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Title: Quantum Computation for the Understanding of Mass: Simulating Quantum Field Theories
Creator: Rivero Ramírez, Pedro
Date: 2021
Description: This thesis demonstrates the production of hadron mass on a quantum computer. Working in the Nambu–Jona-Lasinio model in 1+1 dimensions and 2...
Show moreThis thesis demonstrates the production of hadron mass on a quantum computer. Working in the Nambu–Jona-Lasinio model in 1+1 dimensions and 2 flavors, I show a separation of the contribution of quark masses and interactions to the mass. Along the way I develop a new tool called Quantum Sampling Regression (QSR) that allows for an optimal sampling of low qubit quantum computers when using hybrid variational eigenvalue solving techniques. I demonstrate the regime where QSR dominates the current standard Variational Eigensolver Technique, and benchmark it by improving the calculation of deuteron binding energy. Finally, I developed QRAND — a multiprotocol and multiplatform quantum random number generation framework — in support of the quantum computing community.
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Title: ELECTROSPUN SILKWORM SILK FIBROIN - INDOCYANINE GREEN BIOCOMPOSITE FIBERS: FABRICATION, CHARACTERIZATION AND APPLICATION TOWARDS HEMORRHAGE CONTROL
Creator: Siddiqua, Ayesha
Date: 2022
Description: Silk fibroin (SF), a structural protein found in the Bombyx mori cocoons has gained attention in several biomedical applications as tissue...
Show moreSilk fibroin (SF), a structural protein found in the Bombyx mori cocoons has gained attention in several biomedical applications as tissue engineering scaffolds and wound dressings owing to its properties such as biocompatibility, water vapor permeability and biodegradability. Indocyanine Green (ICG) is an FDA approved tricarbocyanine dye used in medical diagnostics due to its unique photothermal and fluorescent properties. Electrospinning is a highly efficient, easy, and inexpensive technique used to generate nanometer to micrometer thick fibers. In this study, SF and ICG were co-spun to generate flexible microfibers with high surface area to volume ratios. Pure silk, SF-ICG (0.1%) and SF-ICG (0.4%) were chosen for the purpose of this study. Since, as-spun fibers are unstable in aqueous solutions, post treatment methods were explored to enhance the durability of the fibers and to minimize ICG leaching. It was found that ethanol vapor treatment (EVT) not only induced β-sheet formation in SF but also improved the SF-ICG interaction thereby reducing ICG leaching from the composite fibers. Ethanol vapor treated SF-ICG fibers showed less ICG leaching than liquid ethanol treated (LET) SF-ICG fibers indicating the efficacy of the EVT. The increase in SF solution viscosity with ICG concentration suggested a strong silk-ICG interaction which was further confirmed by DSC. The 1h water uptake and the three-day mass loss experiments indicated that the fibers are stable and highly absorbent material. Heat evolution was evaluated by measuring the temperature change in water of a fixed volume after irradiation with a 500 mW, 808 nm diode laser. The heat evolved by the flat fiber scaffolds was higher than the 3D fiber balls, indicating improved light penetration in the former. Pure silk produced negligible heat and it was used as a control. With 14.9 W/cm2 irradiation, the post-treated SF-ICG (0.4%) 3D fibrous ball of 2-3 mg dry weight, solidified a drop of bovine blood in 40 s. In contrast, a single layer fiber matrix required 3 min. to achieve the same clotting effect. Fibers folded into flat scaffolds were able to solidify a blood drop in 25 s. Pure silk fibers in all the cases showed negligible change after irradiation. The results suggest that a larger contact area of fibers is desirable for faster blood clotting, and EVT prompted better ICG retention in SF fibers. Based on the above results, SF-ICG (0.4%) fibers were utilized in a device developed to mimic blood flowing at a rate of 0.5 mL/h through a damaged blood vessel. It was found that irradiation of SF-ICG locally placed at the “damage” region effectively stopped “bleeding” whereas irradiated pure silk was unable to control the blood flow, which demonstrated the success of our SF-ICG fibers towards hemorrhage control.
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Title: Advanced methods for storage ring nonlinear beam dynamics design and implementation
Creator: Song, Minghao
Date: 2022
Description: To meet the increasing demands of scientific researchers for brighter photonbeams, storage ring beam emittance is continually pushed down to a...
