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Title: Stimulation-Responsive Materials for the Treatment of Disordered Tissues
Creator: Clutter II, Elwin Dean
Date: 2022
Description: Microenvironments offer physical and chemical cues to cells that affect their behavior. These cues can be bioactive chemicals such as drugs...
Show moreMicroenvironments offer physical and chemical cues to cells that affect their behavior. These cues can be bioactive chemicals such as drugs and cytokines, matrix cues like stiffness and composition, and electrical signals as seen in membrane potentials and epithelial wound healing. Controlling these cues can drive cell behavior toward apoptosis, proliferation, or changes in protein expression. In this thesis research, three components were used to model changes in cell behavior: the near infrared dye indocyanine green (ICG), silk fibroin (SF) from Bombyx mori silkworm cocoons, and carbon nanotubes (CNT). The mechanism of ICG photobleaching was studied for the efficacy to kill neuroblastoma cancer cells. ICG was twice as effective at killing neuroblastoma than fibroblast cells. Albumin stabilized monomeric ICG to enhance photobleaching by improving light interaction, and photodegradation of ICG into α,β-unsaturated aldehydes led to significant reduction of proliferation in neuroblastoma cells by targeting cell signaling components such as protein transcription factors. SF-ICG composite materials were developed into films and electrospun fibers. These composite materials were examined as light-activated wound coverings to control bleeding in hemorrhage, using ICG’s photothermal effect. ICG added an absorbance peak to SF at 805 nm. Irradiation decreased this peak, produced a new absorbance peak at 352 nm, and an increased fluorescence peak around 490 nm, showing photochemical changes that may be useful in sensor design. Increased heat production from irradiation of SF-ICG occurred in the films with 0.2% w/w ICG in SF during 1 min irradiation, whereas SF-ICG fibers required improvement of processing by ethanol vapor treatment (EVT) to reduce loss of ICG during preparation. EVT improved ICG retention in SF fibers during sterilization with 70% ethanol solution thus improving heat generation in the SF-ICG fibers. Heat evolved from SF-ICG 0.2% film solidified bovine blood within 42 s, with visible changes after the first 6 s. SF electrospun fibers were investigated to optimize silk preparation to reduce diameters and increase alignment to mimic local native cell environments with and without CNT to add conductivity for enhancement of electrical stimulation. CNT reduced SF fiber diameters below 1% and effected alignment differently as the concentration increased. Longer degumming times decreased SF fiber diameters and alignment of the same concentration. The optimized conditions were 1 h degumming time with 1.5 ml/h flow rate at a concentration of 100 mg/ml spinning solution with 0.25% CNT to form fibers with 1.36 (± 0.09) µm diameter and 0.31 (± 0.01) a.u. alignment. Additionally, SF fibers were used as a long-term cell growth scaffold to compare with decellularized native tissue. Decellularized tissue decreased fibroblast mRNA expression of collagen type 1, lysyl oxidase-like 1 and matrix metalloproteinase 9, while all other genes expression was the same as cells on plastic. The SF fiber scaffold reduced fibroblast expression of collagen type 3 compared to growth on plastic, and both collagen types 1 and 3 increased over growth time on SF. Immunofluorescence staining showed both collagens newly deposited on the SF scaffold and improved over time. In conclusion, proteins stabilized ICG monomers to improve light interaction, efficacy of photobleaching, and heat evolution to induce apoptosis in neuroblastoma and agglutination of blood in SF composites. Irradiation of ICG enhanced changes in optical properties and may have sensor applications. The decrease of genes may be due to each scaffold having lower stiffness compared to plastic. ICG and SF are both materials with applications as biological scaffolds in pelvic organ prolapse and treatment of neuroblastoma and hemorrhage.
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Title: EMAT DESIGN CONFIGURATIONS AND SOFTWARE-DEFINED ULTRASONIC COMMUNICATIONS THROUGH METALLIC CHANNELS IN NUCLEAR FACILITIES
Creator: Huang, Xin
Date: 2022
Description: Nuclear facilities are partitioned into different blocks, and all equipment therein is well-packed for isolation purposes. The primary...
