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Title: MODELING THE PERFORMANCE OF A SOLAR CHIMNEY WITH BUILT-IN PHASE CHANGE MATERIALS TO IMPROVE NATURAL VENTILATION
Creator: Khorraminejad, Aysan
Date: 2014, 2014-12
Description: The use of solar chimneys to improve natural ventilation in buildings has been shown to yield energy savings while maintaining thermal comfort...
Show moreThe use of solar chimneys to improve natural ventilation in buildings has been shown to yield energy savings while maintaining thermal comfort in some climate zones. However, one disadvantage is that the ability to control passive ventilation with solar chimneys is often limited by temporal variations of building function and diurnal weather patterns. The unique thermal properties of phase change materials (PCMs) may provide opportunities to manage some of the limitations of solar chimney strategies in buildings through the timed storage and release of thermal energy, which can aid in minimizing daytime heat gains and increasing the effectiveness of nighttime flushing by natural ventilation. This work explores the potential of PCMs combined with solar chimneys to support the passive ventilation of buildings using whole building energy simulation. Results are intended to inform architects and engineers on best practices for incorporating PCMs in buildings with solar chimneys. A model of a prototype office building designed to ASHRAE Standard 90.1 was developed in EnergyPlus and investigated in five U.S. climate zones. A total of 1023 energy simulations were performed to address the following research questions: (1) In what U.S. climate zone is the use of PCMs most appropriate? (2) Can PCMs improve night flushing ventilation when used with a solar chimney? (3) What are the optimal locations for installation of PCMs in building and solar chimney construction in order to provide optimal cooling load reductions? and (4) How do PCM properties influence cooling load reductions? Results demonstrate that the solidification and melting process of PCMs can indeed be used to prolong natural ventilation for night flushing in the evening and nighttime, particularly in climate zones with large diurnal outdoor temperature fluctuations. Results also suggest the following: (1) the optimal location for installation of PCMs in most climates is within the structure of south-facing envelope assemblies; (2) the PCM melting temperature should be equal to or greater than the zone set point temperature; (3) thicker PCMs can yield slightly more cooling energy savings than thinner PCMs; and (4) the thermal conductivity of PCMs does not appear to have a substantial influence on performance.
Ph.D. in Architecture, December 2014
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Title: Towards a Secure and Resilient Smart Grid Cyberinfrastructure Using Software-Defined Networking
Creator: Qu, Yanfeng
Date: 2022
Description: To enhance the cyber-resilience and security of the smart grid against malicious attacks and system errors, we present software-defined...
Show moreTo enhance the cyber-resilience and security of the smart grid against malicious attacks and system errors, we present software-defined networking (SDN)-based communication architecture design for smart grid operation. Our design utilizes SDN technology, which improves network manageability, and provides application-oriented visibility and direct programmability, to deploy the multiple SDN-aware applications to enhance grid security and resilience including optimization-based network management to recover Phasor Measurement Unit (PMU) network connectivity and restore power system observability; Flow-based anomaly detection and optimization-based network management to mitigate Manipulation of demand of IoT (MadIoT) attack. We also developed a prototype system in a cyber-physical testbed and conducted extensive evaluation experiments using the IEEE 30-bus system, IEEE 118-bus system, and IIT campus microgrid.
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Title: SIMULTANEOUS RELEASE OF BIOACTIVE AFLIBERCEPT AND DEXAMETHASONE FROM A MICROSPHERE- AND NANOPARTICLE-HYDROGEL OCULAR DRUG DELIVERY SYSTEM FOR THE ENHANCED TREATMENT OF NON-RESPONSIVE PATIENTS WITH CHOROIDAL NEOVASCULARIZATION
Creator: Rudeen, Kayla M
Date: 2022
Description: There is a growing subset of wet age-related macular degeneration (AMD) patients who do not fully respond to standard of care treatment, which...
Show moreThere is a growing subset of wet age-related macular degeneration (AMD) patients who do not fully respond to standard of care treatment, which consists of bimonthly/monthly bolus intravitreal injections of anti-vascular endothelial growth factors (anti-VEGFs). Some of these patients may respond to a combination therapy of anti-VEGF and corticosteroids. One treatment option uses a dexamethasone implant that releases for six months. This regimen, however, requires both the bimonthly/monthly intravitreal injections of anti-VEGF and semiannual intravitreal injections of the dexamethasone implant. Combining the two treatments into a single drug delivery system (DDS) would reduce the total number of injections, reducing the risk of potential complications (endophthalmitis, retinal detachment, intravitreal hemorrhage, increased intraocular pressure, and cataract) as well as the socioeconomic burden of treatment.The overarching goal of this study was to develop a single DDS that simultaneously releases anti-VEGF (aflibercept) and corticosteroid (dexamethasone) for the treatment of non-responsive wet AMD patients. Our laboratory previously developed a thermoresponsive, biodegradable microparticle-hydrogel DDS that releases anti-VEGF over a period of six months. The aims of the study were to (1) modify this system to include dexamethasone-loaded nanoparticles, optimize release kinetics for both drugs, and characterize the DDS; (2) evaluate the in vivo treatment efficacy in a laser-induced choroidal neovascularization (CNV) model; and (3) investigate the impacts of temperature and storage on the DDS integrity.