Show moreTo meet the increasing demands of scientific researchers for brighter photonbeams, storage ring beam emittance is continually pushed down to a new ultra-low level. It, therefore, becomes correspondingly more challenging to ensure such storage rings have good nonlinear beam dynamics performance. This thesis work is focused on developing advanced methods for low emittance storage ring nonlinear beam dynamics design and implementation.Nonlinear beam dynamics optimization is essential to low emittance storagering design. A highly efficient multi-objective optimization algorithm is needed to simultaneously achieve a large dynamic aperture and a large local momentum aperture. Work was done to improve and test a machine learning-based algorithm called multi-generation Gaussian process optimizer (MG-GPO). This advanced method uses constructed GP models to pre-select solutions, and benchmarking of results on toy problems shows that MG-GPO converges significantly faster than traditional algorithms. The MG-GPO algorithm was successfully applied to nonlinear lattice design optimization, for example, to the SPEAR3 upgrade 7-nm lattice, and it was demonstrated to converge faster than NSGA-II and MOPSO. This was due to its capability of selecting candidates that tend to have better performance. This algorithm will help accelerate nonlinear lattice studies.Correction of nonlinear beam dynamics is also important for low emittancestorage ring commissioning and operation. In order to measure and correct features relevant to the nonlinear beam dynamics, an effective method is needed to excite sustained beam oscillations to large amplitude. A method based on the concept of autoresonance was proposed. This advanced technique excites nonlinear transverse beam motion in storage rings by sweeping the drive frequency. The theory for the autoresonance threshold was derived for the nonlinear optics systems in storage rings, both with and without damping effects, using Hamiltonian dynamics. The theoretical predictions for the drive amplitude threshold were found to agree well with simulations for a simple storage ring model, as well as for simulations with the actual SPEAR3 and APS lattices. The theory was also compared favorably to historical data from experiments on SPEAR3. Simulations verified that an oscillation driven by autoresonant excitation matches the character of a free oscillation, so that beam oscillation data taken during the ramping process can confidently be used to characterize the nonlinear beam dynamics performance. The precision of measurements can be improved by using autoresonant excitation since large amplitude beam oscillations are sustained significantly longer. Simulations of autoresonant excitation demonstrated the measurements of the detuning coefficients and resonance driving terms. The use of autoresonant excitation for the detection of faulty magnets and correction of resonance driving terms was also demonstrated.Online optimization is an alternative way to effectively improve nonlinear beamdynamics performance in a real storage ring. The greater efficiency of an advanced optimization algorithm is also needed to find globally optimal solutions in the limited experimental time that is typically available. The MG-GPO algorithm was implemented for SPEAR3 vertical emittance minimization and injection efficiency optimization. Again, the optimized solutions demonstrate that MG-GPO is more efficient than the commonly used PSO algorithm. SPEAR3 performance was successfully improved during the online optimization runs with MG-GPO.
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Title: EXAMINING PERFORMANCE DEGRADATION OF LI-ION BATTERIES WITH SILICON-BASED ANODE AND POSSIBLE SOLUTIONS TO IMPROVE THE SILICON ANODE BEHAVIOR
Creator: Luo, Mei
Date: 2022
Description: Si has been investigated as a promising alternative to conventional graphite because of its high specific capacity and wide operating voltage;...
Show moreSi has been investigated as a promising alternative to conventional graphite because of its high specific capacity and wide operating voltage; however, technical challenges related to volume change in the silicon anode have hampered their practical application. In this work, the effects of silicon volume change on electrochemical performance has been studied in NMC532/Si full cells. First, different area specific capacity ratios of the negative to positive electrode (N:P ratio) were investigated using three-electrode cells. With individual electrode potentials monitored by a reference electrode, different depths of lithiation/delithiation at the anode and cathode were found to play an important role on cell performance; the cell with higher N:P ratio displays superior electrochemical performance due to its smaller silicon volume change. Further, calendar-life aging and cycle-life aging of NMC532/Si cells were compared with their electrode potentials monitored using a reference electrode. The observation of larger capacity decay and impedance growth of cycle-life aging cells illustrates the important effect of silicon volume change; significant capacity decay of calendar-life aged cell was observed as well, revealing an essential role of chemical effect of ongoing side reactions at Si anode. Specially-designed silicon with different protocols and electrolyte additives were investigated to address the intrinsic challenges of Si anodes for lithium-ion batteries.