Show moreNuclear facilities are partitioned into different blocks, and all equipment therein is well-packed for isolation purposes. The primary barriers of each block include a thick, reinforced, high-strength concrete wall. The presence of physical boundaries introduces a major challenge to implementing wired or radio frequency (RF) wireless communication. Achieving data communication through the solids channel, especially considering the complex environment in nuclear power plants, is very challenging. Ultrasonic communication is a desirable method for information transfer through solid mediums such as metallic bars or pipes. This thesis is methodologically innovative in the way it seeks the best solution for ultrasonic communications through metallic channels. Therefore, we address the following research areas: 1. The advantages of using electrical-magnetic acoustic transducers (EMATs) as transmitter and receiver; 2. The fundamentals of the EMAT structure and wave generation mechanism for ultrasonic communications; 3. The channel model and behavior of ultrasonic wave propagation in a different structure of solid channels; 4. How to minimize the adverse impact of wave dispersion and reverberation; 5. How to increase the bitrate and decrease the bit error rate (BER) of an ultrasonic communication system; 6. How to utilize the software-defined system-on-chip (SoC) platform for ultrasonic communications; and 7. How to implement secure ultrasonic video transmission through solid channels. In this thesis, we have investigated the feasibility of using Periodic-permanent-magnet electromagnetic acoustic transducers (PPM-EMATs) transmitter and receiver as the information-bearing of ultrasonic waves across the plate channels (shear horizontal waves) and pipe channels (torsional waves). Methods such as time-reversal (TR), pulse shaping, and adaptive equalizer techniques are studied for improving the signal-to-noise ratio (SNR) of ultrasonic communication systems. We also investigated a novel software-defined ultrasonic communication system (SDUC) for real-time video transmission through a highly reverberant and dispersive metallic bar channel. Furthermore, we investigated the feasibility of combining orthogonal frequency-division multiplexing (OFDM) with quadrature amplitude modulations (QAM) for bitrate peak performance. Strategies and guidelines were established for the best solutions to combat intersymbol interference (ISI) caused by the severe reverberation inherent in metallic channels. A practical solution for video transmission, adhering to the Digital Video Broadcasting Terrestrial (DVB-T) standard, was also examined for video streaming transmission of 240p, 480p, and 720p resolutions at 20 frames per second (FPS) across a rectangular aluminum bar (ARB) channel. Through ultrasonic experimental studies for channel analysis, we achieved a peak video transmission rate of 1074 kbps with 3.3×10-4 BER despite reverberation, the multipath effect, and signal fading within the ARB channel.
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Title: Two Essays on Corporate Finance and Fixed-income Securities
Creator: Shen, Hao
Date: 2023
Description: In this study, we empirically investigate the relation between corporate finance and fixed income securities. Specifically, we employ...
Show moreIn this study, we empirically investigate the relation between corporate finance and fixed income securities. Specifically, we employ staggered changes in state corporate income tax rates as exogenous shocks and estimate how these state tax changes affect bond at-issue yield spreads. We find a significant increase in bond yield spreads after state tax increases but not after state tax decrease. Tax increases result in a 36 basis points increase in the yield spreads, which translates into a $12 million increase in interest expenses for firms experiencing tax increases. Besides, we employ the staggered adoption of universal demand (UD) laws by different states in the United States as a quasi-experimental setting and investigate the effect of UD laws on bond yield spreads at issuance. The adoption of UD laws raises the hurdle for shareholders to bring derivate lawsuits against firms and weakens shareholder litigation rights. Using a sample of bond issuances from 1985 to 2009, we find that the adoption of UD laws is positively associated with yield spreads of bonds issued by U.S. firms.
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Title: Polarization Induced by A Terahertz Electric Field in A Semiconductor Nanodimer in the Overlapping Regime
Creator: Wang, Zi
Date: 2023
Description: Boltzmann transport equation is a theoretical framework for the description of thermodynamics or charge reactions in a system not in...
Show moreBoltzmann transport equation is a theoretical framework for the description of thermodynamics or charge reactions in a system not in equilibrium, which can be applied to the analysis of the interactions of mobile charges with an electromagnetic wave. When the dimensions of the object are small compared to the wavelength, the induced dipole moment provides a means to characterize the collective response while providing insight to the nature of the charge-field interactions. Semiconductor nanoparticles exhibit surface plasmon resonance in the terahertz frequency range and are of current interest for the development of components and circuits in that part of the electromagnetic spectrum. By changing the plasmon frequencies of doped semiconductors through the change of carrier concentration, new opportunities arise for plasmonic manipulation in terahertz region leading to various promising applications. Despite the Drude model's long-term success and convenience in describing the electrical conductivity of metals in terms of dielectric functions, some aspects of polarization are not accounted for by bulk properties. By incorporating the transport equations of the charge carriers with Maxwell's equations, screening effects of charge carriers can be accounted for, enabling the internal field, space charge and induced dipole moment of a semiconductor nanoparticle to be studied.The computations performed for elementary dimer structures in overlapping cases revealed the internal field screening, while the complex dipole moments show dispersion and absorption effects. The numerical algorithms are implemented using the finite element method to investigate the surface plasmon resonance (SPR) induced on the semiconductor particles. Unique SPR modes evolution is observed as the thickness of the overlap region is varied. The characteristics can be interpreted by the migration of local space charge as the level of overlap is varied. This degree of freedom provided by a semiconductor nanodimer could be employed to control the local field near a simple cluster of nanoparticles, with potential for application in sensing and circuit components in the terahertz frequency range.