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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: MULTICRITERIA DECISION-MAKING METHODOLOGY WITH TRADEOFF ANALYSIS FOR TRANSPORTATION BUDGET ALLOCATION
Creator: Truong, Tung Quoc
Date: 2022
Description: Transportation agencies in the United States nowadays rely on tax dollars for maintaining surface transportation infrastructure, which mainly...
Show moreTransportation agencies in the United States nowadays rely on tax dollars for maintaining surface transportation infrastructure, which mainly comes from fuel tax. However, travel behaviors are changing every day. People and businesses demand better and safer roads. Yet, consumers travel in more fuel-efficient vehicles and buy less gas, which means less revenue for fixing aging roads and highways. Meanwhile, new construction and repair costs increase for our overburdened transportation systems. Transportation agencies, therefore, must use their limited funding more wisely to optimize the service performance and minimize risks (Li, 2018). The budget allocation problem in transportation is not an easy task. The consequences of an ineffective decision in allocating resources are multi-facet both in the short- and long-term, including degrading in the condition of transportation facilities, losing public trust, and increasing backlogs in maintenance and repair. Therefore, transportation agencies are seeking more robust and comprehensive data-driven strategies that take into account of agency’s strategic goals and regulatory requirements, user expectations, nature of the asset, availability of resources, and lifecycle cost analysis in determining the optimal allocation of resources and making the best use of available funds (Li and Sinha, 2004; Sinha and Labi, 2007). The proposed research aims to utilize the concept of multicriteria decision making coupled with a holistic asset management framework to support performance-based allocations of transportation budgets and help transportation agencies achieve the future vision of the nation’s strategic planning requirements to enable sustainable management of the system. A computational study for the real-world dataset obtained by a state Department of Transportation (DOT) is conducted using the proposed budget allocation method. The results from the computational study reveal that the proposed method can derive optimal decision solutions for transportation budget allocation problems and can be utilized by transportation agencies on different scales – urban and rural, in other sectors – public and private, to effectively manage the transportation infrastructure sustainably, by effectively spending transportation budget to maximize service performance and minimize operating costs.
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Title: MEASUREMENT OF ELECTRON NEUTRINO AND ANTINEUTRINO APPEARANCE WITH THE NOνA EXPERIMENT
Creator: Yu, Shiqi
Date: 2020
Description: As a long-baseline neutrino oscillation experiment, the NuMI Off-axis $\nu_e$ Appearance (NOvA) experiment aims at studying neutrino physics...
Show moreAs a long-baseline neutrino oscillation experiment, the NuMI Off-axis $\nu_e$ Appearance (NOvA) experiment aims at studying neutrino physics by measuring neutrino oscillation parameters using the neutrino flux from the Main Injector (NuMI) beam. It has two functionally identical detectors. The near detector is onsite at Fermi National Accelerator Laboratory. The far detector is 810 km away from the source of neutrinos and antineutrinos, at Ash River, Minnesota. At the near detector, muon neutrinos or antineutrinos, before significant oscillations take place, are used to correct the Monte Carlo simulation. At the far detector, the neutrino and antineutrino fluxes after significant oscillations have happened are measured and analyzed to study neutrino oscillation. The NOvA experiment is sensitive to the values of $\sin^2\theta_{23}$, $\Delta m^2_{32}$, and $\delta_{CP}$. The latest values from the NOvA 2020 analysis are as follows: $\sin^2\theta_{23}=0.57^{+0.03}_{-0.04}$, $\Delta m^2_{32}=(2.41\pm0.07)\times10^{-3}$ eV$^2$/c$^4$, and $\delta_{CP}=0.82\pi$ with a wide 1$\sigma$ interval of uncertainty. My study is focused on the neutrino oscillation analysis with NOvA, including detector light model tuning, particle classification with convolutional neural network, electron neutrino and antineutrino energy reconstruction, and oscillation background estimation. Most of my studies have been used in the latest NOvA publication and the NOvA 2020 analysis.
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Title: SAFETY AND MOBILITY IMPACTS ASSESSMENT OF THE CHICAGO BIKE LANE PROGRAM
Creator: Zhao, Yu
Date: 2021
Description: In recent years, bike as a travel mode is getting increasingly popular among large cities in the U.S. These cities also found promoting bike...