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Title: Growth kinetics of Salmonella enterica and Listeria monocytogenes during rehydration of dehydrated corn and subsequent storage
Creator: Mate, Madhuri
Date: 2022
Description: Dehydrated vegetables, including corn, are often used in restaurants and retail grocers. They do not support the growth of pathogens as their...
Show moreDehydrated vegetables, including corn, are often used in restaurants and retail grocers. They do not support the growth of pathogens as their moisture content is very low. After rehydration, these food products attain high water activity values suitable with neutral pH for the survival and proliferation of foodborne pathogens, including Salmonella enterica and Listeria monocytogenes. The purpose of the study was to examine the extent to which dehydrated corn supports the growth of S. enterica and L. monocytogenes during rehydration at 5 or 25°C water and following storage at 5, 10, and 25°C temperatures at 1, 3, 5 and 7 d intervals. Fresh corn was dehydrated at 60°C for 24 h. Dehydrated corn was inoculated with a 4-strain cocktail of either S. enterica or rifampicin-resistant L. monocytogenes, resulting in 4 log CFU/g, and held at ambient temperature for 24 h. This corn was then rehydrated using either 5 or 25°C water for 24 h. Throughout rehydration, corn samples were removed at intervals and enumerated. To enumerate S. enterica and L. monocytogenes, the samples were homogenized with BPB and BLEB respectively and cultivated on TSAYE with overlaid XLD or BHIARif200, respectively. Rehydrated corn was then stored at 5, 10, or 25°C and enumerated at intervals 1,3,5 and 7 d. Triplicate samples were assessed at each timepoint and three independent experiments were conducted for each rehydration water temperature. Growth rates were determined by DMFit and statistically analyzed using Student t-test. A p-value ≤0.05 was considered significant. Overall the growth rate of S. enterica was higher when rehydrated in 5°C water temperature and then stored at 25°C and was determined to be 0.61 ± 0.23 log CFU/g per d. This timepoint was also the shortest time required to increase by 1 log which was: 1.64 d, i.e. 39 h. For L. monocytogenes, the 25°C water rehydration showed the fastest growth rate when stored at 25°C. It took only 1.58 d or 37.8 h for 1 log increase in the population. After 5°C water rehydration of corn the highest populations of mesophilic bacteria and yeasts and molds were observed for 25°C storage ranging from 8.43 to 9.39 log CFU/g and 4.75 to 7.87 log CFU/g, respectively. After 25°C water rehydration, the highest population of mesophilic bacteria, 8.88 log CFU/g, was observed at 5°C storage at 5 d; yeasts and molds were 8.70 log CFU/g for 25°C storage on the same day. The results of this study determined that S. enterica and L.monocytogenes could survive and grow in dehydrated plant foods during rehydration and storage, highlighting the need for product assessments for these types of foods.
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Title: New Insights to Thermoelectrics from Fundamental Transport Properties to Potential Materials and Device Design
Creator: Pan, Zhenyu
Date: 2022
Description: Thermoelectric (TE) materials have been widely studied as their ability to make direct energy conversion between heat and electricity. However...
Show moreThermoelectric (TE) materials have been widely studied as their ability to make direct energy conversion between heat and electricity. However, the conversion efficiency is still low compared with conventional devices no matter in power generation or electrical cooling. Therefore, most efforts have been made to improve the zT of TE materials, which is the commonly accepted metric for determining the performance of TE materials. But the progress is slow as the key parameters governing the zT is interrelated to each other which makes improving one often at the cost of the others leading to a narrow use of TE applications. Thus this thesis does not confine itself only in searching for high zT TE materials but also exploring useful things which are buried or ignored in previous thermoelectric researches from fundamental transport properties to TE device design. Firstly, we reevaluated the photo-Seebeck effect, which has been known for decades, and demonstrated that it is a powerful tool for semiconductor study as it allows the determination of mobilities, photo-carrier densities, even weighed mobilities (hence effective masses) of both electrons and holes and impact of defects all from a single sample. We then investigated a newly discovered low dimensional material, 2D tellurene, which has the potential to decouple the interrelated parameters to achieve a high zT. Lastly, we reconsidered the question that whether zT is the only merit index determining TE device performance. We hope this thesis can shed some light on thermoelectrics both from fundamental transport properties to device design.