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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: Machine Learning for NDE Imaging Applications
Creator: Zhang, Xin
Date: 2023
Description: Infrared Thermography and Ultrasonic Imaging of materials are promising non-destructive evaluation (NDE) methods but signals face challenges...
Show moreInfrared Thermography and Ultrasonic Imaging of materials are promising non-destructive evaluation (NDE) methods but signals face challenges to be analyzed and characterized due to the nature of complex signal patterns and poor signal-to-noise ratios (SNR). Industries such as nuclear energy, are constructed with components produced using high-strength superalloys. These metallic components face challenges for wide deployment because material defects and mechanical conditions need to be non-destructively evaluated to identify potential danger before they enter service. Low NDE performance and lack of automation, particularly considering the complex environment in the in-situation NDE and nuclear power plant, present a major challenge to implement conventional NDE. This study solves the problems of using the advantages of machine learning as signal processing methods for Infrared Thermography and Ultrasonic NDE imaging applications. In Pulsed Infrared Thermography (PIT), for quality control of metal additive manufacturing, we proposed an intelligent PIT NDE system and developed innovative unsupervised learning models and thermal tomography 3D imaging algorithms to detect calibrated internal defects (pores) of various sizes and depths for different nuclear-grade metallic structures. Unsupervised learning aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Difficulties to detect defects by using PIT are thermal imaging noise patterns; uneven heating of the specimen; defects of micron-level size with overly weak temperature signals and so on. The unsupervised learning methods overcome these barriers and achieve the high defect detection accuracies (F-score) of 0.96 to detect large defects and 0.89 to detect microscopic defects, and can successfully detect defects with diameter of only 0.101-mm. In addition, we researched and developed innovative unsupervised learning models to compress high-resolution PIT imaging data and achieve the average high compression ratio >30 and a highest compression of 46 with reconstruction accuracy peak signal-to-noise ratio (PSNR) >73dB while preserving weak thermal features corresponding to microscopic defects. In ultrasonic NDE imaging, for structural health monitoring of materials, we built a high-performance ultrasonic computational system to inspect the integrity of high-strength metallic materials which are used in high-temperature corrosive environments of nuclear reactors. For system automation, we have been developing neural networks with various architectures for grain size estimation by characterizing the ultrasonic backscattered signals with high accuracy and data-efficiency. In addition, we introduce a response-based teacher-student knowledge distillation training framework to train neural networks and achieve 99.27% characterization accuracy with a high image processed throughput of 192 images/second on testing. Furthermore, we introduce a reinforcement learning based neural architecture search framework to automatically model the optimal neural networks design for ultrasonic flaws detection. At last, we comprehensively researched the performance of using unsupervised learning methods to compress 3D ultrasonic data and achieve high compression performance using only 4.25% of the acquired experimental data.
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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: PREDICTING AND SIMULATING OUTDOOR THERMAL COMFORT-BASED HUMAN BEHAVIOR IN URBAN ENVIRONMENTS
Creator: Khan, Zahida Marzaban
Date: 2022
Description: Rapid urban growth due to a constant rise in world population has amplified the need for sustainable design development of cities. Human...