Show moreIn recent years, bike as a travel mode is getting increasingly popular among large cities in the U.S. These cities also found promoting bike mode can potentially mitigate traffic congestion issues, reduce carbon emission and improve the quality of life for residents. Therefore, many cities-initiated bike-related programs promote the bike mode from all aspects, such as establishing a shared bike system and developing bike-related facilities. Specifically, bike lane installation is widely seen in large cities as a pivot component of bike promotion programs. Due to the installation of bike lanes on the existing network, vehicles’ safety and mobility performance may be affected due to the variation of facilities. This study attempts to propose a methodology to quantify the safety and mobility impacts on vehicles brought by bike lane installation. The proposed method accounts for safety impact by using predicted crashes in conjunction with field observed crash data for empirical Bayes (EB) before-after comparison group analysis. The mobility impact is captured by comparing the segment average travel time before and after the bike lane installation. Further, vehicle volume information is involved in the consumer surplus computation to quantify the variation in vehicle safety, and mobility performance resulting from the bike lane installation. A case study is conducted using a real data set from the city of Chicago bike lane program. The results reveal that the safety and mobility impacts vary mainly depending on the type of bike lane installed and location.
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Title: Population Dynamics of Listeria monocytogenes in Nut, Seed and Legume Butters
Creator: Zhang, Xinyuan
Date: 2020
Description: Nut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that...
Show moreNut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that some pathogens, such as Listeria monocytogenes, can survive for long periods of time in butters, such as almond butter. However, information on the persistence of L. monocytogenes in butters is lacking. The purpose of this study was to determine the population dynamics of L. monocytogenes in butters stored at 5 and 25°C. Nut (almond, hazelnut, pecan), seed (pumpkin, sesame, sunflower), legume (peanut and soy) and butters containing chocolate (hazelnut and peanut) were inoculated with a 4-strain cocktail of rifampicin-resistant L. monocytogenes at 4 (high inoculation) or 1 log CFU/g (low inoculation). High inoculation butters were mixed by hand for 15 min and 100-g portions were weighed into deli-style containers with lids and stored at 5 or 25°C for 12 mo (370 d). Low inoculation butters were stored in 25- g portions in stomacher bags at 25°C for 6 mo (180 d). During storage, 25 g from the 100- g high inoculation portion or 25 g from the low inoculation samples, in triplicate, were homogenized with 225 mL BPB (or BLEB for FDA BAM enrichments when necessary) and serial dilutions of the homogenate were plated onto BHIA with rifampicin for enumeration of L. monocytogenes. Data were statistically analyzed using Student’s t-test (α=0.05). The average initial population of L. monocytogenes in the butters was 3.58±0.25 log CFU/g for the high inoculation butters; L. monocytogenes was detected through enrichments for all low inoculation butters. After 12 mo storage at 5°C, the population of L. monocytogenes decreased by 1.34, 1.27, 1.72, 2.04 and 0.93 log CFU/g in almond, hazelnut, peanut with chocolate, hazelnut with chocolate and pecan butter, respectively, when inoculated at the higher level. Significantly less population reduction was observed in pumpkin, sesame, soy, peanut and sunflower butters (1.08, 0.61, 0.84, 0.05 and 0.40 log CFU/g, respectively). After 12 mo storage at 25°C, the L. monocytogenes population in all butters, with the exception of sunflower butter, decreased to below the limit of enumeration (1.67 log CFU/g), but the pathogen was still present via enrichment. For low inoculation butters, L. monocytogenes was present as determined by enrichment in all butters in at least one of two trials after 6 mo. The results of this study provide information on the survival of L. monocytogenes in different butter types when stored at different temperatures.
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Title: ATOMIC LAYER DEPOSITION STUDIES OF GOLD AND TUNGSTEN DISULFIDE
Creator: Liu, Pengfei
Date: 2020
Description: In the last few decades, atomic layer deposition (ALD), as a vapor deposition technique and a powerful thin film fabrication method, has...
