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Title: Reconditioning Dharavi: A Toolkit of Strategies for Incremental Development
Creator: Bhogle, Saylee Deepak
Date: 2022
Description: The 2003 Global Report on Human Settlements (Un-Habitat, 2003) defines a "slum" as a densely populated metropolitan area that is distinguished...
Show moreThe 2003 Global Report on Human Settlements (Un-Habitat, 2003) defines a "slum" as a densely populated metropolitan area that is distinguished by a variety of low-income settlements, subpar housing, and squalor. Dharavi, on the other hand, is far more than a "slum." In the heart of Mumbai, Dharavi is an economically prosperous and socially active informal town. Mumbai is a thriving metropolis with many different realities and patterns, even though it appears to be a slum filled with squatters. However, the region has recently become a hub for informal settlements and urban problems associated with poor hygiene in developing countries. People’s misconceptions about Dharavi stem from a failure to recognize its social capital and economic power: the area encompasses a variety of economic networks, production types, income levels, land tenure arrangements, and religious activities and festivities. Dharavi is made up of 85 separate groups with a strong feeling of belonging and high expectations for stability and improved economic position and living standards. It is also clear that these folks are capable of building and enhancing their shelter if they have the resources to do so. To develop all these qualities, Dharavi's Social Capital must be recognized and promoted as an asset to the city of Mumbai. A community such as Dharavi requires ‘urban acupuncture’; where mediation of the littlest kind will have the greatest effect. Dharavi, like any other "Informal" city, requires rigorous examination to be fully comprehended. It is a unique location where a large flood of migrants has managed to build jobs and their city. My underlying attitude to this location is a conflicting desire to save and replace it. The desire to save is linked to the aesthetic of informality as well as the intense sociality, diversity, and production of the streets and lanes - a fascinating and diversified urban ensemble. The desire to eliminate stems from hopeless states of sterilization, ventilation, light, open space, and congested areas. As a result, a reliable strategy for combining the two methodologies and locating a functioning arrangement should be developed. The government has been trying to redevelop this area for the past 50 years but hasn’t been successful in doing so. In contrast to the existing redevelopment plan, which promotes uniform top-down development, my concept anticipates techniques for progressive self-development, including "bottom-up" finance models and architectural approaches. After identifying various patterns and carefully examining behavior patterns, production systems, and existing community facilities, a toolkit of methods can be built that can be used in various places and "outboxes." The simple homogeneity of solutions for Dharavi's changing conditions has been avoided. Dharavi's current identity and "mixed-use" paradigm have been respected, with Home recognized as an instrument of production. The proposed design has been tested for various environmental factors using different tools for natural lighting and ventilation. The outdoor areas are also analyzed for thermal comfort since a lot of social activities take place in these areas. Communal areas have been designed to accommodate micro infrastructure systems while also increasing productivity. As a result, a system of self-development triggers has been created that can improve present conditions while also supporting the community's need for stability. Simultaneously, by focusing on property ownership as an economic driver, the proposed approach can provide a type of "social mobility" for Dharavi's residents.
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Title: Population dynamics and pathogens of the western bean cutworm (Striacosta albicosta)
Creator: Bunn, Dakota C.
Date: 2022
Description: Understanding an herbivorous pest’s population dynamics is necessary to ensure proper integrated pest management strategies are being...
Show moreUnderstanding an herbivorous pest’s population dynamics is necessary to ensure proper integrated pest management strategies are being developed and used. The western bean cutworm is a pest of both corn and dry beans that is understudied and difficult to manage due to its nocturnal lifestyle, adaptation to current management techniques and a general lack of understanding regarding its population structure. Our studies focused on the effects of host plant and pathogens on western bean cutworm population structure and found that mainly adults which developed on corn are contributing to the next generation of western bean cutworm in Michigan, making corn and dry beans unsuitable as co-refuges in insecticide resistance management strategies.We also found a 100% prevalence of the Nosema sp. in the adult population of western bean cutworm in Michigan. This prevalence, when paired with the consistent crop damage caused annually by the western bean cutworm, which confirms an abundance of cutworms are present, suggests the infection is slow acting and non-lethal to its host. Following sequencing, assembly, and annotation of the Nosema sp. genome, we were unable to provide a reason for the Nosema sp.’s low virulence, however, we were able to confirm the presence of all 6 polar tube proteins. Upon further examination of the Nosema sp. genome we were able to determine that it is a true Nosema with genome size of ~9.57 Mbp (~20% of which are transposable elements), which is within the typical range for this genus.
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Title: Carrier phase multipath characterization and frequency-domain bounding
Creator: Benz, Chloe
Date: 2022
Description: Safely relying on Global Navigation Satellite Systems (GNSS) measurements for position estimation using multi-sensor navigation algorithms,...
Show moreSafely relying on Global Navigation Satellite Systems (GNSS) measurements for position estimation using multi-sensor navigation algorithms, especially in critical phases of flight – such as takeoff or landing – requires precise knowledge of the errors affecting position estimates and their extrema values at any time. This work investigates a method for characterization and power-spectral density (PSD) bounding of GNSS carrier phase multipath error intended for use in sensor fusion for aircraft navigation. In this dissertation, two methods of GNSS carrier phase multipath characterization are explored: single frequency dual antenna (DA) and single antenna dual frequency (DF). However, since not all aircraft are equipped with multiple GNSS antennas, because the DA method entails a meticulous tracking of the lever arm between the two antennas, and as multipath seen by two antennas in a short baseline configuration may cancel out, the DF method is preferred and is the main emphasis of this work. By subtracting carrier phase measurements collected by a receiver overtwo distinct frequencies, a composite measurement containing ionospheric delay and carrier phase multipath is obtained. The ionospheric delay has slower dynamics than multipath, so it is removed using a high pass filter. The filter cutoff frequency is carefully picked based on a study of ionospheric delay dynamics. The DF method is validated on a rooftop GPS carrier phase dataset, and finally, directions and considerations for its ultimate intended use on airborne collected GNSS carrier phase data are provided.
