Atila; Xu, YingTropospheric ozone that infiltrates buildings reacts readily with many indoor materials and compounds that are commonly detected in indoor air. These reactions lead to lower indoor ozone concentrations. However, the products of ozone reactions may be irritating or harmful to building occupants. While active technologies exist (i.e., activated carbon filtration in HVAC systems) to suppress indoor ozone concentrations, they can be costly and/or infeasible for dwellings that do not have these systems. Passive methods of ozone removal are an interest of building environment researchers. This dissertation involves (1) a review of the state of the knowledge on building materials and coatings that are intended to passively remove indoor ozone, especially clay-based materials; (2) a compilation of current data on ozone removal and reaction byproduct formation for these materials; (3) a model for ozone removal effectiveness for a selected clay-based material that is implemented in a hypothetical home; (4) a survey of the effects of a clay-based coating with and without ozone and a reactant source on human perceptions of air quality; (5) an investigation of the long-term potential for passive control of indoor ozone by two different clay-based surface coatings that were exposed to real indoor environments; and (6) development of a location-specific model to estimate the monetary benefits versus costs of indoor ozone control using passive removal materials. The above tasks were completed through ongoing reviews of the literature, experimental studies conducted in small and large environmental chambers, and in the field. Results of these studies suggest that clay or materials made from clay are a viable material for passive reduction of indoor pollution, due in part to clay’s ability to catalyze ozone. Human sensory perceptions of indoor air quality were shown to significantly improve when a clay-based plaster was present in an ozonated environment. Based on modeling efforts, effective passive removal of indoor ozone is possible for realistic indoor scenarios when clay-based materials are implemented. There is a growing number of papers that are published on the subject of clay materials and indoor environmental quality, but few that investigate the longer term impacts and performance of clay materials, especially ones that have been exposed to real indoor environments.Item Composite Modeling and Analysis of FDM Prototypes for Design and Fabrication of Functionally Graded Parts(2001) Li, Longmei; Bellehumeur C., Sun; Gu, P.Solid Freeform Fabrication technologies have potential to manufacture parts with locally controlled properties (LCP), which would allow concurrent design of part’s geometry and desired properties. To a certain extent, Fused Deposition Modelling (FDM) has the ability to fabricate parts with LCP by changing deposition density and deposition orientation. To fully exploit this potential, this paper reports a study on the mechanical properties of FDM prototypes, and related materials and fabrication process issues. Both theoretical and experimental analyses of mechanical properties of FDM parts were carried out. To establish the constitutive models, a set of equations is proposed to determine the elastic constants of FDM prototypes. An example is provided to illustrate the model with LCP using FDM.Item Computational modeling of high pressure plasmas for plasma assisted combustion, liquid reforming and thermal breakdown applications(2019-01-22) Sharma, Ashish, 1990-; Raja, Laxminarayan L.; Varghese, Philip L; Goldstein, David B; Bisetti, Fabrizio; Hallock, Gary AThe goal of the present work is to study high pressure non-equilibrium plasma discharges in chemically reactive systems. In this work, we present coupled computational studies of high pressure nanosecond pulsed plasmas for multiphysics applications ranging from plasma assisted combustion ignition, large gap thermal breakdown, to electric discharge in liquids for fuel reforming and biomedical applications. In the first part of the work, we report the results of a computational study which explores argon surface streamers as a low-voltage mechanism for thermal breakdown of large interelectrode gaps and investigate the effect of impurities (molecular oxygen) on the development of continuous surface streamer channels under atmospheric-pressure conditions. In pure argon, a continuous conductive streamer successfully bridges the gap between two electrodes indicating high probability of transition to arc. Presence of oxygen impurities in small concentrations (less than 5%) is found to be conducive to streamer induced thermal breakdown as it reduces the threshold voltage of streamer formation and minimizes unwanted streamer branching effects while maintaining a high probability of streamer to arc transition. Higher oxygen impurity levels > 5% are found to significantly deteriorate the continuous conductivity of streamer channel and lead to a much lower probability for transition to thermal arcs. In the second part of the work, we present a computational study of nanosecond streamer discharges in helium gas (He) bubbles suspended in distilled water (H₂O) for liquid reforming applications. The model takes into account the presence of water vapor in the gas bubble for an accurate description of the discharge kinetics. The objective is to study the kinetics and dynamics of streamer evolution and maximize active species production within the gas bubbles which is the quantity of interest for plasma processing of liquids. We investigate two parameters, namely a) trigger voltage polarity and b) the presence of multiple bubbles, which are found to significantly influence the characteristics of the discharge in gas bubbles. A substantial difference is observed in initiation, transition and