Show moreIn the last few decades, atomic layer deposition (ALD), as a vapor deposition technique and a powerful thin film fabrication method, has received more and more attention in many fields. A variety of materials can be made by ALD; however, the progress of ALD application is still necessary. Meanwhile, in the process of film fabrication by ALD, the interfacial chemistry is interesting and well worth studying. This dissertation mainly described the process of exploring two materials, gold and tungsten disulfide, fabrication and related content.For the portion of applying ALD in gold thin film deposition, a relatively comprehensive process was explored, studied, analyzed and discussed. Start with the synthesis of the gold precursor, Me2Au(S2CNEt2), the synthetic reaction was explored. By modified the conditions, such as solvent system, twice the yield as previously reported in the literature were achieved. Next, the application of in situ microbalance and infrared spectroscopic technique illuminate the organometallic chemistry during the gold thermal ALD process with Me2Au(S2CNEt2) and ozone. In situ quartz crystal microbalance (QCM) studies give an explanation for the nucleation delay and island growth of gold on a freshly prepared aluminum oxide surface. In situ infrared spectroscopy provides insight to study the surface chemistry during the process, which supports an oxidized gold surface mechanism. The epitaxy of gold thin film was explored by X-ray diffraction. The thermal ALD gold on various substrates reveals out-of-plane orientation, however, in-plane orientation was only existed in the gold film on mica. For the portion of applying ALD in tungsten disulfide fabrication, the early work started with studying the effect of interfaces upon crystallinity. The sulfuration of indium thin film with different interface was explored. Then the idea of “interfaces” was brought into the process of tungsten compounds fabrication. Due to this “indirect” method which made tungsten disulfide by sulfurizing ALD made tungsten compounds (eg. tungsten oxide and tungsten nitride) could not reduce the reaction temperature of tungsten disulfide synthesis to less than 400 °C. Sequently, the “direct” way of tungsten disulfide fabrication which directly utilized tungsten precursor and H2S in ALD system was tested and explored. With the tungsten precursors developed by our group, finally, tungsten disulfide could be fabricated at the temperature as low as 125 °C.
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Title: Exploiting contextual information for deep learning based object detection
Creator: Zhang, Chen
Date: 2020
Description: Object detection has long been an important research topic in computer vision area. It forms the basis of many applications. Despite the great...
Show moreObject detection has long been an important research topic in computer vision area. It forms the basis of many applications. Despite the great progress made in recent years, object detection is still a challenging task. One of the keys to improving the performance of object detection is to utilize the contextual information from the image itself or from a video sequence. Contextual information is defined as the interrelated condition in which something exists or occurs. In object detection, such interrelated condition can be related background/surroundings, support from image segmentation task, and the existence of the object in the temporal domain for video-based object detection. In this thesis, we propose multiple methods to exploit contextual information to improve the performance of object detection from images and videos.First, we focus on exploiting spatial contextual information in still-image based object detection, where each image is treated independently. Our research focuses on extracting contextual information using different approaches, which includes recurrent convolutional layer with feature concatenation (RCL-FC), 3-D recurrent neural networks (3-D RNN), and location-aware deformable convolution. Second, we focus on exploiting pixel-level contextual information from a related computer vision task, namely image segmentation. Our research focuses on applying a weakly-supervised auxiliary multi-label segmentation network to improve the performance of object detection without increasing the inference time. Finally, we focus on video object detection, where the temporal contextual information between video frames are exploited. Our first research involves modeling short-term temporal contextual information using optical flow and modeling long-term temporal contextual information using convLSTM. Another research focuses on creating a two-path convLSTM pyramid to handle multi-scale temporal contextual information for dealing with the change in object's scale. Our last work is the event-aware convLSTM that forces convLSTM to learn about the event that causes the performance to drop in a video sequence.
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Title: IMPACT OF DATA SHAPE, FIDELITY, AND INTER-OBSERVER REPRODUCIBILITY ON CARDIAC MAGNETIC RESONANCE IMAGE PIPELINES
Creator: Obioma, Blessing Ngozi
Date: 2020
Description: Artificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical...
Show moreArtificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical diagnosis, disease prediction, and treatment, with such interests intensifying in the medical image field. AI can automate various cumbersome data processing techniques in medical imaging such as segmentation of left ventricular chambers and image-based classification of diseases. However, full clinical implementation and adaptation of emerging AI-based tools face challenges due to the inherently opaque nature of such AI algorithms based on Deep Neural Networks (DNN), for which computer-trained bias is not only difficult to detect by physician users but is also difficult to safely design in software development. In this work, we examine AI application in Cardiac Magnetic Resonance (CMR) using an automated image classification task, and thereby propose an AI quality control framework design that differentially evaluates the black-box DNN via carefully prepared input data with shape and fidelity variations to probe system responses to these variations. Two variants of the Visual Geometric Graphics with 19 neural layers (VGG19) was used for classification, with a total of 60,000 CMR images. Findings from this work provides insights on the importance of quality training data preparation and demonstrates the importance of data shape variability. It also provides gateway for computation performance optimization in training and validation time.
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Title: Improving self-supervised monocular depth estimation from videos using forward and backward consistency
Creator: Shen, Hui
Date: 2020
Description: Recently, there has been a rapid development in monocular depth estimation based on self-supervised learning. However, these existing self...
Show moreRecently, there has been a rapid development in monocular depth estimation based on self-supervised learning. However, these existing self-supervised learning methods are insufficient for estimating motion objects, occlusions, and large static areas. Uncertainty or vanishing easily occurs during depth inferencing. To address this problem, the model proposed in this thesis further explores the consistency in video and builds a multi-frame model for depth estimation; secondly, by taking advantage of the optical flow, a motion mask is generated, with additional photometric loss applied for those masked regions. Experiments are carried out on the KITTI dataset. The proposed model performs better than the baseline model in quantitative results, and as seen from the depth map, the scale uncertainty and depth incomplete situations are improved in motion objects and occlusions explicitly.