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Title: KERNEL FREE BOUNDARY INTEGRAL METHOD AND ITS APPLICATIONS
Creator: Cao, Yue
Date: 2022
Description: We developed a kernel-free boundary integral method (KFBIM) for solving variable coefficients partial differential equations (PDEs) in a...
Show moreWe developed a kernel-free boundary integral method (KFBIM) for solving variable coefficients partial differential equations (PDEs) in a doubly-connected domain. We focus our study on boundary value problems (BVP) and interface problems. A unique feature of the KFBIM is that the method does not require an analytical form of the Green’s function for designing quadratures, but rather computes boundary or volume integrals by solving an equivalent interface problem on Cartesian mesh. We decompose the problem defined in a doubly-connected domain into two separate interface problems. Then we evaluate integrals using a Krylov subspace iterative method in a finite difference framework. The method has second-order accuracy in space, and its complexity is linearly proportional to the number of mesh points. Numerical examples demonstrate that the method is robust for variable coefficients PDEs, even for cases when diffusion coefficients ratio is large and when two interfaces are close. We also develop two methods to compute moving interface problems whose coefficients in governing equations are spatial functions. Variable coefficients could be a non-homogeneous viscosity in Hele-Shaw problem or an uptake rate in tumor growth problems. We apply the KFBIM to compute velocity of the interface which allows more flexible boundary condition in a restricted domain instead of free space domain. A semi-implicit and an implicit methods were developed to evolve the interface. Both methods have few restrictions on the time step regardless of numerical stiffness. Theyalso could be extended to multi-phase problem, e.g., annulus domain. The methods have second-order accuracy in both space and time. Machine learning techniques have achieved magnificent success in the past decade. We couple the KFBIM with supervised learning algorithms to improve efficiency. In the KFBIM, we apply a finite difference scheme to find dipole density of the boundary integral iteratively, which is quite costly. We train a linear model to replace the finite difference solver in GMRES iterations. The cost, measured in CPU time, is significantly reduced. We also developed an efficient data generator for training and derived an empirical rule for data set size. In the future work, the model could be expanded to moving interface problems. The linear model will be replaced by neural network models, e.g., physics-informed neural networks (PINNs).
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Title: PROGRAM SURVIVABILITY THROUGH K-VARIANT ARCHITECTURE
Creator: BEKIROGLU, BERK
Date: 2021
Description: Numerous software systems, particularly mission and safety-critical systems, require a high level of security during their execution....
Show moreNumerous software systems, particularly mission and safety-critical systems, require a high level of security during their execution. Enhancing software security through architecture is a highly effective method of defending against cyberattacks. The N-version is a software architecture that was developed to increase the security of software systems. In the N-version architecture, functionally equivalent versions of a program run concurrently to complete a mission or task. Each version is developed independently by a different team using only the software specifications in common. As a result, each version is expected to contain unique vulnerabilities. Due to the high cost of developing and maintaining an N-version system, this architecture is typically used only in high-budget projects requiring a high-security level. The K-variant, an alternative architecture for enhancing system security, is explained and analyzed in this thesis. In contrast to the N-version architecture, each variant is automatically generated using source-to-source program transformation techniques. Automation significantly reduces the cost of developing variants in the K-variant architecture. The K-variant architecture can help protect systems from memory exploitation attacks. Various attack strategies can be used against K-variant systems in order to increase the likelihood of a successful attack. Various attack strategies are proposed and investigated in this thesis. Furthermore, experimental studies are being conducted to investigate various defense mechanisms against proposed attack strategies. The effectiveness of each defense mechanism against various attack strategies is evaluated by using a metric of the probability of an unsuccessful attack. Additionally, various source code program transformation techniques for generating new variants in the K-variant architecture have been proposed and investigated experimentally. This thesis also describes a machine learning technique for estimating the survivability of K-variant systems under various attack types and defense strategies. To make the design of K-variant systems easier, a neural network model is proposed. With the developed tool that utilizes the neural network model, fast and accurate predictions about the survivability of K-variant systems can be obtained.
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Title: ESTIMATES OF AIR EXCHANGE RATES THROUGH THE USE OF TOTAL VOLATILE ORGANIC COMPOUND DECAY MEASUREMENTS
Creator: Bradley, Christopher
Date: 2021
Description: Indoor air exchange rates are commonly used to assess the overall fitness of a building and assess its performance. More recently, air...