Show moreRapid urban growth due to a constant rise in world population has amplified the need for sustainable design development of cities. Human behavior, a key performance metric of sustainable design, can be rewarding for urban policies and city planning. Due to its complex nature, human behavior prediction and simulation are increasingly challenging. Complexity is associated with multiple factors, among which social and environmental factors are critical, especially in urban conditions with tall buildings that create unique microclimates. Human behavior in this study referred to human spatial behavior. This research hypothesized that the microclimatic variations at seasonal and diurnal levels affect people’s behavior in outdoor urban environments. Additionally, interdisciplinary crossover studies on novel methodologies to predict human behavior is becoming popular. Moreover, architects and urban designers are interested in human behavior simulation tools that can help them make informed design decisions through ‘what-if’ scenarios and assess their designs before execution. This doctoral research investigated the inter-relationship between Outdoor Thermal Comfort (OTC), human behavior, and urban morphology for Plazas in urban conditions with tall buildings and within a specific climate zone. The study focused on two overarching objectives: (1) to present a novel research methodology to investigate and predict OTC-based human behavior in urban conditions; and (2) to develop HuBeSIM - a human behavior simulation framework using an agent-based model (ABM) to simulate OTC integrated human behavior in outdoor spaces. Daley Plaza – an urban public space built-in 1965 in downtown Chicago — was used as (1) a case study to test the feasibility of this research methodology and (2) a pilot study to demonstrate the HuBeSIM framework. The outcome of this study shows a significant impact in the outdoor urban environments with design goals that use human behavior as a key performance indicator. The research contributes to the modeling and simulation of OTC-based human behavior in urban environments to nurture livable communities and sustainable cities. The first part of the dissertation presented a novel research methodology involving data collection through an on-site observational study for behavioral mapping, and microclimatic CFD simulations for OTC index - Physiological Equivalent Temperature (PET). The sample data consisted of two seasons, namely summer and fall, with more than 600 observations collected during the three-hour lunchtime period. The second part of the dissertation involved developing a Human Behavior SIMulation (HuBeSIM) framework in the popular computer aided design platform Rhino® and Grasshopper® (GH). This part integrated OTC using physics-based modeling and human behavior using mathematical agent-based modeling to develop a simulation framework for outdoor urban space design. The findings from the observational study revealed a moderate relationship between microclimate and human behavior in the fall, and a weak correlation in summer. The results showed that people’s behavior is not affected by PET values above 35°C. The proposed Human Behavior SIMulation framework has a high potential to develop into a comprehensive model by incorporating other behavioral factors. This study contributes to the sustainable built environment design that leads to the environmental, social, and economic upliftment of a city.
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Title: Factors Influencing the Level of Detection of Testing Listeria monocytogenes in Ice Cream
Creator: Chen, Bairu
Date: 2022
Description: The increasing evidence has shown that having a sensitive detection method for Listeria monocytogenes in food products is critical for public...
Show moreThe increasing evidence has shown that having a sensitive detection method for Listeria monocytogenes in food products is critical for public health as well as industrial economics. L. monocytogenes was associated with foodborne illness outbreaks linked to ice cream in the United States from 2010 to 2015, with another recent outbreak under investigation. The FDA Bacteriological Analytical Manual (BAM) method was commonly used for L. monocytogenes detection. However, the performance characteristics of the chromogenic methods (MOX, RLM, and R&F agars) remain to be elucidated. The factorial effect on Level of Detection (LOD) as an essential element of the International Organization for Standardization (ISO) approach for qualitative method validation was investigated in this study.For examining the LOD of L. monocytogenes in ice cream, fractional contaminated samples were prepared with the ice cream obtained from the 2015 outbreak and enumerated using the FDA BAM Most Probable Number (MPN) method for Listeria. The effect of test portion size was determined by comparing 10g and 25g using the BAM method with chromogenic agars (MOX, RLM, and R&F). The ISO single-lab validation requirement was followed for the factorial effect study, including four different factors: sample size (10g and 25g), ice cream types (commercially available regular vanilla ice cream and vanilla ice cream with low fat and no added sugar), re-freezing process (with re-freezing and without re-freezing process), and thawing process (slow thaw and fast thaw). LOD and relative LOD (RLOD) were computed using MiBiVal software to compare the sensitivity of the three chromogenic agars and the different factors. For all of the detection experiments, presumptive colonies were identified using the API listeria kit. The 2015 naturally contaminated ice cream was enumerated and resulted in an average contamination level of 2.15 MPN/g. At fractional levels of 0.25 MPN/10g and 0.75 MPN/10g, the positive rates of L. monocytogenes detected from 10g and 25g of sample portions were consistent with the statistically theoretical positive rates. The RLOD values for the reference method (MOX) and the alternative methods (RLM, R&F) were above 1 in both portion sizes, which suggested that MOX was slightly more sensitive than RLM and R&F. The factorial effect study indicated that the four factors have no significant influence on the LOD of L. monocytogenes detection at the fractional contamination levels. However, the test portion size of 25g provided more consistent results among the chromogenic media than the 10g portion size. Fat content was shown to have an effect on L. monocytogenes detection in a large test portion. The information from this study will be useful for the improvement of the reproducibility of a qualitative detection method and can also be used for data analysis standards such as ISO 16140 in method validation studies.