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Title: IMPROVING PEDESTRIAN DETECTION USING OPTICAL FLOW
Creator: Kong, Lingxing
Date: 2015, 2015-12
Description: Pedestrian detection, which has wide applications on surveillance, automatic driving and robotics, plays a significant role in computer vision...
Show morePedestrian detection, which has wide applications on surveillance, automatic driving and robotics, plays a significant role in computer vision. Among all kinds of pedestrian detection methods, stereo based method achieves an accurate and efficient detection result by exploiting depth and color information. However, many stereo based systems fail at considering motion information which is important in locating and detecting an object. For many pedestrian detection systems, adding extra data like motion is one of the most effective ways to improve the performance. Therefore, this thesis proposes a multi-cue pedestrian detection system which integrates optical flow based and stereo based modules for combining motion, depth and color information. In the proposed system, optical flow and disparity value are estimated by using the frames which obtained from a stereo camera. In order to obtain accurate pedestrian motion, ego motion is compensated by using motion clustering, affine model and RANSAC. After that, the motion and the depth information are exploited for ROI generation. Finally, SVM is trained by the combination of motion feature and HOG feature. Experimental results show that the use of high-accuracy optical flow along with depth and color information improves the performance of multi-cue pedestrian detection system.
M.S. in Electrical Engineering, December 2015
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Title: AN AUTOMATED ENGINEERING PROCESS TO VERIFY THE CORRECT COORDINATION OF MULTILAYER RECOVERY
Creator: Kroculick, Joseph
Date: 2017, 2017-05
Description: Recovery is a critical function in backbone networks. The primary function of recovery is to provide connectivity regardless of which layer...
Show moreRecovery is a critical function in backbone networks. The primary function of recovery is to provide connectivity regardless of which layer recovery operates at. Another function of recovery is for all services traversing a failed link to be restored in a way that is consistent with a service user’s requirements. These requirements can include the consideration of factors such as (1) the cost of recovery, (2) the amount of traffic restored, and (3) the delay in restoring units of traffic. With more options available to recover traffic, providing an integrated recovery solution is necessary. An important force driving the evolution of network devices to transport services such as IP traffic is the layering of network resources. Layering enables networks to increase capacity by extending legacy SONET networks to interface with optical wavelengths. Inconsistent provisioning can prevent service continuity from being achieved during a failure. Continuity of service has been recognized as one key business goal. Furthermore, since recovery can occur at a different time than when it is provisioned, inconsistent provisioning is determined after the fact, with services left unrepaired, repaired unnecessarily at an extra cost, or not repaired fast enough. A network manager can check if recovery is consistent with a global perspective on how traffic should be restored by comparing the provisioning at each device against suitable properties of a formal representation. To address this issue an engineering method was developed to detect errors in provisioning automated recovery processes in multilayer and multiprotocol transport networks. This dependability assessment process (DAP) leverages inference techniques provided by Semantic Web technologies in order to detect network-device provisioning errors. Provisioning should be accompanied by methodologies, processes, and activities to ensure that it can be trusted to achieve a desired network state. The DAP takes into account unique constraints in the telecommunications domain including bottom-up evolution of physical layer technologies to provide connectivity, and lack of a universal model of network functionality. This method is applied to assessing the correctness of provisioning decisions for a protection switching application in a transport network in both the spatial and temporal domains.
Ph.D. in Computer Science, May 2017
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Title: VANADIUM OXIDE BASED MATERIALS AS OXIDATIVE DEHYDROGENATION CATALYST: SYNTHESIS, CHARACTERIZATION AND PROPERTIES
Creator: Aydemir, Kadir
Date: 2013, 2013-12
Description: The project concerns with design, synthesis and characterization of molecular and extended structure materials composed of vanadium oxides and...