Show moreIndoor air exchange rates are commonly used to assess the overall fitness of a building and assess its performance. More recently, air exchange has become a concern due to the COVD-19 pandemic, requiring replacement air to ensure safety; especially so considering that humans spend much of their time indoors. Building science has focused on air exchange to quantify needs for thermal loads, balancing the overall tightness of a building with the amount of energy consumed. Moreover, guidelines have been created by several different organizations to maintain adequate ventilation to remove indoor air pollution, replacing it with clean outdoor air. Research focuses on how to maintain a comfortable and safe quality of indoor air while balancing the needs of the energy crisis.When installed with proper HVAC systems, air exchange rates can be set to a recommended value based upon the conditions of the environment. Buildings without mechanical ventilation face another issue, mainly that they only rely on natural ventilation and the infiltration rate. Temperature differences between the indoor and outdoor environment and the condition of wind speed and direction create pressure differences across the building envelope, influencing the infiltration rate, which can change the amount of air exchange in buildings with natural or mechanical ventilation. Currently, air exchange rates are commonly measured using tracer gases. More frequently used gases have included perfluorocarbon, sulfur hexafluoride, and carbon dioxide, though none of these have proven to be ideal tracers. Alongside this, cost and burden on the participants of these studies often limit the amount of measurements made. Numerous studies have been conducted on how to model the air exchange rate by the changes in concentrations, but accuracy depends on the amount of information available. Other attempts have been made to characterize buildings by their infiltration rate to make estimations, but other questions have arisen about the accuracy of these methods. Due to their ubiquity in indoor environments, volatile organic compounds have been suggested as a plausible tracer gas for measuring air exchange rates. The plausibility of this method raises questions, such as their behavior within the indoor environment, their ability to be measured and the cost to measure concentrations, and the analytical requirements to characterize the rates of removal as air exchange rates. However, due to the rapid increase of available technology in low cost, lightweight, high-resolution sensors, this novel method of using VOCs, especially indicators of total VOCs (TVOCs), may prove fruitful in measuring air exchange within specific microenvironments. Analysis of time-series TVOC concentration measurements taken from a study conducted in multiple residences was conducted to investigate the feasibility of using these measurements, and especially naturally occurring elevation and decay periods, as a proxy for calculating air exchange rates. Though the removal rates of these compounds fell within the range of typical air exchange rates for residential spaces, the results of this analysis suggest the method has potential but with limitations, including the unknown behavior of the individual compounds comprising TVOC measurements within the space, proximity and mixing effects, and potentially invalid comparisons to air exchange rates given from a LBLX model rather than simultaneous tracer gas tests. Future work should explore simultaneous use of TVOC measurements alongside conventional tracer gas testing to further explore the potential utility of such methods.
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Title: INTELLIGENT STREET LIGHTING AND REMOTE POWER UNITS AS CASE STUDIES FOR CITIES TO DECARBONIZE
Creator: Burgess, Patrick G.
Date: 2022
Description: There is a scientific consensus that atmospheric warming caused by the release of emissions will reach critical levels in our lifetime if...
Show moreThere is a scientific consensus that atmospheric warming caused by the release of emissions will reach critical levels in our lifetime if significant efforts are not made to decarbonize our buildings and power grid. The City of Los Angeles is a prime example of the challenges of decarbonizing, balancing global, federal, and state policies and issues and addressing environmental justice. The first research case studies of the details and challenges of decarbonization efforts include the implementation of the first networked light-emitting diode (LED) streetlights in the city of Chicago on IIT’s campus to improve the reliability and economics of its main campus, 2.5 mi south of downtown Chicago. Research shows that these networked LED streetlights greatly reduce a city's rising energy costs, but the CSMART project team has set out to prove the benefits of integrating an intelligent communications and control system with an existing smart grid infrastructure, such as an existing network and supervisory control and data acquisition (SCADA) systems. In addition to assessing the economic and environmental drivers for the intelligent streetlight solution, the project team is dedicated to assessing the potential cybersecurity vulnerabilities of such a system and working to mitigate or eliminate them. The second research case study covers off-grid remote power units providing continuous illumination for safer streets and safer driving that is unaffected by power outages. Thanks to individual lighting control potentially allowing for dimming, blinking, and even color changing, streetlights powered by RPUs can be used as emergency signaling devices, directing traffic during a city evacuation or other emergency. The RPU control and monitoring can be accessed through the cloud, thereby avoiding reliance on local servers.
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Title: Assessing the Impact of Understanding Nature of Scientific Knowledge and Understanding Nature of Scientific Inquiry on Learning about Evolution in High School Students
Creator: Jimenez Pavez, Juan Paulo
Date: 2022
Description: Nature of Scientific Knowledge (NOSK) and Nature of Scientific Inquiry (NOSI) are important components of scientific literacy and important...
Show moreNature of Scientific Knowledge (NOSK) and Nature of Scientific Inquiry (NOSI) are important components of scientific literacy and important educational objectives in science education. Recent literature theorizes that understanding both NOSK and NOSI increases students' understanding of science content knowledge. However, this assumption has yet to be tested empirically. Much research has been done on developing informed views of NOSK and NOSI for students in kindergarten through twelfth grade, but research on the effect of understanding NOSK and NOSI on facilitating science learning in high school appears limited.The main purpose of this study was to empirically test the assumption that understanding NOSK and NOSI improves science student content learning, in particular learning about evolution. This study also aimed to determine which NOSK and NOSI aspects are most useful in such an endeavor. Using a quasi-experimental, nonequivalent control group design, a sample of 453 9th grade high school students from 12 classes in a large Chilean city were randomly assigned to intervention and control groups via classroom clusters (Intervention groups = 6, Control groups = 6). Students in the intervention groups were given a special online explicit and reflective five-week NOSK/NOSI Unit, followed by an online five-week Evolution Content Unit, as a treatment. Those in the control groups received only the online five-week Evolution Content Unit. To measure understanding of NOSK, understanding of NOSI, and understanding about evolution, students answered three valid and reliable instruments: The Views of Nature of Science (VNOS D+), the Views about Scientific Inquiry (VASI), and a multiple-choice Evolution Content Test. The students' answers to the VNOS D+ and VASI questionnaires were scored as naive, mixed, or informed according to the level of understanding for each aspect, and the answers to the evolution content test were scored as correct or incorrect. The results of this study showed that the NOSK/NOSI Unit was effective in improving understanding of NOSK and NOSI aspects in the intervention groups. The results also showed that the Evolution Content Unit was effective in improving understanding about evolution in both groups. However, students in the intervention groups outperformed their peers in the control groups by scoring higher on the Evolution Content Test. Further analysis revealed that students with informed views of NOSK and NOSI achieved better scores on the Evolution Content Test than students with naive views, supporting the argument that understanding NOSK and NOSI facilitates learning about evolution. In addition, all aspects except for the difference between Theories and Laws (NOSK) had a significant positive impact on learning about evolution. Taken together, the findings of this dissertation support the assumption that understanding NOSK and NOSI improves learning about evolution. Furthermore, most NOSK and NOSI aspects seem to foster understanding about evolution. These are new insights, especially about the importance of understanding NOSI for learning about evolution. Some limitations for this study include the remote context in which the study took place and the potential bias in the qualitative analysis of the VNOS D+ and VASI questionnaires.