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Title: High Energy High Power Primary Lithium Batteries with Graphite Fluoride and Functionalized Boron Nitride Cathodes
Creator: Huo, Haobin
Date: 2022
Description: The present Thesis concerns with the creation of high energy and high power batteries through the utilization of functionalized 2D materials...
Show moreThe present Thesis concerns with the creation of high energy and high power batteries through the utilization of functionalized 2D materials such as graphite fluoride (CFx) and functionalized boron nitride (FBN). The recent literature of Li-CFx batteries brings forward several methods to fabricate high energy and high power batteries. These methods include nano-architecture and porosity design, boron doping, electrolyte additives etc. The resulting batteries are capable to achieve 800-1000 Wh/kg energy density at a power density of 60-70 kW/kg. Our method is capable to achieve the same performance in a much simpler way by the application of a binder that also functions as an effective inhibitor of the growth of LiF crystals. Since LiF is the discharge product of Li-CFx batteries, it typically clogs the pores of the cathode and avoids fast discharge. Methods that increase the power density of Li-CFx batteries typically focus on the amorphization/dissolution of LiF to allow for a fast Li ion diffusion. Our solution using the effective binder appears to be well suited for a scalable production of high energy and high power Li-CFx batteries through a very small modification of existing production lines. Such high energy and high power batteries are needed for the electrification of aircraft such as unmanned aerial vehicles (UAVs), vertical take-off and landing planes (VTOLs), passenger airplanes and pulsed power sources. While Li-CFx batteries are not rechargeable this is not a problem for the above mentioned applications as current rechargeable batteries cannot provide the required energy and power densities.Li-FBN batteries may provide a rechargeable alternative to Li-CFx when fully developed. In the present thesis, we have demonstrated Li-FBN batteries with similar discharge plateaus and approximately half the capacity of Li-CFx batteries. Our Li-FBN batteries are also rechargeable to a much greater extent than Li-CFx.
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Title: Functionalized 2D Materials as Enablers of High Energy and High Power Energy Storage Devices
Creator: Radhakrishnan, Sivaviswa
Date: 2023
Description: The present Thesis concerns with the synthesis of novel functionalized 2D materials for applications as cathodes in lithium-ion batteries. It...
Show moreThe present Thesis concerns with the synthesis of novel functionalized 2D materials for applications as cathodes in lithium-ion batteries. It further concerns with the role of porosity in these novel cathode materials to achieve simultaneously high energy and power density. Examples of the novel cathode materials synthesized here include several functionalized hexagonal boron nitride (hBN) and graphene (G) species. hBN was functionalized with Li₂C₂O₄, LiBF₄, -OBF₂ groups, NOBF₄, etc. The color of the functionalized hBN species ranges from white through brown to black indicating drastic changes in the band structure of hBN due to functionalization. Functionalized G species include Li₂C₂O₄ and -OBF₃ functionalized ones. Preliminary electrochemical tests were carried out for an initial assessment of the properties of these materials. Additionally, the role of the DOL solvent was also investigated in high power CFx batteries
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Title: SYSTEMWIDE INTERSECTION SIGNAL TIMING OPTIMIZATION SIMULTANEOUSLY MINIMIZING VEHICLE AND PEDESTRIAN DELAYS
Creator: Roshandeh, Arash Moradkhani
Date: 2013, 2013-07
Description: The ever-growing traffic volume especially in urban areas stretches the transportation system to be operated at near or exceeding capacity and...
Show moreThe ever-growing traffic volume especially in urban areas stretches the transportation system to be operated at near or exceeding capacity and causes congestion. Expanding system capacity and effectively utilizing available capacity could help reduce traffic congestion. In most of cases, adding extra travel lanes in dense urban street networks is not feasible any more due to land scarcity. This study introduces a new method for signal timing optimization that is carried out by adjusting green splits of AM peak, PM peak, and rest of the day timing plans for each signalized intersection in the network without changing the existing cycle lengths and signal coordination to minimize total vehicle and pedestrian delays per cycle. The proposed method contains a basic model that handles vehicle delays only and an enhanced model that simultaneously addresses vehicle and pedestrian delays using two different pedestrian delay estimation methods. Both models are incorporated into an agent-based regional travel demand forecasting tool for detailed traffic assignments using data on Chicago regional travel demand, traffic counts, geometric designs, and signal timing plans for major intersections in the Chicago Central Business District (CBD) street network. The computational experiment reveals that vehicle delays in the CBD area could reduce by 10 percent when only considering vehicle delays and 5 percent when simultaneously considering vehicle and pedestrian delays for signal timing optimization. Considering the intersections safety analysis, it has been found that signals timing optimization in all four areas combined without considering pedestrian delays decreased different crash types under various severities for multiple vehicle collisions as well as vehicle-pedestrian ones. Taking care of both vehicles and pedestrians delay xvi vii simultaneously, using HCM method, just a very few situations represent slight increases in crash frequencies and all other cases indicate crash reductions. Compared with the sensitivity analysis results using the HCM method for calculating pedestrian delays in the enhanced model applications, the Levinson method produces different results even though crash frequency reduction trends are almost the same as HCM method results.