Show moreThe project concerns with design, synthesis and characterization of molecular and extended structure materials composed of vanadium oxides and evaluation of their catalytic oxidative dehydrogenation (ODH) properties. A long-term objective is to develop an understanding of the structure-property relationships in ODH catalysts. Chapter 1 provides an overview of the field of metal oxides, polyoxometalates, and catalytic oxidative dehydrogenation of propane. This chapter also defines the research problem concerning this thesis and its fundamental and practical significance. Chapters 2-4 describe the synthesis, characterization and ODH properties of a select number of structurally correlated vanadium oxide based materials. The ODH catalysts studied in this work includes molecular compounds - (NH4)8[VIV 12VV 6O42(SO4)0.85(VO4)0.15]·10H2O (NH4-POV) and NH4V10O28, layered structure materials - MgVV 2VIV 2O10·4H2O (MV4) and V2O5, a chain structure - NH4VO3, and a nanostructured three-dimensional framework material - [Co3V18O42(H2O)12 (XO4)]·24H2O (X = V, S) (Co-POV). Their catalytic activities for ODH of propane to propylene - an important industrial feedstock material, were studies and compared in an attempt to get an insight of the structure-property relationships. Chapter 2 discusses synthesis and characterization of a new mixed-valence vanadate, MgVV 2VIV 2O10·4H2O (MV4), an extended structure solid, synthesized hydrothermally and characterized by single-crystal X-ray diffraction, spectroscopic methods, thermogravimetric analyses and temperature dependent magnetic measurements. MV4 represents the first model compound for the naturally occurring mineral melonovanadite, Ca2VV 4VIV 4O20·10H2O. MV4 is an important material with xv structural and electronic properties that are attractive for making it a potential promising ODH catalyst. The framework structure in MV4 consists of vanadium oxide layers crosslinked by {Mg(H2O)4} groups. The vanadium oxide layers are composed of edge shared {VIVO5} square pyramids, forming {V2O8} dimers, which share corners with {VVO4} tetrahedral units. Chapter 2 also discusses synthesis of a novel mixed-valence molecular polyoxovanadate - (NH4)8[VIV 12VV 6O42(SO4)0.85(VO4)0.15]·10H2O (NH4-POV) and its characterization by single-crystal X-ray diffraction, spectroscopic and thermogravimetric analyses. Structure consists of {V18O42} shell composed of 18 edge sharing {VO5} square pyramids, hosting a tetrahedral species {XO4} (X = S, V). Highly reduced molecular structure of NH4-POV makes it a promising ODH catalyst. Chapter 3 describes the ODH properties of a polyoxovanadate based openframework material - [Co3V18O42(H2O)12 (XO4)]·24H2O (X = V, S) (Co-POV). It is composed of {V18O42(XO4)} (X = S, V) building units, which is the molecular cluster present in NH4-POV, interconnected by {-O-Co-O-} bridging groups. Alternatively, since the building unit clusters {V18O42XO4} can be viewed as derived from sheets of V2O5, the 3-D structure of Co-POV can be viewed as made of V2O5 and CoO units. Therefore the ODH property of Co-POV was compared with the ODH property of the molecular cluster NH4-POV on one hand and with the V2O5 and CoO on the other hand. Co-POV was shown to have superior catalytic performance for ODH of propane as compared with its constituent metal oxides, V2O5, CoO and their mixture. ODH of propane reaction over NH4-POV catalyst has higher propylene selectivity of above 60% at moderate temperatures as compared to 37% selectivity of Co-POV catalyst. Supporting NH4-POV on high surface area γ-alumina was shown to improve propane xvi conversion drastically. In this study, highest propylene yield of 13% was achieved at 550 °C by supported NH4-POV catalyst. On the other hand, MV4 showed catalytic activity at marginally low temperature 200 °C due to propane activation energy (Ea) of 27 kJ/mol, the lowest Ea found in this study. Co-POV was utilized as a model compound to describe the effect of varying doses of γ-ray irradiation on the catalytic ODH properties of polyoxometalates for the first time. γ-ray irradiation enhanced catalysts’ selectivity to propylene during the oxidative dehydrogenation of propane. Chapter 4 describes full characterization of the catalysts studied in this work by powder X-ray diffraction analysis, temperature programmed reduction, X-ray absorption fine structure, BET surface area analysis and scanning electron microscopy. Structural changes of catalysts were investigated by comparing characterization results of asprepared, oxygen pretreated and post-catalysis (spent) catalysts. New vanadium oxide phases formed upon oxygen pretreatment. In general, ODH catalysis did not further alter catalysts’ structures.
PH.D in Chemistry, December 2012
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Title: LATTICE DESIGN OF THE INTEGRABLE OPTICS TEST ACCELERATOR AND OPTICAL STOCHASTIC COOLING EXPERIMENT AT FERMILAB
Creator: Kafka, Gene
Date: 2015, 2015-05
Description: The Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab will serve as the backbone for a broad spectrum of Advanced Accelerator...
Show moreThe Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab will serve as the backbone for a broad spectrum of Advanced Accelerator R&D (AARD) experiments, and as such, must be designed with significant flexibility in mind, but without compromising cost efficiency. The nonlinear experiments at IOTA will include: achievement of a large nonlinear tune shift/spread without degradation of dynamic aperture; suppression of strong lattice resonances; study of stability of nonlinear systems to perturbations; and studies of di↵erent variants of nonlinear magnet design. The ring optics control has challenging requirements that reach or exceed the present state of the art. The development of a complete self-consistent design of the IOTA ring optics, meeting the demands of all planned AARD experiments, is presented. Of particular interest are the precise control for nonlinear integrable optics experiments and the transverse-to-longitudinal coupling and phase stability for the Optical Stochastic Cooling Experiment (OSC). Since the beam time-of-flight must be tightly controlled in the OSC section, studies of second order corrections in this section are presented.