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Title: SYSTEMATIC ANALYSIS OF THE MCENTER BEAMLINE AT THE FERMILAB TEST BEAM FACILITY FOR THE NOVA TEST BEAM EXPERIMENT
Creator: Temizel, Buse Naz
Date: 2021
Description: This thesis presents a systematic analysis of the MCenter beamline at the Fermilab Test Beam Facility to help to generate improved beam...
Show moreThis thesis presents a systematic analysis of the MCenter beamline at the Fermilab Test Beam Facility to help to generate improved beam profiles for the NOvA Test Beam Experiment. Several studies were carried out to understand beam transport to the experiment, including optics calculations and computer simulations using a novel procedure for incorporating the acceptance of the channel. Data from beam profile monitors was used to trace the beam phase space and compared to simulation results. Detailed analysis revealed that the beam sizes on the NOvA target were large compared to its transverse size. New tunes were proposed for a detailed beam optics study. Analysis of the new tunes shows that the new optics produce two components corresponding to two different peaks at different energies in the horizontal profile at the NOvA target.
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Title: DEEP LEARNING IMAGE-DENOISING FOR IMPROVING DIAGNOSTIC ACCURACY IN CARDIAC SPECT
Creator: Liu, Junchi
Date: 2022
Description: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a noninvasive imaging modality widely utilized...
Show moreMyocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a noninvasive imaging modality widely utilized for diagnosis of coronary artery diseases (CAD) in nuclear medicine. Because of the concern of potential radiation risks, the imaging dose administered to patients is limited in SPECT-MPI. Due to the low count statistics in acquired data, SPECT images can suffer from high levels of noise. In this study, we investigate the potential benefit of applying deep learning (DL) techniques for denoising in SPECT-MPI studies. Owing to the lack of ground truth in clinical studies, we adopt a noise-to-noise (N2N) training approach for denoising in full-dose studies. Afterwards, we investigate the benefit of applying N2N DL on reduced-dose studies to improve the detection accuracy of perfusion defects. To address the great variability in noise level among different subjects, we propose a scheme to account for the inter-subject variabilities in training a DL denoising network to improve its generalizability. In addition, we propose a dose-blind training approach for denoising at multiple reduced-dose levels. Moreover, we investigate several training schemes to address the issue that defect and non-defect image regions are highly unbalanced in a data set, where the overwhelming majority by non-defect regions tends to have a more pronounced contribution to the conventional loss function. We investigate whether these training schemes can effectively improve preservation of perfusion defects and yield better defect detection accuracy. In the experiments we demonstrated the proposed approaches with a set of 895 clinical acquisitions. The results show promising performance in denoising and improving the detectability of perfusion-defects with the proposed approaches.
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Title: Data-Driven Methods for Soft Robot Control and Turbulent Flow Models
Creator: Lopez, Esteban Fernando
Date: 2022
Description: The world today has seen an exponential increase in its usage of computers for communication and measurement. Thanks to recent technologies,...
Show moreThe world today has seen an exponential increase in its usage of computers for communication and measurement. Thanks to recent technologies, we are now able to collect more data than ever before. This has dawned a new age of data-driven methods which can describe systems and behaviors with increasing accuracy. Whereas before we relied on the expertise of a few professionals with domain-specific knowledge developed over years of rigorous study, we are now able to rely on collected data to reveal patterns, develop novel ideas, and offer solutions to the world’s engineering problems. No domain is safe. Within the engineering realm, data-driven methods have seen vast usage in the areas of control and system identification. In this thesis we explore two areas of data-driven methods, namely reinforcement learning and data-driven causality. Reinforcement learning is a method by which an agent learns to increase its selection of ideal actions and behaviors which result in an increasing reward. This method was applied to a soft-robotic concept called the JAMoEBA to solve various tasks of interest in the robotics community, specifically tunnel navigation, obstacle field navigation, and object manipulation. A validation study was conducted to show the complications that arise when applying reinforcement learning to such a complex system. Nevertheless, it was shown that reinforcement learning is capable of solving three key tasks (static tunnel navigation, obstacle field navigation, and object manipulation) using specific simulation and learning hyperparameters. Data-driven causality encompasses a range of metrics and methods which attempt to uncover causal relationships between variables in a system. Several information theoretic causal metrics were developed and applied to nine mode turbulent flow data set which represents the Moehlis model. It was shown that careful consideration into the method used was required to identify significant causal relationships. Causal relationships were shown to converge over several hundred realizations of the turbulent model. Furthermore, these results match the expected causal relationships given known information of self-sustaining processes in turbulence, validating the method’s ability to identify causal relationships in turbulence.