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Title: Efficiency of Carbon Fiber Composite Structural Systems for Tall Buildings: A Parametric Simulation Based Framework for Finite Element Analysis
Creator: Khairnar, Piyush Rajendra
Date: 2022
Description: The rate of global urban migration has increased drastically over the last century. With increasing population, the need for dense urban...
Show moreThe rate of global urban migration has increased drastically over the last century. With increasing population, the need for dense urban habitats is growing. Tall buildings are at the forefront of this growth and changing skyline of different cities around the globe is evident. The Structural system is an important and critical component of any tall building. Structural material can significantly impact the performance of a structural system as well as the way it is constructed. Carbon composite is known for its high strength and stiffness, also it is a lightweight structural material. Current industrial techniques allow for manufacturing of structural components made of carbon composite to be used in building structures. Carbon composite as a structural material shows potential to be used in tall buildings where strength and stiffness requirements are a key parameter.This research focuses on applications of Carbon Composite, also known as Carbon Fiber Reinforced Polymer (CFRP), as a structural material for tall buildings. The research aims to study the properties of carbon composite as a structural material and to explore its application in the structural system for tall buildings. Mechanical properties of CFRP such as strength, stiffness, etc. are studied with available literature to assess the potential of the material to be used in the design of structural system for tall buildings. Manufacturing processes along with fabrication methods are also studied to investigate the constructability using CFRP. The research draws attention on the issues of connectivity within CFRP structural components as well as performance of CFRP as a structural material in tall building structural systems. Computer based simulations are utilized to develop digital models and analyze the performance of the material in structural systems of tall buildings. Current applications of the material in building and construction sector are addressed in the literature review. This research evaluates the performance of the structural systems for tall buildings using carbon composite as the primary structural material. Connection level simulations presented in this research provide insights on the significance of fiber orientation in the fabrication of structures. Other challenges in the widespread use of CFRP material in tall buildings are addressed in the research but focus of the research is on the structural applications of the material in tall buildings. The research provides information about the use of CFRP as a structural material in tall buildings. The results of this study offer significant insights about the issues of connectivity and constructability related to use of CFRP in tall buildings. This research also provides a parametric framework for architects and designers to evaluate and study the performance of a structural materials to be used in tall building structural systems using finite element analysis.
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Title: Evaluating the Impact of Residential Indoor Air Quality and Ventilation and Filtration Interventions on Adult Asthma-Related Health Outcomes in Chicago, IL
Creator: Kang, Insung
Date: 2022
Description: Human exposure to a variety of airborne pollutants is associated with various adverse health effects, ranging from respiratory symptoms to...
Show moreHuman exposure to a variety of airborne pollutants is associated with various adverse health effects, ranging from respiratory symptoms to exacerbation of chronic diseases to cardiovascular disease and cancer. While most of our knowledge of the adverse impacts of air pollution comes from studies utilizing outdoor air pollutants as surrogates for exposure, people spend most of their time indoors, especially at home, where pollutant concentrations are often higher than outdoors. And within homes, mechanical ventilation systems and filtration are increasingly recommended to provide fresh air for ventilation and dilute indoor pollutant sources. There are a variety of ventilation system types that can be used for home retrofits; however, there is limited information on how they affect indoor air quality (IAQ) from both indoor and outdoor sources and how they influence occupant health and well-being. Therefore, to fill some of these knowledge gaps, this research aims to evaluate the effects of indoor air quality broadly, as well as interventions with three common types of residential mechanical ventilation system retrofits (i.e., continuous exhaust-only, intermittent fan-integrated supply, and continuous balanced systems with energy recovery ventilators), on asthma-related health outcomes in a cohort of adults in Chicago, IL. The key findings of this dissertation indicate that exposures to indoor NO2 and PM, higher indoor temperature, and mold/dampness were associated with poorer asthma control. The home ventilation and air filtration interventions, regardless of ventilation system type, significantly improved asthma control of the study population (~4% increase in ACT score; p < 0.001), and led to reductions in indoor concentrations of formaldehyde (HCHO) (-19.5 ppb; -63%; p < 0.001), carbon dioxide (CO2) (-120 ppm; -15%; p < 0.001), nitrogen dioxide (NO2) (-1.8 ppb; -3%; p = 0.035), and particulate matter (PM), including PM1 (-4.9 µg/m3; -43%; p = 0.001), PM2.5 (-4.9 µg/m3; -39%; p = 0.003), and PM10 (-6.2 µg/m3; -41%; p = 0.003). Additionally, asthma control was significantly improved in all subgroups: participants who received both ventilation and filtration interventions (~6% increase in ACT score; p < 0.001); continuous exhaust-only systems (~3% increase in ACT score; p = 0.033); intermittent central-fan-integrated-supply (CFIS) systems (~3% increase in ACT score; p = 0.018); and continuous balanced systems with an energy recovery ventilator (ERV) (~7% increase in ACT score; p < 0.001). Indoor CO2 concentrations were significantly reduced in homes with continuous ventilation systems, including exhaust-only (-165 ppm, -20%; p = 0.005) and balanced ERV systems (-186 ppm, -23%; p = 0.004), while indoor particulate matter (PM1, PM2.5, and PM10) concentrations were significantly reduced in homes with ventilation systems with filtration upgrades, including CFIS (PM1: -5.3 µg/m3, -46%; PM2.5: -5.0 µg/m3, -39%; and PM10: -6.2 µg/m3, -41%; all p < 0.05) and balanced ERV systems (PM1: -7.5 µg/m3, -59%; PM2.5: -8.3 µg/m3, -58%; and PM10: -10.4 µg/m3, -61%; all p < 0.05). Last, results of a cost-benefit analysis (CBA) of the three types of mechanical ventilation systems over an assumed 10-year life span, which predicted impacts on mortality and asthma outcomes based on measured impacts on two indoor pollutants – PM2.5 and NO2 – relative to initial and operational costs, as well as filtration upgrade costs, suggest that the intermittent CFIS system with improved MERV 10 filtration was the most beneficial approach, with the central benefit-cost ratio (BCR) of 6.0, followed by the continuous balanced ERV system (central BCR = 3.7) and exhaust-only system (central BCR = 3.2). This dissertation provides the first known empirical data in the U.S. on asthma outcomes associated with different types of mechanical ventilation systems that have highly varying impacts on indoor pollutant concentrations of both indoor and outdoor origin and environmental conditions. Results are also expected to provide much-needed guidance to homeowners, contractors, builders, and agencies on the advantages and disadvantages of different types of residential mechanical ventilation systems.
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Title: Self-Reconfigurable Soft Robots Based on Boundary-Constrained Granular Swarms
Creator: Karimi, Mohammad Amin
Date: 2022
Description: Unlike conventional robots, which consist of rigid bodies and linkages, soft robots are composed of compliant and flexible components and...
Show moreUnlike conventional robots, which consist of rigid bodies and linkages, soft robots are composed of compliant and flexible components and actuators. This distinction enables adaptive behaviors in response to unpredictable environments, like manipulating objects with a variety of shapes. As such, soft robots afford greater potential over traditional robots for safe human interaction.Despite these advantages, there remain obstacles due to the challenges in modeling, controlling, and fabricating soft materials. For example, soft robots that rely on thermal or electrical actuation are typically slow to respond and unable to apply large forces as compared to traditional robots. Pneumatically actuated soft robots, while more responsive and capable of applying larger forces, generally need to be tethered to external control mechanisms, which becomes limiting in tasks that require lightweight, autonomous functionality.In contrast, this thesis describes a new type of robot that exhibits those same characteristics, but achieves them via a boundary-constrained swarm.The robotic structure consists of passive granular material surrounded by an active membrane that is composed of a swarm of interconnected robotic sub-units. The internal components are important for overall function, but their relative configuration is not. This allows for an effectively random, unstructured placement of the internal components, which in turn creates excellent morphability. Collectively, the subunits determine the overall shape of the robot and enable locomotion through interaction with external surfaces.The constrained swarm embodies the continuum, compliant, and configurable properties found in soft robots, but in this state the robot is limited in its ability to manipulate objects due to the relatively low force it can apply to external objects.To address this issue, the unique ability to execute a jamming phase transition is added to the robot. Importantly, jamming is controlled by the degree by which the passive particles are spatially confined by the membrane, and this in turn is controlled by the active sub-unit robots using different jamming mechanisms. The robot exploits its ability to transition between soft (unjammed) and rigid (jammed) states to induce fluid-like flexibility or solid-like rigidity in response to objects and features in the environment.In order to investigate this design concept, I have studied different prototype designs for the robot that varied in terms of the locomotion and jamming mechanisms. I also present a simulation framework in which I model the design and study the scalability of this class of robots. The simulation framework uses the Project Chrono platform, which is a multi-body dynamics library that allows for physics-driven collision and contact modeling.
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Title: Workload Interference Analysis and Mitigation on Dragonfly Class Networks
Creator: Kang, Yao
Date: 2022
Description: Dragonfly class of networks are promising interconnect topologies that support current and next-generation high-performance computing (HPC)...