Ph.D. in Physics, May 2015
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Title: ANALYSIS AND CONTROL OF COMPRESSION-IGNITION AND SPARK-IGNITED ENGINES OPERATING WITH DUAL-FUEL COMBUSTION STRATEGY
Creator: Kassa, Mateos
Date: 2017, 2017-07
Description: In recent years, the implementation of a dual-fuel combustion strategy has been explored as a means to improve the thermal efficiencies of...
Show moreIn recent years, the implementation of a dual-fuel combustion strategy has been explored as a means to improve the thermal efficiencies of internal combustion engines while simultaneously reducing their emissions. The dual-fuel combustion strategy was introduced in compression ignition engines to control the combustion phasing by varying the proportion of two simultaneously injected fuels, and altering the combustion timing. The dual-fuel injection strategy also allowed to extend the load limitation of advanced combustion engines, since the two injected fuel ignite in succession reducing the high peak pressures that generally act as a limiting factor. In spark-ignited (SI) engine, the implementation of a dual-fuel combustion strategy serves as an alternative approach to avoid knock (the inadvertent auto-ignition of the fuel mixture). Although conventional engines rely on delaying spark timing to avoid knocking cycles (which significantly reduces the thermal efficiency), the dual-fuel SI engine rely on the simultaneous injection of a low knock resistance and high knock resistance fuel to dynamically adjust the fuel resistance to knock as required. The dual-fuel SI engine thereby successfully suppresses knock without compromising the engine efficiency. Despite the benefits of the dual-fuel combustion strategy, several challenges arise in its implementation, especially when it is implemented along with other advanced combustion strategy leveraging variable valve timing, exhaust gas recirculation, turbocharging, and so forth. This study explores some of these challenges and addresses them from a control standpoint. Cylinder-to-cylinder variations is identified as one of the main challenges. An in-cylinder oxygen estimation strategy and modification to the conventional fueling strategy are proposed as approaches to reduce the combustion variations. In SI engines, the valve dynamics in transient operations are shown to negatively impact the dual-fuel control strategy. The effect of the valve timing on knock propensity and the resulting effect on the fueling strategy is investigated. Finally, the dual-fuel SI engine relies on measurements of the combustion intensity to adjust the fuel split between the low RON and high RON fuel. The implementation of a conventional knock control is shown to be counterintuitive for dual-fuel SI engines due to the highly reactive nature of the controller and the deterministic approach that assumes cycle-to-cycle correlation of the combustion intensity. Statistical investigation of the combustion intensity metric is conducted to identify key properties that can be leveraged for more effective control strategy.
Ph.D. in Mechanical, Material and Aerospace Engineering
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Title: VALUE OF BATTERY STORAGE SYSTEM IN THE FEREQUENCY REGULATION MARKETS OF PJM AND CAISO
Creator: Khorsand, Shervin
Date: 2017, 2017-05
Description: With an increasingly urgent need to decrease our utilization of fossil fuels, renewable power sources such as wind and solar are being...
Show moreWith an increasingly urgent need to decrease our utilization of fossil fuels, renewable power sources such as wind and solar are being incorporated in the electricity grid. However, these sources lack the conventional reliability that fossil fuels, such as natural gas, and oil have previously provided. The solution lies in energy storage, and exactly why battery storage systems are the means for renewable energy sources to become truly transformative and revolutionize the energy market. In the first part of this paper, a comprehensive summary of the different types of energy storage technologies have been provided along with their features, which make each technology suitable for different applications. Next, a detailed chapter focused on battery storage systems and their properties is provided along with the ancillary services they offer as sustenance and support sources integrated in the electric grid. These service are integral to the continuous transmission of power to consumers, and necessary for the supply to meet end-user demands. Among these service include frequency regulation as well as spinning reserve services, the latter being important under emergency condition following a power disruption. Regulation services however, are constantly required for grid stability and reliability, which is why this service was selected for further market analysis. For this market analysis, the California Independent Systems Operator (CAISO), and PJM Interconnection (PJM) were selected as both have extensive regulation markets and two of the major power suppliers nationwide. The main question in conducting this analysis was to determine which market would be more attractive and profitable for a potential regulation provider to invest using a Lithium ion battery. The Regulation Market Clearing Price (RMCP) for each market was extracted from the operators’ annual reports over the last six years and used as measure of investor revenue. The Levelized Cost of Energy Storage was computed for a Lithium ion battery with certain characteristics, and the investor revenue was calculated as a percent of the LCOE. Our analysis showed that although CAISO’s regulation market is showing growth in the recent years, especially in 2016 during the period of increased regulation requirement, PJM has had consistently higher RMCP values, which means the investor revenue would be higher in PJM. Our calculations show that investing a Lithium ion battery with a power rating of 10MW, and energy capacity of 5 MWh, operating at 89% efficiency for 4.8 cycles per day for 350 days in PJM is going to be economically a much smarter choice.