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Title: Heterogeneous Workloads Study towards Large-scale Interconnect Network Simulation
Creator: Wang, Xin
Date: 2023
Description: High-bandwidth, low-latency interconnect networks play a key role in the design of modern high- performance computing (HPC) systems. The ever...
Show moreHigh-bandwidth, low-latency interconnect networks play a key role in the design of modern high- performance computing (HPC) systems. The ever-increasing need for higher bandwidth and higher message rate has driven the design of low-diameter interconnect topologies like variants of dragonfly. As these hierarchical networks become increasingly dominant, interference caused by resource sharing can lead to significant network congestion and performance variability. Meanwhile, with the rapid growth of the machine learning applications, the workloads of future HPC systems are anticipated to be a mix of scientific simulation, big data analytics, and machine learning applications. However, little work has been conducted to understand performance implications of co-running heterogeneous workloads on large-scale dragonfly systems. There is a greater need to study how different interconnect technologies affect workload performance, and how conventional scientific applications interact with emerging big data applications at the underlying interconnect level. In this work, we firstly present a comparative analysis exploring the communication interference for traditional HPC applications by analyzing the trade-off between localizing communication and balancing network traffic. We conduct trace-based simulations for applications with different communication patterns, using multiple job placement policies and routing mechanisms. Then we develop a scalable workload manager that provides an automatic framework to facilitate hybrid workload simulation. We investigate various hybrid workloads and navigate various application-system configurations for a deeper understanding of performance implications of a diverse mix of workloads on current and future supercomputers. Finally, we propose a scalable framework, Union+, that enables simulation of communication and I/O simultaneously. By combining different levels of abstraction, Union+ is able to efficiently co-model the communication and I/O traffic on HPC systems that equipped with flash-based storage. We conduct experiments with different system configurations, showing how Union+ can help system designers to assess the usefulness of future technologies in next-generation HPC machines.
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Title: Retrospective Quantitative T1 Imaging to Examine Characteristics of Multiple Sclerosis Lesions
Creator: Young, Griffin James
Date: 2024
Description: Quantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1...
Show moreQuantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1 relaxometry is gaining popularity as elevated T1 values have been shown to correlate with increased inflammation, demyelination, and gliosis. The predominant issue is that relaxometry requires parametric mapping through advanced imaging techniques not commonly included in standard clinical protocols. This leaves an information gap in large clinical datasets from which quantitative mapping could have been performed. We introduce T1-REQUIRE, a retrospective T1 mapping method that approximates T1 values from a single T1-weighted MR image. This method has already been shown to be accurate within 10% of a clinically available reference standard in healthy controls but will be further validated in MS cohorts. We also further aim to determine T1-REQUIRE’s statistical significance as a unique biomarker for the assessment of MS lesions as they relate to clinical disability and disease burden. A 14-subject comparison between T1-REQUIRE maps derived from 3D T1 weighted turbo field echoes (3D T1w TFE) and an inversion-recovery fast field echo (IRFFE) revealed a whole-brain voxel-wise Pearson’s correlation of r = 0.89 (p < 0.001) and mean bias of 3.99%. In MS white matter lesions, r = 0.81, R2 = 0.65 (p < 0.001, N = 159), bias = 10.07%, and in normal appearing white matter (NAWM), r = 0.82, R 2 = 0.67 (p < 0.001), bias = 9.48%. Mean lesional T1-REQUIRE and MTR correlated significantly (r = -0.68, p < 0.001, N = 587) similar to previously published literature. Median lesional MTR correlated significantly with EDSS (rho = -0.34, p = 0.037), and lesional T1-REQUIRE exhibited xiii significant correlations with global brain tissue atrophy as measured by brain parenchymal fraction (BPF) (r = -0.41, p = 0.010, N = 38). Multivariate linear regressions between T1- REQUIRE NAWM provided meaningful statistical relationships with EDSS (β = 0.03, p = 0.027, N = 38), as well as did mean MTR values in the Thalamus (β = -0.27, p = 0.037, N = 38). A new spoiled gradient echo variation of T1-REQUIRE was assessed as a proof of concept in a small 5-subject MS cohort compared with IR-FFE T1 maps, with a whole brain voxel-wise correlation of r = 0.88, R2 = 0.77 (p < 0.001), and Bias = 0.19%. Lesional T1 comparisons reached a correlation of r = 0.75, R2 = 0.56 (p < 0.001, N = 42), and Bias = 10.81%. The significance of these findings means that there is the potential to provide supplementary quantitative information in clinical datasets where quantitative protocols were not implemented. Large MS data repositories previously only containing structural T1 weighted images now may be used in big data relaxometric studies with the potential to lead to new findings in newly uncovered datasets. Furthermore, T1-REQUIRE has the potential for immediate use in clinics where standard T1 mapping sequences aren’t able to be readily implemented.
