Engineering Commons^™

Towards Understanding Protein Immobilization Rules Through Site-Specific Covalent Immobilization Of T4 Lysozyme, Maxwell Hilbert

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Soluble enzymes have the unique ability to assist the conversion of complex substrates in fewer steps compared to conventional chemical synthesis; however, when immobilized to a surface, the insoluble enzyme's activity and stability can suffer in its new environment. To improve upon future immobilized enzyme efficacy, a fundamental understanding of the interactions across the enzyme, linker, and surface during covalent, site-specific immobilization that can be detrimental to its activity is required. More specifically, using a well-characterized and model enzyme, T4 lysozyme (T4L), 28 different cysteine attachment points' effects on site-specifically immobilized activity are examined. Different combinations of heterobifunctional amine-to-sulfhydryl crosslinkers …

A Youthful Metaverse: Towards Designing Safe, Equitable, And Emotionally Fulfilling Social Virtual Reality Spaces For Younger Users, Divine Maloney

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Social virtual reality (VR) represents the modern rendition of the metaverse, this dissertation aims to fill the research gaps while highlighting trends of youth in VR. The scientific contributions of this research include 1) expanding the current HCI understanding of the social dynamics and the interactions of teens in emerging novel online digital spaces; 2) bridging two research areas that have not been widely studied in HCI, social VR and young users in social VR; and 3) generating design implications to inform the design of future social VR platforms to better support and protect teens’ online social experiences, results which …

Understanding Process-Structure-Property-Performance Relationships Of Thermoplastic Olefins (Tpo) Foams Through A Novel Manufacturing To Response Pathway, Sai Aditya Pradeep

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The global transportation industry is the second highest contributor to climate change. As a result, there has been a concerted effort to spearhead research in economical lightweighting technologies, as every 10 % reduction in weight will lead to to 6 – 8 % improvement in fuel efficiency. Additionally, the recent push for electrification and the emphasis on Corporate Average Fuel Economy (CAFE) standards have seen original equipment manufacturers (OEM’s) dive into lightweighting of materials to improve overall range and/or fuel-efficiency. Thermoplastic Olefins (TPOs) have in recent years carved out a niche in the automotive industry due to advantages such as …

Seismic Performance Assessment Of Building Contents: Monetary Losses And Injuries, Sereen Majdalaweyh

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Building contents include all the components that are not attached to the building which the owners place after the construction phase, such as furniture, electrical equipment, glassware, and other personal items. Loss and damage assessment of building contents proved to be challenging in performance-based earthquake engineering frameworks because of the data sparsity. Damages to building contents during an earthquake not only cause monetary losses; tumbling and over-toppling of heavy building contents could result in injuries and even deaths of occupants. While major advancements have been made in performance-based earthquake engineering; however, the focus is mainly on damages and collapse risk …

Investigation And Characterization Of New Optically Stimulated Luminescence (Osl) Dosimetric Materials, Linyu Pan

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Optically stimulated luminescence (OSL) dosimeters have attracted increasing attention due to advantages over TL dosimeters, including no thermal quenching and higher sensitivity. Nevertheless, currently, there are only two commercially available OSL dosimeters, BeO and Al₂O₃:C. An OSL dosimeter requires low effective atomic number (Z_eff < 16), at least one type of recombination center and one type of trap, and UV~blue emission. In this dissertation, motivated by the search of new OSL dosimetric materials, a systematic investigation of alumina (Z_eff = 11.3) and magnesium aluminate spinel (Z_eff = 11.2) based materials was performed in terms of the engineering of the recombination centers and electronic traps. Microstructural characterization was executed by means of X-ray diffraction (XRD) and Raman spectroscopy. Luminescence was characterized under X-ray excitation (radioluminescence; RL) at ambient and …

Deep Learning-Guided Prediction Of Material’S Microstructures And Applications To Advanced Manufacturing, Jianan Tang

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Material microstructure prediction based on processing conditions is very useful in advanced manufacturing. Trial-and-error experiments are very time-consuming to exhaust numerous combinations of processing parameters and characterize the resulting microstructures. To accelerate process development and optimization, researchers have explored microstructure prediction methods, including physical-based modeling and feature-based machine learning. Nevertheless, they both have limitations. Physical-based modeling consumes too much computational power. And in feature-based machine learning, low-dimensional microstructural features are manually extracted to represent high-dimensional microstructures, which leads to information loss.