PH.D in Civil Engineering, July 2013
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Title: ASSESSMENT METHODS AND TOOLS FOR ARCHITECTURAL CURRICULA
Creator: Marriott, Christine A.
Date: 2012-03-26, 2012-05
Description: This research explores the process of assessment within the arena of architectural education by questioning traditional assessment practices...
Show moreThis research explores the process of assessment within the arena of architectural education by questioning traditional assessment practices and probing into the conditions that necessitate change. As architectural educators we have opened our studios to digital technologies for the purposes of design and representation, but how do we measure and judge new approaches to design process now that the tools students are using to solve problems have changed? New tools are available that allow us to examine the design process, but now that there are these new tools, how do we exploit them without completely uprooting our traditional assessment practices? Researchers have learned a great deal about how we learn, but how can this new understanding help to improve the learning that occurs in the architectural design studio? These are the questions that this research has investigated, and with an understanding of the conditions that surround architectural education, a model for assessment has been proposed. That model integrates the technology used for design and representation with the available tools of technology for the purpose of assessment and a growing body of knowledge about the way that we learn. This model is specific to the study of architecture and the teaching and learning of design process.
Ph.D. in Architecture, May 2012
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Title: MULTILEVEL ALGORITHMS FOR PHASE RETRIEVAL
Creator: Tanoue, Cullen
Date: 2015, 2015-05
Description: Phase retrieval is an important optimization problem that arises in di raction imaging, where the original structure of an object needs to be...
Show morePhase retrieval is an important optimization problem that arises in di raction imaging, where the original structure of an object needs to be reconstructed from its measured di raction data that does not have information concerning the phase of the object. Multilevel algorithms can be used to compute solutions to the standard phase retrieval optimization problem by constructing a hierarchy of problems using a series of restriction and prolongation operations. The coarser problems have a quarter of the variables as the ner problems, and hence, there are much less linear algebra requirements for solving the coarser problems. Further, the prolongation of the solutions computed for the coarser problems yield good starting points for the ner problems. We can also use an approach that alternates between solving the coarse and ne problem. Parameters for these methods include the number of levels, prolongation and restriction operations, and the number of iterations to perform at each level. We study the solutions to the standard phase retrieval optimization problem that result from exploring these parameters and compare them to the results obtained from using single-level methods.
M.S. in Applied Mathematics, December 2014
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Title: TEMPERAMENT AND CHILD AGENCY/PERSISTENCE: ARE THEY RELATED TO EARLY ACADEMIC ACHIEVEMENT?
Creator: D’aniello, Maria Elizabeth
Date: 2011-04-23, 2011-05
Description: It is well-known that early academic achievement is a significant predictor of later achievement. Thus, a number of studies have examined...
Show moreIt is well-known that early academic achievement is a significant predictor of later achievement. Thus, a number of studies have examined predictors of early academic achievement, but these have focused mainly on parenting variables, with relatively little attention paid to child variables, specifically temperament, or other child characteristics that may be related to early academic achievement. The aim of this study was to: (a) examine the relationship between child negative affect (NA), effortful control (EC), behavioral inhibition (BI), and agency/persistence and academic achievement; and (b) to determine if EC and agency/persistence moderated this relationship. Participants included 690 (322 males and 358 females) 5-year-old children and their primary caregivers. NA and EC were assessed by parent-report with the Child Behavior Questionnaire (CBQ). EC also was assessed with an observer-rated task, Gift Delay, which measures the child’s ability to delay a prepotent response. BI was assessed with two subtests from the NEPSY; Knock and Tap, and Statue. Child agency/persistence was assessed by a factor-analyzed composite of variables rated during the NICHD 3-Boxes Task. Letter-Word Identification, Passage Comprehension, and Quantitative Concepts subtests of the Woodcock-Johnson III were used as the measures of academic achievement. Results of hierarchical regression analyses indicated that NA, EC, BI and Agency/Persistence were not related to reading achievement, but BI and agency/persistence were related to math achievement. There also was no evidence of moderation of NA by EC or child agency/persistence. Implications of these findings and suggestions for further research are discussed.