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Title: Prediction and Control of In-Cylinder Processes in Heavy-Duty Engines Using Alternative Fuels
Creator: Pulpeiro Gonzalez, Jorge
Date: 2024
Description: This Ph.D. thesis focuses on advancing diagnostic techniques and control-oriented models to enhance the efficiency and performance of internal...
Show moreThis Ph.D. thesis focuses on advancing diagnostic techniques and control-oriented models to enhance the efficiency and performance of internal combustion (IC) engines, particularly heavy-duty engines utilizing alternative fuels. The research endeavors to contribute to the field of model-based control of engines through the development and implementation of innovative methodologies. The primary emphasis is on the development of diagnostic methods, control-oriented models and advanced control strategies for compression ignition engines using alternative fuels. The first key topic explores the determination of the Most Representative Cycle for Combustion Phasing Estimation based on cylinder pressure measurements. The method developed extracts crucial information from experimental data obtained from four distinct engines: the heavy-duty single-cylinder GCI engine, the light-duty multi-cylinder diesel engine, a CFR engine, and a single-cylinder light-duty Spark Ignition (SI) engine. This work lays the foundation for precise combustion phasing estimation, a critical parameter for engine control. The second major contribution involves the development of control-oriented models for Variable Geometry Turbochargers (VGT) and inter-coolers. Two models are established: a data-driven turbocharger model and an empirical inter-cooler model. These models are meticulously calibrated and validated using experimental data from a multi-cylinder light-duty diesel engine, providing valuable insights into the behavior of these components under varying conditions. The outcomes contribute to facilitate predictive control of engine air systems. The third core aspect of the thesis revolves around Model Predictive Control of Combustion Phasing in heavy-duty compression-ignition engines utilizing alternative fuels. A combustion phasing and engine load model is derived from experimental data and incorporated into an MPC framework. The MPC strategy is subsequently tested in the heavy-duty GCI test cell and compared against a conventional Proportional-Integral-Derivative (PID) control strategy. The results showcase the effectiveness of the MPC approach in achieving precise control of combustion phasing, demonstrating its potential for optimizing engine performance. In summary, this Ph.D. thesis contributes significantly to the field of engine controls by advancing diagnostic techniques, control-oriented models, and implementing a cutting-edge MPC-based control strategy for compression ignition engines using alternative fuels. The research findings not only enhance the understanding of in-cylinder processes but also pave the way for more efficient and sustainable heavy-duty engines using alternative fuels.
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Title: Prediction and Control of In-Cylinder Processes in Heavy-Duty Engines Using Alternative Fuels
Creator: Pulpeiro Gonzalez, Jorge
Date: 2024
Description: This Ph.D. thesis focuses on advancing diagnostic techniques and control-oriented models to enhance the efficiency and performance of internal...