Show moreDragonfly class of networks are promising interconnect topologies that support current and next-generation high-performance computing (HPC) systems. Serving as the "central nervous system", Dragonfly tightly couples tens of thousands of compute nodes together by providing high-bandwidth, low-latency data exchange for exascale computing capability. Dragonfly can support unprecedented system scale at a reasonable cost thanks to its hierarchical architecture. In Dragonfly systems, network resources such as routers and links are arranged into identical groups.Groups are all-to-all connected through global links, and routers within groups are connected via local links. In contrast to the fully connected inter-group topology, connections for the routers within groups are designed according to the system requirement. For example, the one-dimensional all-to-all connection is favored for higher network bandwidth, a two-dimensional grid arrangement can be constructed to support larger system size, and a tree structure router connection is built for the extreme system scale. The hierarchical design with groups enables the topology to support unprecedented system size while maintaining a low-diameter network. Packets can be minimally delivered by simply traversing the network hierarchy between groups through global links and reaching their destinations through local links. In case of network congestion, packets can be non-minimally forwarded through any intermediate group to increase the system throughput. As a result, all network resources are shared such that links and routers are not dedicated to any node pair. While link utilization is increased, shared network resources lead to inevitable network contention among different traffic flows, especially for the systems that hold multiple workloads at the same time. This network contention is observed as the workload interference that causes degraded system performance with delayed workload execution time. In this thesis, we first model and analyze the workload interference effect on Dragonfly+ topology through extensive system simulation.Based on the comprehensive interference study, we propose Q-adaptive routing, a multi-agent reinforcement learning based solution for Dragonfly systems. Compared with the existing routing solutions, the proposed Q-adaptive routing can learn to forward packets more efficiently with smaller packet latency and higher system throughput. Next, we demonstrate that intelligent routing algorithms such as Q-adaptive routing can greatly mitigate workload interference and optimize the overall system performance. Subsequently, we propose a dynamic job placement strategy for workload interference prevention. When combined with Q-adaptive routing, dynamic job placement gives users the flexibility to either reduce workload interference from communication intensive applications or protect target applications for higher performance stability.
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Title: Intelligent Battery Switching Module for Hybrid Electric Aircraft
Creator: Kamal, Ahmad
Date: 2022
Description: The growth in world economics, tourism and international cooperation has resulted in significant growth of civil aviation industry. This...
Show moreThe growth in world economics, tourism and international cooperation has resulted in significant growth of civil aviation industry. This growing number of fossil fuel reliant aircrafts will significantly increase waste gas emissions with detrimental impact on the environment. The system efficiency of the aircraft must be substantially improved to reduce the fuel burn and thus waste gas emissions. Therefore, the aircraft industry is pushing towards higher electrification of future aircrafts to increase system efficiency, reduce fuel burn and to lower emissions as well as operational costs. The more electric aircraft (MEA) design concept, commercially realized by Boeing 787 and Airbus A380, increases system efficiency by replacing the mechanical, pneumatic, and hydraulic systems with electrical systems. However, global regulation authorities demand further reduction in waste gas emissions and fuel burn. To meet these stringent demands, the aircraft industry is exploring hybrid electric aircrafts which can significantly reduce fuel burn by electrifying the propulsion train of the aircraft. This higher penetration of electrical energy in the aircraft warrants smart short-circuit protection with ultrafast response time. However, current hybrid aircrafts still use outdated mechanical and thermal short-circuit protection which have historically proven to cause numerous tragedies. Solid-state power controller (SSPC) is an alternate solution which uses semiconductor devices to offer faster response. However, the main drawbacks of SSPCs are their need for active cooling due to higher conduction loss and the use of foldback current limiting approach to limit the inrush current of DC-link capacitor of the powertrain. The foldback current limiting approach degrades the power semiconductor devices used due to excessive heat loss by driving the device near the safe operating area (SOA) limits of the device. This thesis presents a 750V/250A intelligent Li-ion battery switching module (BSM) for hybrid electric aircraft propulsion application. The BSM uses commercially available 1200 V SiC JFET power modules with ultra-low RDSON in parallel to achieve sub-mΩ total on-resistance, comparable to the incumbent mechanical contactor solution. This allows the total nominal conduction power loss of the BSM to be less than merely 23 W, permitting maintenance-free passive cooling. In contrast to the incumbent contactor solution, the BSM has ultrafast response (µs-level) to a fault condition. Which, in conjunction with the reduced fault current stress, significantly improves the operation lifetime of the entire system. The BSM incorporates various intelligent features by implementing a tri-mode operation concept, which allows to pre-charge the DC-link capacitor with a limited charging current in PWM mode. To mitigate single-point failures, several design redundancy measures are implemented to ensure reliability and safety for the aircraft. Design considerations of the circuit and physical design of the BSM are discussed in detail including the design of the custom laminated busbar and thermal analysis. Furthermore, the inherent uncontrolled oscillation phenomenon of the JFET cascode structure is explored and addressed. Finally, the experimental results obtained from the built and tested prototype of the BSM are reported.
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Title: Examining Associations Between Discrimination, Social Cohesion, and Health among White and POC LGBT Chicagoans
Creator: Kannout, Lynn
Date: 2022
Description: Consistent with the minority stress perspective, lesbian/gay, bisexual, and transgender (LGBT) individuals on average report worse health than...
Show moreConsistent with the minority stress perspective, lesbian/gay, bisexual, and transgender (LGBT) individuals on average report worse health than heterosexual individuals in several domains, e.g., general health, mental health, physical health, and health care access. Intersectionality-based research shows that LGBT-POC are, on average, at even greater risk for adverse health outcomes compared to their White LGBT counterparts. Discrimination and social cohesion may be two mechanisms underlying these between- and within-group disparities, given their broader relations to health and their relatively high frequency within marginalized populations. This study used data from the Chicago Department of Public Health to examine broad health differences between LGBT White and LGBT-POC individuals, and to test specific mediations models in which social cohesion mediated links between discrimination and health. LGBT-POC reported experiencing worse general health, lower access to health care, more experiences of discrimination, and lower feelings of social cohesion than did White LGBT individuals. No mediation effects emerged, however there was a direct effect of experiencing discrimination on mental health distress. Further, discrimination exposure related inversely to feelings of social cohesion. Study strengths, limitations, and implications are discussed.
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Title: Advanced methods for storage ring nonlinear beam dynamics design and implementation
Creator: Song, Minghao
Date: 2022
Description: To meet the increasing demands of scientific researchers for brighter photonbeams, storage ring beam emittance is continually pushed down to a...