evolution stages of streamer discharge for positive and negative trigger voltages. The volumetric distribution of species in the streamer channel is more uniform for negative trigger voltages on account of the formation of multiple streamers. In case of the presence of more than one gas bubble, we see the phenomenon of streamer hopping between bubbles where the high electric field in the sheath of the first bubble triggers the streamer discharge in the adjacent bubble. The presence of multiple immersed bubbles reduces the breakdown voltage of the plasma discharge and results in more uniform generation of active species. It is concluded that a negative pin trigger with multiple immersed gas bubbles maximizes the active species generation which is conducive to plasma assisted liquid reforming applications. In the final part of the work, a coupled two-dimensional computational model of nanosecond pulsed plasma induced flame ignition and combustion for a lean H₂ – air mixture in a high pressure environment is described. The model provides a full fidelity description of plasma formation, combustion ignition, and flame development. We study the effect of three important plasma properties that influence combustion ignition and flame propagation, namely a) plasma gas temperature, b) plasma-produced primary combustion radicals O, OH, and H densities, and c) plasma-generated charged and electronically excited radical densities. Preliminary zero-dimensional studies indicate that plasma generated trace quantities of O, OH and H radicals drastically reduces the ignition delay of the H₂ – air mixture and becomes especially important for high pressure lean conditions. Multi-dimensional simulations are performed for a lean H₂ – air mixture (φ=0.3) at 1 and 3.3 atm and a range of initial tem- perature from 1000 - 5000 K. The plasma is accompanied by fast gas heating due to N₂ metastable quenching that results in uniform volumetric heating in the interelectrode gap. The spatial extent of the high temperature region generated by the plasma is a key parameter in influencing ignition; a larger high temperature region being more effective at initiating combustion ignition. Plasma generation of even trace quantities (∼ 0.1%) of primary combustion radicals, along with plasma gas heating, results in a further fifteen-fold reduction in the ignition delay. The radical densities alone did not ignite the H₂ – air mixture. The generation of other plasma specific species results only in a slight ∼ 10 % improvement in the ignition delay characteristics over the effect of primary combustion radicals, with the slow decaying ions (H₂⁺, O₂⁻, O⁻ ) and oxygen metastable species (O₂ [superscript a1], O₂ [superscript b1], O₂ [superscript *]) primarily contributing to com- bustion enhancement. These species influence the ignition delay, directly by power deposition due to quenching, attachment and recombination reactions, and indirectly by enhancing production of primary combustion radicals.Item Computational studies of electron transport and reaction rate models for argon plasma(2010-08) Min, Timothy T.; Raja, Laxminarayan L.; Hallock, GaryA validation study was performed on a capacitively coupled argon discharge to determine the most suitable models for chemistry and electron transport. Chemical reaction rate and electron transport models choices include equilibrium or non-equilibrium electron EDFs. Experimental studies performed by our collaborative partners in the Colorado School of Mines. Conditions for the studies are 138, 315, and 618 mTorr where the cycle averaged power varied at 20, 50, and 80 Watts in which the voltage supply was driven at 13.56 MHz. Simulations were performed using pressures and voltage used in experiments. The most accurate case was for 138 mTorr at 50 Watts using a non-Maxwellian EDF based chemistry (called Bolsig+ chemistry) and a constant electron momentum transfer cross section of 20 Angstroms which was computed from Boeuf’s paper; this model accurately modeled power deposition to within 2.6%. Furthermore, species number densities, electron temperature, and sheath thicknesses are obtained. Using Bolsig+ chemistry resulted in 20,000K higher electron temperatures than using Arrhenius chemistry rates. Results indicate that power deposition occurs due to electrons gaining energy from the sheath which in turn bombard neutral species producing metastable argon.Item Computer modeling of the instructionally insensitive nature of the Texas Assessment of Knowledge and Skills (TAKS) exam(2009-08) Pham, Vinh Huy, 1979-; Stroup, Walter M.Stakeholders of the educational system assume that standardized tests are transparently about the subject content being tested and therefore can be used as a metric to measure achievement in outcome-based educational reform. Both analysis of longitudinal data for the Texas Assessment of Knowledge and Skills (TAKS) exam and agent based computer modeling of its underlying theoretical testing framework have yielded results that indicate the exam only rank orders students on a persistent but uncharacterized latent trait across domains tested as well as across years. Such persistent rank ordering of students is indicative of an instructionally insensitive exam. This is problematic in the current atmosphere of high stakes testing which holds teachers, administrators, and school systems accountable for student achievement.Item Computer tools for designing self-sufficient military base camps(2012-08) Putnam, Nathan Hassan; Seepersad, Carolyn; Webber, Michael E., 1971-; Campbell, Matthew; Morton, David; Novoselac, AtilaMilitary Forward Operating Base Camps (FOBs) support and enable sustained military operations abroad by providing safe locations for soldiers and supporting contractors to eat, sleep, and maintain personal hygiene. FOBs need some