Show moreThis Ph.D. thesis focuses on advancing diagnostic techniques and control-oriented models to enhance the efficiency and performance of internal combustion (IC) engines, particularly heavy-duty engines utilizing alternative fuels. The research endeavors to contribute to the field of model-based control of engines through the development and implementation of innovative methodologies. The primary emphasis is on the development of diagnostic methods, control-oriented models and advanced control strategies for compression ignition engines using alternative fuels. The first key topic explores the determination of the Most Representative Cycle for Combustion Phasing Estimation based on cylinder pressure measurements. The method developed extracts crucial information from experimental data obtained from four distinct engines: the heavy-duty single-cylinder GCI engine, the light-duty multi-cylinder diesel engine, a CFR engine, and a single-cylinder light-duty Spark Ignition (SI) engine. This work lays the foundation for precise combustion phasing estimation, a critical parameter for engine control. The second major contribution involves the development of control-oriented models for Variable Geometry Turbochargers (VGT) and inter-coolers. Two models are established: a data-driven turbocharger model and an empirical inter-cooler model. These models are meticulously calibrated and validated using experimental data from a multi-cylinder light-duty diesel engine, providing valuable insights into the behavior of these components under varying conditions. The outcomes contribute to facilitate predictive control of engine air systems. The third core aspect of the thesis revolves around Model Predictive Control of Combustion Phasing in heavy-duty compression-ignition engines utilizing alternative fuels. A combustion phasing and engine load model is derived from experimental data and incorporated into an MPC framework. The MPC strategy is subsequently tested in the heavy-duty GCI test cell and compared against a conventional Proportional-Integral-Derivative (PID) control strategy. The results showcase the effectiveness of the MPC approach in achieving precise control of combustion phasing, demonstrating its potential for optimizing engine performance. In summary, this Ph.D. thesis contributes significantly to the field of engine controls by advancing diagnostic techniques, control-oriented models, and implementing a cutting-edge MPC-based control strategy for compression ignition engines using alternative fuels. The research findings not only enhance the understanding of in-cylinder processes but also pave the way for more efficient and sustainable heavy-duty engines using alternative fuels.
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Title: Co-design Framework for Design and Optimization of Switched Reluctance Motors
Creator: Zhang, Ziyan
Date: 2024
Description: This thesis developed a co-design optimization framework for Switched Reluctance Motors (SRM) where geometric and control parameters are...
Show moreThis thesis developed a co-design optimization framework for Switched Reluctance Motors (SRM) where geometric and control parameters are jointly optimized to improve the overall performance of the motor. This algorithm aims to increase the average torque, decrease the ripple of the torque profile, and enhance operating efficiency as well as acoustic noise. This co-design methodology allows the motor electromagnetic design to be combined with the control strategy and presents a solution for multi-physics optimization. A magnetic equivalent circuit (MEC) based approach is proposed to analyze the electromagnetic characteristics which greatly improves the accuracy over conventional MEC for arbitrary geometries. The natural frequencies of the stator system are identified using a system approach, which is suitable for motors with complex frames. The vibration response and acoustic noise prediction are analyzed and evaluated by the analytical approach. To demonstrate the effectiveness of this approach, case studies were performed that compare optimized SRM designs obtained from their framework to those designed traditionally. Experimental validation is performed to evaluate the accuracy of the proposed approach.
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Title: WIDESPAN: Masters Project
Creator: Ninan, Janice
Date: 2011-05, 2010-12
Description: Widespan design.Investigating the integration of windmills into longspan structure and investigating the axial forces of tension to span...
Show moreWidespan design.Investigating the integration of windmills into longspan structure and investigating the axial forces of tension to span grater spans using virtual depth concepts with slender lightweight design.
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Title: Avoidatrak (Summer 2003) IPRO 351: Avoidatrack IPRO351 Summer2003 Final Presentation
Date: 2003, 2003-07
Description: A Fall 2002 EnPRO Team created a demonstration version of a computer game that puts you in control of a wheelchair. They also explored some of...
Show moreA Fall 2002 EnPRO Team created a demonstration version of a computer game that puts you in control of a wheelchair. They also explored some of the business issues associated with this game concept. The aim of this game will be to help hone wheelchair-maneuvering skills for training and entertaining. With the simulation of such wheelchair activities as racing, basketball and other recreational activities, Avoidatrak will be a challenging and entertaining game for all.The National Easter Seal Society, the YMCA, special education teachers and others are interested in the results of this project. The idea is to eventually develop a combination computer game and training tool to meet the needs of children and others with disabilities that is based on a concept of collision avoidance conceived by Mr. Julius Jones, Jr., a Chicago independent inventor. This concept responds to the need for a simulation that helps children become familiar with how to use a wheelchair as well as offers an entertainment experience for those confined to wheelchairs or their friends.