M.S. in Psychology, May 2011
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Title: INTEGRATION OF DAYLIGHT IN THE COMMERCIALLY USED BUILDINGS FOR ENERGY SAVING PURPOSES
Creator: Tabibzadeh, Meysam
Date: 2014, 2014-07
Description: The integration between different building systems’ operation in response to various room and weather conditions has a direct positive effect...
Show moreThe integration between different building systems’ operation in response to various room and weather conditions has a direct positive effect on buildings energy performance and cost effectiveness. A Building Automation System (BAS) or an integrated Building Energy Management System (BEMS) typically control five major building systems, including people occupancy detection, shading control, HVAC, and lighting systems. Other building systems and internal energy loads also need to be considered when developing integrated controls and energy efficiency in office buildings. The controls are designed to operate in different building zones (lighting and thermal), while communicating with the main building management system. Whether the zone is being occupied or not will define further actions by other control components. The main goal of this research is to improve energy performance in commercial office buildings by developing the integration between various building controls and the use of natural light indoors and outside views while maintaining both the occupants’ visual and thermal comfort and high building energy performance at the same time. In this research, the proposed synchronization between building occupancy, daylighting, and integrated controls for various building systems in a commercial office space was assessed using computer simulations. The study uses Microsoft Excel as the primary database and result compiling platform. The work flow algorithm of the integrated control (in Visual Basic Application for Excel) automatically defines the new simulation criteria, makes adjustments in the simulation inputs, and runs DOE2.2 energy simulations for the proposed models with integrated controls as well as the baseline model (compliant with the ASHRAE 90.1-2010 standard) for further analysis. The simulations are conducted for eight simulation dates over five years. The results from the proposed model are analyzed and compared with the baseline results in order to evaluate its energy performance and to determine possible savings. The simulation results analysis determines how the implementation of the proposed system can improve the daylighting and energy performance in the building by maximizing the integration between different building systems controls in response to different parameters, such as occupancy, weather conditions, and daylight. The evaluated results of the proposed system are summarized as the system and sub-system algorithms, features, and components of each system, and, finally, as the design guidelines for implementation of the new fully integrated controls for commercial office buildings. From the evaluation of the proposed system performance, the list of research outcomes and deliverables will be concluded, by determining the impact of integrated controls on the overall energy performance of the office work space. The fact that if and when the energy efficiency and improved comfort and environmental quality work hand in hand, in addition to and the role of integrated occupancy in improving the energy efficiency will define the level of success for the proposed control system. The final research outcome is the development of the integrated workflow that can be used in new Building Automation Systems (BAS) or incorporated into the simulation engine for “Simulation Assisted” (see section 2.2.2) Building Energy Management Systems (BEMS).
Ph.D. in Architecture, July 2014
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Title: HYBRID ENERGY STORAGE SYSTEM TOPOLOGIES FOR ELECTRIC AND HYBRID ELECTRIC VEHICLES
Creator: Thiakos, Dimitrios
Date: 2014, 2014-05
Description: Progress has made over the last several years in developing cleaner, more fuel-efficient vehicles. In particular, hybrid electric vehicles ...
Show moreProgress has made over the last several years in developing cleaner, more fuel-efficient vehicles. In particular, hybrid electric vehicles (HEVs) have helped reduce fuel emissions by using electrical power to power the vehicle. HEVs have been enhanced by the use of hybrid-energy-storage-systems (HESS), which use an ultracapacitor to satisfy peak-power demands, thereby increasing the life of the battery. In this paper, dynamic models of the individual components of a HEV are created from dynamic equations, and then implemented in Simulink. The components include a realistic battery, an ultracapacitor, and a Permanent Magnet Synchronous Motor. The models are simulated, and the results serve as a basis for how these components should behave. Next, the various power management and control algorithms of a HESS are presented. Then, several HESS topologies are modeled in PSIM, which is a simulation tool for power electronics and motor drives. Simulation results for a simple drive-cycle are presented, and the pros and cons of each topology are described. Considerations are given as to the topologies with the best combination of performance, cost, and life cycle. Furthermore, the benefits of using a HESS in terms of cost, volume, weight, and efficiency, are explained in more detail. Finally, some limitations of PSIM that affected simulation results are explained. Overall, this thesis lays out the various factors that affect choices in HESS topologies.