amount of energy and water to provide these services but are often located in austere environments that do not have access to grid utilities. Off-grid FOBs are not self-sufficient; they are dependent on supply chains for the services they provide to camp occupants. The challenge of supplying FOBs with fuel and water and removing waste (resource resupply and waste removal comprise logistical requirements) is associated with very high human, monetary, strategic, and environmental costs. There are many research efforts across the U.S. Department of Defense (DoD) that seek to reduce FOB logistical requirements, but it is currently very difficult to identify the research efforts that are most beneficial to DoD goals. There are also many factors that make designing FOBs to be more self-sufficient challenging including varying missions, environments, and legacy equipment at currently-fielded FOBs, a lack of baseline data on FOB logistical requirements, an unclear relationship between design changes and resource use behavior, and an unclear valuation of saved resources. This research seeks to develop computer tools and contribute to a methodology that can be used to design FOBs that are more self-sufficient. More self-sufficient FOBs provide high quality services to occupants but do so with mitigated logistical requirements. To this end, a detailed computer model of specific type of FOB (a single 150-person Force Provider module) is developed, and baseline levels of resource requirements are established. Potentially resource-saving devices and other design changes are incorporated into the FOB model and simulated to assess each design change's effect on resource use and waste production. Then, estimated resource savings are weighed against required investment for each design change to arrive at design recommendations. The results of this research effort are specific design recommendations for making the Force Provider system more self-sufficient, as well as computer tools and a methodology that are applicable to other off-grid habitation redesign problems.Item Conquering the charity stripe : a literature review on the biomechanics of free throw shooting(2021-07-24) Williams, Edward Joseph, M.S. in Kinesiology; Hsiao, Hao-YuanBasketball is one of the most popular sports on the planet and free throws are vital component of the game. This literature review aims to assess the existing literature to identify key performance indicators for successful free throw trajectory and the biomechanics of the free throw motion that generate such indicators. Specifically, this review addresses mathematical and computer-generated models regarding free throw shooting trajectory and biomechanical analyses that utilized motion capture. Several motor learning principles are considered in the analysis as well, such as Gentile’s taxonomy of motor skills, Bernstein’s degrees of freedom problem and individual variability. Modeling studies have shown that free throw success is remarkably sensitive to release velocity of the ball. Three other crucial variables were identified as well: release height, release angle and backspin. Biomechanical analyses showed that intersegmental coordination is crucial for success, particularly in the upper arm. Postural control, balance and stability are important as well. However, individual movement patterns can differ significantly and there is some degree of movement variability, even in experts. Therefore, individual analysis is warranted for different players. There are notable gaps in our current understanding of the free throw motion. While the upper extremity is frequently assessed in detail, details regarding the lower extremity are lacking and any relationship between the two is largely ignored. Although postural variables were revealed to play a significant role in consistent success, they are infrequently assessed. Application of models and biomechanical assessments to skill improvement has not yet been investigated in the literature and would be an ideal future direction for this line of research. Future studies should seek to assess the whole body as a unit, rather than the largely segmental approaches utilized thus far. More advanced kinetic data and force plate analysis should be explored by future investigators as well.Item Design, modeling, and control of a roll-to-roll mechanical transfer process for two-dimensional materials and printed electronics(2022-06-08) Zhao, Qishen; Li, Wei (Of University of Texas at Austin); Chen, Dongmei, Ph. D.; Djurdjanovic, Dragan; Liechti, Kenneth M.Flexible electronics, as an emerging field, has gained tremendous attention over the past few years with the advancement in areas such as two-dimensional (2D) materials fabrication and transfer printing techniques. Mechanical peeling, where thin film materials or printed patterns are transferred from a donor substrate to a target substrate, is demonstrated to be a promising and key operation to transfer 2D material or fabricating complex flexible electronic devices, and it is shown that in many cases performing the mechanical peeling process at a desired peeling condition is needed for high quality product. However, despite the promise of mechanical peeling techniques, studies on scaling up the process and enabling the process in a high-volume manufacturing setting are lacking. In this study, a R2R mechanical peeling process that enables continuous and high-throughput transfer of 2D materials and printed electronics has been developed. The system allows for speed and tension control and is used for performing 2D materials transfer. A system model of the R2R process is derived by integrating the peeling process with the R2R system dynamics. The proposed model provides fundamental understanding of the physics involved in the process, including the interactions