M.S. In Electrical Engineering, May 2017
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Title: MODERATING EFFECT OF MINDFULNESS IN THE RELATIONSHIP BETWEEN CARDIOVASCULAR DISEASE RISK FACTORS
Creator: Kim, Jeong Hye
Date: 2016, 2016-07
Description: Cardiovascular diseases (CVDs) are the leading cause of death worldwide and in the United States. Weight loss, which is associated with blood...
Show moreCardiovascular diseases (CVDs) are the leading cause of death worldwide and in the United States. Weight loss, which is associated with blood pressure and blood glucose, is widely recommended to modify the CVDs risk factors. Among various methods, mindfulness has been extensively studied in improving psychological and physical health. There is some reported evidence that mindfulness based interventions are effective in improving CVDs risk factors. However, overall results are inconclusive. Therefore, more research examining the facets of mindfulness is necessary to understand the fundamental relationship between mindfulness and CVDs risk factors to clarify the effect of mindfulness. In addition, research into whether the relationship between different risk factors is moderated by mindfulness would provide further support of the independent effect of mindfulness on physical health. The current study hypothesized that higher mindfulness skills would correlate with physical well-being. Furthermore, it was hypothesized that mindfulness will moderate a relationship between BMI and other CVDs risk factors (e.g., individuals with higher BMI classification and higher mindfulness will show lower blood pressure compared to individuals at a similar BMI with lower mindfulness). Results found that body adiposity had an inverse relationship with overall mindfulness, and two of the four facets of mindfulness (Describing and Acting with awareness). In addition, the Describing subscale had a significant moderating effect; however, the relationship between body adiposity and systolic blood pressure was stronger rather than weaker with higher Describing skills.
M.S. in Psychology, July 2016
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Title: IMPROVED METHODS FOR DETECTING PARTIALLY HYDROLYZED SOY IN FOOD
Creator: Kande, Parnavi
Date: 2016, 2016-12
Description: Methods are needed to detect soy allergens in hydrolyzed and fermented food. Project objectives included utilizing soy-specific ELISA kits and...
Show moreMethods are needed to detect soy allergens in hydrolyzed and fermented food. Project objectives included utilizing soy-specific ELISA kits and Western blot analysis to a) measure soy protein content of commercial soy sauce products; b) trace soy proteins in model soy sauces during a traditional brewing process, and c) investigate detection of soy proteins in soy protein isolate (SPI) hydrolyzed with trypsin. Twelve different soy sauce products were purchased locally. Traditionally brewed soy sauce formulated with soybeans and wheat was produced by Kikkoman in their pilot plant in Japan. Samples were obtained at the ingredient stage, after the soybeans were cooked, at the koji and moromi mash stages, and during six months of fermentation. Partially hydrolyzed SPI was prepared by treating SPI with trypsin for up to 8 h at 38 ºC. Samples were analyzed in triplicate using six soy-specific ELISA kits: 1) Neogen Veratox for Soy; 2) Ridascreen Fast Soya; 3) Elution Technologies Soy Protein; 4) Morinaga Soya; 5) AgraQuant Soy and 6) ELISA Systems Soy Protein. Western blot analysis was performed using Morinaga Soy ELISA kit antibodies. Of the 12 commercial soy sauce products, soy protein was detected in seven products at concentrations of 7.0 (1.7% CV) - 10.5 (1.8% CV) μg/g using the Elution Technologies kit, and in five samples at concentrations of 0.31 (0.6% CV) - 1.5 (0.3% CV) μg/g with the Morinaga kit. Qualitative Western blot analysis suggested the presence of beta-conglycinin in five commercial brands. Tracking soy proteins in model soy sauce by ELISA resulted >90% decrease in detection after cooking. After addition of koji culture and brine to form the moromi mash, soy protein levels were further reduced. The measured level of soy protein after one month of fermentation was 0.67 μg/g (1.1% CV) and decreased below the limit of quantitation (LOQ, 0.31 μg/g) for samples aged 2-6 months using the Morinaga assay, while other kits resulted in soy protein concentrations below the LOQ. Western blot results showed light bands of proteins for samples after 1-2 months of fermentation suggesting the presence of beta-conglycinin. Trypsin hydrolysis of SPI resulted in a gradual decrease in soy protein bands in SDS-PAGE analysis, while some ELISA kits indicated no changes in detectability of soy proteins after 10 min of hydrolysis. Overall, the results of this study indicate that heating, hydrolysis and fermentation processes can have substantial effects on the detection of soy proteins in food.
M.S. in Food Safety and Technology, December 2016
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