Show moreTo meet the increasing demands of scientific researchers for brighter photonbeams, storage ring beam emittance is continually pushed down to a new ultra-low level. It, therefore, becomes correspondingly more challenging to ensure such storage rings have good nonlinear beam dynamics performance. This thesis work is focused on developing advanced methods for low emittance storage ring nonlinear beam dynamics design and implementation.Nonlinear beam dynamics optimization is essential to low emittance storagering design. A highly efficient multi-objective optimization algorithm is needed to simultaneously achieve a large dynamic aperture and a large local momentum aperture. Work was done to improve and test a machine learning-based algorithm called multi-generation Gaussian process optimizer (MG-GPO). This advanced method uses constructed GP models to pre-select solutions, and benchmarking of results on toy problems shows that MG-GPO converges significantly faster than traditional algorithms. The MG-GPO algorithm was successfully applied to nonlinear lattice design optimization, for example, to the SPEAR3 upgrade 7-nm lattice, and it was demonstrated to converge faster than NSGA-II and MOPSO. This was due to its capability of selecting candidates that tend to have better performance. This algorithm will help accelerate nonlinear lattice studies.Correction of nonlinear beam dynamics is also important for low emittancestorage ring commissioning and operation. In order to measure and correct features relevant to the nonlinear beam dynamics, an effective method is needed to excite sustained beam oscillations to large amplitude. A method based on the concept of autoresonance was proposed. This advanced technique excites nonlinear transverse beam motion in storage rings by sweeping the drive frequency. The theory for the autoresonance threshold was derived for the nonlinear optics systems in storage rings, both with and without damping effects, using Hamiltonian dynamics. The theoretical predictions for the drive amplitude threshold were found to agree well with simulations for a simple storage ring model, as well as for simulations with the actual SPEAR3 and APS lattices. The theory was also compared favorably to historical data from experiments on SPEAR3. Simulations verified that an oscillation driven by autoresonant excitation matches the character of a free oscillation, so that beam oscillation data taken during the ramping process can confidently be used to characterize the nonlinear beam dynamics performance. The precision of measurements can be improved by using autoresonant excitation since large amplitude beam oscillations are sustained significantly longer. Simulations of autoresonant excitation demonstrated the measurements of the detuning coefficients and resonance driving terms. The use of autoresonant excitation for the detection of faulty magnets and correction of resonance driving terms was also demonstrated.Online optimization is an alternative way to effectively improve nonlinear beamdynamics performance in a real storage ring. The greater efficiency of an advanced optimization algorithm is also needed to find globally optimal solutions in the limited experimental time that is typically available. The MG-GPO algorithm was implemented for SPEAR3 vertical emittance minimization and injection efficiency optimization. Again, the optimized solutions demonstrate that MG-GPO is more efficient than the commonly used PSO algorithm. SPEAR3 performance was successfully improved during the online optimization runs with MG-GPO.
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Title: SYSTEMATIC ANALYSIS OF THE MCENTER BEAMLINE AT THE FERMILAB TEST BEAM FACILITY FOR THE NOVA TEST BEAM EXPERIMENT
Creator: Temizel, Buse Naz
Date: 2021
Description: This thesis presents a systematic analysis of the MCenter beamline at the Fermilab Test Beam Facility to help to generate improved beam...
Show moreThis thesis presents a systematic analysis of the MCenter beamline at the Fermilab Test Beam Facility to help to generate improved beam profiles for the NOvA Test Beam Experiment. Several studies were carried out to understand beam transport to the experiment, including optics calculations and computer simulations using a novel procedure for incorporating the acceptance of the channel. Data from beam profile monitors was used to trace the beam phase space and compared to simulation results. Detailed analysis revealed that the beam sizes on the NOvA target were large compared to its transverse size. New tunes were proposed for a detailed beam optics study. Analysis of the new tunes shows that the new optics produce two components corresponding to two different peaks at different energies in the horizontal profile at the NOvA target.
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Title: Predictive Energy Management of Connected Hybrid Electric Vehicles in the Presence of Uncertainty
Creator: Sotoudeh, Seyedeh Mahsa
Date: 2022
Description: Energy efficiency improvements brought by electrification of the powertrain in Hybrid Electric Vehicles (HEVs) highly depend on their...
Show moreEnergy efficiency improvements brought by electrification of the powertrain in Hybrid Electric Vehicles (HEVs) highly depend on their powertrain Energy Management Strategy (EMS) that determines optimal power allocation between powertrain components.Eco-driving based EMS seeks further energy efficiency improvements through optimizing vehicle's driving cycle (velocity and hence torque demand), in addition to the powertrain's EMS. A novel hierarchical EMS is developed in this thesis for connected human-driven HEVs and then extended to automated HEVs that effectively addresses some of the major challenges of the energy management problem. At its high-level, a computationally-tractable Pseudospectral Optimal Controller (PSOC) with discounted cost is employed to approximately solve the powertrain's energy management problem over driving cycle previews of the entire trip. The high-level's approximate solution is then used as a reference by the low-level tube-based Model Predictive Controller (MPC) that solves the problem over higher-quality, short-horizon driving cycles in a real-time applicable fashion. For human-driven HEVs, a Long Short-Term Memory (LSTM) neural network predicts the human driver's velocity profile over low-level's short horizons. A velocity optimizer is added to the low-level for automated HEVs that optimizes the vehicle's driving cycle by effectively utilizing regenerative braking capability of the HEV. At the low-level, the tube-based MPC controller solves the powertrain's energy management problem over either predicted (human-driven HEV) or optimized (automated HEV) driving cycles by accounting for driving cycle's uncertainty, due to uncertain future information, and hence ensures robust constraints satisfaction. A novel cost-to-go approximation method is developed that uses the optimal costate trajectories obtained from the high-level PSOC controller to generate terminal costs for the low-level controller. This improves suboptimality of the short-horizon solutions and ensures charge balance constraint satisfaction at the end of the trip without having to impose conservative constraints. A novel learning-based framework is also proposed to jointly optimize the automated HEV's driving cycle and its powertrain's power split. A Deep Neural Network (DNN)-based MPC controller is developed for the low-level that jointly optimizes the HEV's driving cycle and powertrain energy management in a real-time applicable manner. To ensure constraints satisfaction, a novel Quadratic Programming (QP)-based projection of the DNN-based approximate control laws is proposed that can be efficiently solved in real-time. Simulation results over standard and real-world driving cycles demonstrate efficacy of the proposed control frameworks in terms of suboptimality (fuel efficiency) improvement, potential real-time applicability, and constraints (especially charge balance constraint) satisfaction in the presence of driving cycle uncertainty.