between peeling front and the roller dynamics. The model can be effectively used for control design and simulation. The success of the R2R peeling process is dependent on the peeling front geometry and its stability during the peeling process. A real-time supervisory control strategy is developed to enable the peeling angle control in a R2R mechanical peeling process. The supervisory control strategy utilizes a peeling front model to estimate the peeling speed and the adhesion energy between the donor substrate and the material to be transferred. The information is used to generate reference signals for the web tension controllers at the regulatory level to adjust the web tensions in order to achieve desired peeling angles. The proposed control strategy is demonstrated with both simulation and experimental results. To reject periodic disturbances originating from rotating roller shafts and adhesion energy changes in the laminate, a model-based repetitive controller is developed and demonstrated.Item Determining predictors of response to ambulatory pharmacist-led diabetes care(2020-05-08) Palka, Samuel James; Reveles, Kelly Renee; Davidson, DeWayne A; Koeller, JimPurpose: There is a lack of guidance in referring patients to the clinical pharmacist for diabetes management, which likely results in patients missing out on this beneficial service. It would be useful to know which patients and specific clinical interventions are most likely to show benefit from pharmacy services. To our knowledge, only one study has assessed patient predictors of response to diabetes care provided by a clinical pharmacist, which was limited to baseline variables. Therefore, the primary objective was to describe clinical responses to pharmacist-led diabetes care and to identify baseline and interventional variables that are independently predictive of clinical response. Methods: This was a retrospective cohort study using patient data from two health systems in San Antonio, Texas. Included patients were ≥18 years old with a referral to the pharmacist for Type 2 Diabetes management. Patients were followed for up to 6 months and data were collected at baseline, during follow-up, and at the end of the study. Clinical response was defined as a reduction in the A1C from baseline by ≥1% or meeting the documented A1C goal. Non-responders failed to meet these A1C goals. Variables with P<0.20 on bivariate analysis were included in the multiple variable logistic regression model to determine predictors of response. Results: A total of 180 patients were included. Overall, patients were predominantly female (63%) and obese (58%) with a disease duration ≥10 years (67%). The median (IQR) change in A1C from baseline for responders and non-responders was -2.2% (-3.7 to 1.3) and 0.4% (-0.4 to 1.05) (P<0.001), respectively. Sixty-six percent of patients were considered responders. Significant predictors of response included baseline A1C (OR 1.41; 95% CI 1.08-1.85), number of completed visits with both the physician (OR 0.69; 95% CI 0.49-0.96) and the pharmacist (OR 1.65; 95% CI 1.03-2.64), and medication optimization (OR 10.7; 95% CI 1.04-109.9). Conclusion: Pharmacists are effective in diabetes management. Specifically, more visits with the pharmacist and utilizing medication optimization are especially helpful in lowering the A1C. Higher baseline A1C values are also predictive of response and should be incorporated into new protocols for pharmacist management of diabetes.Item Development and analysis of stretchable electronics in biopotential monitoring(2016-05) Nicolini, Luke Robert; Lu, Nanshu; Djurdjanovic, DraganIn this Thesis, stretchable electronics are studied and developed, with a focus on the epidermal monitoring of biopotentials for healthcare and other applications. Conventional manufacturing processes for stretchable electronics are time and cost intensive. A novel manufacturing method to create stretchable electronics is developed, in which a cutter plotter is used to directly shape thin metal films, in order to produce stretchable designs. The limits of the manufacturing process are investigated and recorded, both in terms of the cutter plotter capabilities and in the use of different materials and substrates for the thin-film device. The thin, stretchable devices are also tested in a wide variety of data collection situations, including measuring of a variety of biopotentials including ECG, EMG, and EEG. The new Epidermal Sensor Systems created with the Cut-and-Paste manufacturing method perform equal to or better than conventional electrodes. Thus the cut-and-paste method is determined to be a novel and more cost effective method to produce stretchable sensors. Stretchable sensors we produce can match the thickness and mechanical stiffness of human epidermis, and can hence be laminated and fully conformed on human skin like a temporary transfer tattoo for long-term biopotential monitoring including electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG). Such epidermal sensors have enabled the investigation of muscle fatigue and recovery over time. An Autoregressive Moving Average (ARMAX) model is developed in order to map between forearm flexor muscle EMG and the grip force of the corresponding hand. The fit of this model is tracked over the course of fatigue, and changes in the model are analyzed to provide useful trends with which to measure and follow muscle fatigue patters. The epidermal sensor is found to be equivalent to conventional electrodes for muscle fatigue monitoring, while being more comfortable and durable. Further, the ARMAX modeling procedure is proven to have useful results in terms of modeling of forearm muscle fatigue. Overall, this research contributes to the field of stretchable electronics and their applications for biopotential monitoring.