M.S. in Electrical Engineering, May 2014
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Title: TOWARDS UNDERSTANDING BIG DATA MOLECULAR SIMULATION USING MACHINE LEARNING ALGORITHMS
Creator: Einakian, Mina
Date: 2016, 2016-05
Description: Analytical experiments and computer simulations have shown unusual thermal conductivity behavior of soft material under mechanical strain. At...
Show moreAnalytical experiments and computer simulations have shown unusual thermal conductivity behavior of soft material under mechanical strain. At first, the conductivity decreases with the increase of the mechanical strain. After reaching a certain minima, with the application of additional strain, it starts increasing. While this behavior is confirmed via experiments as well as computer simulations using molecular modeling techniques, what causes this behavior is still considered an open question. This thesis studies the molecular simulations data from multiple simulations and investigates the use of machine learning techniques to understand the unusual thermal conductivity behavior of soft materials under mechanical strain. The data sets consists of terabytes of data with thousands of spatial as well temporal attributes. In particular, the influence of attributes related to molecular structure including bond length, bond angle, and dihedrals has been probed. Several machine learning and data mining techniques including clustering and association rule mining have been applied on different datasets with different thermal conductivity to find the relationship between the soft material molecular structure and thermal conductivity behavior. The results show that in the alkyls molecules the most important features that affect the thermal conductivity are the O-CH2 bond properties, especially when thermal conductivity is equal to 1.5±ε . Keywords: Thermal conductivity, bond angle, bond length, dihedral angle, association rule mining, ANOVA significance test, K-means clustering.
M.S. in Computer Engineering, May 2016
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Title: A NEW METHODOLOGY FOR TRANSPORTATION DECISION-MAKING CONSIDERING PROJECT INTERDEPENDENCIES
Creator: Veliou, Eirini
Date: 2011-11-21, 2011-12
Description: The objective of transportation decision-making is to decide which projects to invest in and implement, such that total utility of the...
Show moreThe objective of transportation decision-making is to decide which projects to invest in and implement, such that total utility of the transportation network after project implementation viewed from economic (total cost to the transportation agency and the user), social (traffic mobility and safety), and environmental (energy consumption and vehicle emissions) dimensions is maximized. In current state-of-practices, decisions are made in accordance with project benefits that are estimated by independently capturing localized impacts of individual projects. The ignorance of network-level impacts and interdependency relationships of individual projects does not ensure accurately estimating project benefits and making truly optimal investment decisions based on estimated project benefits. This thesis first discusses the need for conducting a comprehensive study to estimate network-wide benefits of interdependent transportation projects and identify the most cost-effective sub-collection of projects under budget and other constraints for implementation. Using data on travel demand, roadway network designs, and traffic operations, as well as six major projects proposed for possible investments to the Chicago Loop area, the proposed methodology is applied to the Frontline Solver optimization software in a computational study. In general, the hypergraph Knapsack model as part of the proposed methodology is found to be able to identify the best sub-collection of investment projects for implementation under various budget levels. Specifically, the computational study has revealed that the overall benefits in terms of travel-time savings after considering project network-wide impacts and their interdependency relationships are much lower (by 38-64 percent) and the rate of benefit increase follows a diminishing trend with a higher level of budget, suggesting that an optimal level of investments can be established for mobility improvements. Future research directions are pointed out on developing efficient solution algorithms to identify a reasonably small number of possible sub-collection of projects that contains the optimal solution. It is also proposed to consider additional transportation costs items that extend from travel times to include costs of facility construction, rehabilitation, and maintenance and vehicle operations, crashes, and emissions in the estimation of network-wide benefits of single and multiple projects.
M.S. in Civil Engineering, December 2011
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Title: RECEIVER INITIATED MAC PROTOCOL FOR WIRELESS SENSOR NETWORK
Creator: Duan, Sze Ching Eric
Date: 2012-04-30, 2012-05
Description: In wireless sensor networks, wireless devices should wake up as necessary as possible to be able to communicate with neighbors and kept high...
Show moreIn wireless sensor networks, wireless devices should wake up as necessary as possible to be able to communicate with neighbors and kept high quality performance. On the other hand, it is also important that wireless devices remain sleeping as much as possible to maintain low power consumption. Thus a power efficient duty cycle mac protocol is required in wireless sensor networks. This thesis proposed a mac layer duty cycle protocol which uses receiver initiated wake up mechanism to allow device to keep their transceivers off most of the time to maintain energy efficiency. Also this report measures the energy consumption of the protocol and made comparisons with other popular mechanisms which shows the approach have successfully reduced energy consumption in compare to other popular protocols.
M.S. in Computer Science, May 2012
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