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Title: Thermal Effects in Fluid Dynamics
Creator: Sulzbach, Jan-Eric
Date: 2021
Description: In this thesis we propose a mathematical framework modeling non-isothermal fluids.The framework is based on a coupling between non-equilibrium...
Show moreIn this thesis we propose a mathematical framework modeling non-isothermal fluids.The framework is based on a coupling between non-equilibrium thermodynamics and an energetic variational approach for the mechanical parts of the system. From this general model we derive and analyze three separate systems.The first application is the Brinkman-Fourier model. This is related to the ideal gas system, where the pressure and internal energy depend linearly on the product of density and temperature. This is a subsystem to the general Navier-Stokes-Fourier system. We prove the existence of local-in-time weak solutions via compensated compactness arguments.The next model we study is a non-isothermal diffusion system involving chemical reactions. For a system close to chemical equilibrium we show the well-posedness of classical solution using a fixed-point argument involving theory of homogeneous Besov spaces.The third application of the general theory is for another general diffusion system with a Cahn-Hilliard energy. In this framework, we study in detail how the temperature can affect the system on different scales, leading to different models. For the analysis, we focus on one case and show the well-posedness of classical solutions. The proof relies on methods from the theory of Besov spaces and paradifferential calculus.
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Title: Technological Consciousness in Midwestern American Farming: From Party Lines to Autonomous Tractors
Creator: Sziron, Mónika
Date: 2022
Description: This dissertation is primarily concerned with understanding the current conceptions, perceptions, and ethical concerns of artificial...
Show moreThis dissertation is primarily concerned with understanding the current conceptions, perceptions, and ethical concerns of artificial intelligence in Midwestern agriculture. Using the theory of technological consciousness as a backdrop for understanding the relationship between Midwestern agriculture and technology, in chapter two this dissertation first provides a narrative review of major technological developments throughout history in Midwestern farming and how the human experience in farming is influenced by technology throughout history. This history provides context for the current state of Midwestern agriculture, which is now increasingly entangled with artificial intelligence. The theory behind artificial intelligence ethics and general trends in artificial intelligence are discussed in chapter three. To understand present conceptions, perceptions, and ethical concerns of artificial intelligence for Midwestern farmers, a pilot survey was dispersed to farmers and pilot media content analysis was conducted on Midwestern agriculture publications. The results from this pilot survey and pilot media content analysis are discussed in chapter four. Chapter five delves into theory and how the human experience with technology has evolved over time and its effects on the human experience today. This chapter also provides theoretical insights for the future of farming with artificial intelligence. The dissertation concludes with reviewing the ethical concerns relating to artificial intelligence in agriculture for Midwestern farmers, provides recommendations for developers of agriculture technology, and highlights the new partnership between farmers and computer scientists and how this partnership will lead the way in the future of Midwestern farming.
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Title: Biophysical and Computational Characterization of CinDel Edits of Dystrophin
Creator: Stojkovic, Vladimir
Date: 2022
Description: Duchenne muscular dystrophy (DMD) is a degenerative genetic disease caused by a genetic defect that results in the absence of dystrophin, a...
Show moreDuchenne muscular dystrophy (DMD) is a degenerative genetic disease caused by a genetic defect that results in the absence of dystrophin, a protein with an important stabilizing role in muscle cells. DMD causes progressive muscle degeneration leading to the loss of ambulation, and typically results in death before the third decade of life. Treatments for DMD aim to restore dystrophin expression and typically do so by producing edited or modified dystrophins. The only FDA approved therapy, exon skipping, produces dystrophin edits at exon boundaries but emerging therapeutic approaches like gene replacement therapy and CRISPR-Cas9-based gene editing techniques like CinDel allow for greater flexibility and are not constrained to exon boundary edits. However, understanding of what makes a “good”, functional edit is limited so it is not clear how to make use of this increased flexibility to produce optimal edits which are believed to be necessary for robust treatment. In an effort to improve understanding of the biophysics of these non-exon edits, we have embarked on a mixed experimental and computational study of a set of CinDel edits in the D19-D21 region of the dystrophin central rod domain. First, we have conducted an Alphafold structure prediction-based screen of a subset of possible edits in this region and selected one edit for follow-up characterization. We then compared this computationally-selected edit to three other heuristically designed edits experimentally and computationally by molecular dynamics simulations. We found that the computationally selected edit is significantly more thermodynamically stable than the other edits in the cohort. This edit also generally exhibited more favorable properties in MD simulations across multiple measures such as helicity, STR-junction unwinding and conformational variability.
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