Sponsorship: IIT Collaboratory for Interprofessional Studies and the Ed Kaplan Entrepreneurial Studies Program
Project Plan for IPRO 351: Avoidatrak for the Summer2003 semester
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Title: Adoption and Implementation of Diabetes Electronic Support Center at Mount Sinai Hospital, Summer 2011, IPRO 345
Creator: Kos, Carolyn, Valio, Nicole, Michael, Hazel, Chinzorig, Unubold, Johnson, Kendra
Date: 2011-06-17, 2011-07
Description: The purpose of IPRO 345 is to improve and mobilize the data and remote health care system for Mount Sinai Hospital. Specifically, this project...
Show moreThe purpose of IPRO 345 is to improve and mobilize the data and remote health care system for Mount Sinai Hospital. Specifically, this project aims to create a data support to aid diabetic patients within 500 meters of the hospital in order to decrease cost of operation and time and increase the quality of care. We will develop the groundwork for future IPRO 345 teams that will eventually implement the new data collection program.
Sponsorship: SolarWindUSA
Design+Prototype+Test an Integrated Roof-Top Photovoltaic Solar System Design, Summer 2011, IPRO 345
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Title: Adoption and Implementation of Diabetes Electronic Support Center at Mount Sinai Hospital, Summer 2011, IPRO 345: Poster
Creator: Kos, Carolyn, Valio, Nicole, Michael, Hazel, Chinzorig, Unubold, Johnson, Kendra
Date: 2011-06-17, 2011-07
Description: The purpose of IPRO 345 is to improve and mobilize the data and remote health care system for Mount Sinai Hospital. Specifically, this project...
Show moreThe purpose of IPRO 345 is to improve and mobilize the data and remote health care system for Mount Sinai Hospital. Specifically, this project aims to create a data support to aid diabetic patients within 500 meters of the hospital in order to decrease cost of operation and time and increase the quality of care. We will develop the groundwork for future IPRO 345 teams that will eventually implement the new data collection program.
Sponsorship: SolarWindUSA
Design+Prototype+Test an Integrated Roof-Top Photovoltaic Solar System Design, Summer 2011, IPRO 345
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Title: Developing a Conference of Human Consciousness (Fall 2001) IPRO 315
Creator: Baste, Suhad, Curtis, Chris, Powers, Gina, Weiss, Doug, Chang, Robert, Daschbach, Patti, Twenter, Barry
Date: 2001, 2001-12
Description: The team will organize and conduct a conference to address the question of what is the status of our knowledge about human consciousness. This...
Show moreThe team will organize and conduct a conference to address the question of what is the status of our knowledge about human consciousness. This will provide interested students an opportunity to develop and apply project management skills, and develop many contacts in various professional areas in academia, government agencies, professional societies and professional services firms, social services organizations, and a range of associated health fields. The question of human consciousness has philosophical, psychological, and neurobiological dimensions. The 90�s were the decade of the brain. The genome project has focused attention on the evolution of the brain especially with the emergence of the discipline of evolutionary psychology. A conference (following the format of the previous one-day conference we organized and conducted on November 7, 1998, The Ganges River Pollution Problem) will display the several dimensions of the question via presentations by experts representing the range of complementary issues and areas of study associated with the topic of human consciousness. Self-awareness is a source of wonder and curiosity for all humans. A conference with this focus will give all of us that comprise the IIT community an opportunity to explore with, and gain insight from, experts in each of the relevant fields of knowledge to advance our own levels of understanding about this fascinating phenomenon.
Sponsorship: IIT Collaboratory for Interprofessional Studies
Project Plan for IPRO 315: Developing a Conference of Human Consciousness for the Fall 2001 semester
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Title: Legal Aspects Website (Spring 2002) IPRO 380
Date: 2002, 2002-05
Description: Students will research, design, and build a web site to be hosted in the Ukraine at our partner university. The site is designed to teach...
Show moreStudents will research, design, and build a web site to be hosted in the Ukraine at our partner university. The site is designed to teach viewers about important legal issues relating to e-commerce both internationally and in Ukraine. Our objective is to create the leading legal portal addressing e-commerce in Ukraine. The site should also include tutorials on practical issues such as what steps to take to seek intellectual property protection for one's inventions.
Sponsorship: U.S. Government
Project plan for IPRO 380: Legal Aspects Website for the Spring 2002 semester
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