In this dissertation, a deep learning-guided microstructure prediction framework is established. It uses a conditional generative adversarial network (CGAN) …

Development Of Solution Blow Spun Nanofibers As Electrical And Whole Cell Biosensing Interfaces, Craig Levar Miller

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Infectious pathogens place a huge burden on the US economy with more than $120 billion spent annually for direct and indirect costs for the treatment of infectious diseases. Rapid detection schemes continue to evolve in order to meet the demand of early diagnosis. In chronic wound infections, bacterial load is capable of impeding the healing process. Additionally, bacterial virulence production works coherently with bacterial load to produce toxins and molecules that prolongs the healing cycle. This work examines the use of nonwoven polymeric conductive and non-conductive nanofiber mats as synthetic biosensor scaffolds, drug delivery and biosensor interface constructs. A custom-made …

Mechanical Interfacial Locking And Multiscale Modeling Of Reinforced Thermoplastic Composites For Structural Applications, Anmol Kothari

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The ever-growing pressure of reducing the adverse impact of transportation systems on environment has pushed industries towards fuel-efficient and sustainable solutions. While several approaches have been used to improve fuel efficiency, the light-weighting of structural components has proven broadly effective. In this regard, reinforced thermoplastic composites (RTPC), owing to their high recyclability, higher impact strength and fast cycle times, have become competitive candidates at an industrial scale. However, to implement RTPC toward large scale structural applications several challenges pertaining to material design and manufacturing effects need to be addressed. To this end, a computational study is carried out to address …

Integrating Degradation Forecasting And Abatement Framework Into Advanced Distribution Management System, Huu Phuong Hoang

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Future distribution grids are expected to face an increasing penetration of heterogeneous distributed energy resources (DERs) and electric vehicles (EVs). This landscape change will pose challenges to the control and management of distribution grids because of the variability of renewable energy resources and EV charging. In addition, multiple DERs dispersed over networks can also challenge the grid operation and maintenance as various DERs at various locations are needed to be monitored and managed. However, customers will not be content with reductions in power quality, reliability, economy, safety, or security. To enhance the effectiveness of grid control and management, future grids …

Numerical And Experimental Study Of Machining Process Of High Strength Lightweight Materials, Chao Zhang

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No abstract provided.

Coupled Thermal Mechanical Analysis Methodology For Thermal Performance Evaluation And Failure Mode Identification Of Thermal Barrier Coatings For Heavy Duty Diesel Engines, Sean Moser

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Consumer demand and government regulation, as well as the Department of Energy’s SuperTruck program has motivated extraordinary effort to maximize the heavy-duty diesel engine’s thermal efficiency. Thermal barrier coatings (TBCs) provide an avenue for increasing the thermal efficiency of the mixing controlled combustion (MCC) process through the reduction of heat transfer losses. The myriad of previous studies presents conflicting conclusions, both in the merit of TBCs for cycle improvement, and also for coating durability and potential adverse effects from coating failure. While the most recent studies with thin thermal barrier coatings (~100-250 µm) have shown a majority of positive cycle …

Influencing The Inflammatory Response Through Multi-Scale Geometry, Antibiotic Release, And Fluid Management In A Textile-Based Biomaterial Wound Dressing, Elizabeth Gianino

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The total population of diagnosed and undiagnosed diabetes mellitus in the United states is expected to rise by 54% between the years of 2015 and 2030 contributing to $200 billion in health care expense. The exponential rise in common diabetic wounds, such as diabetic foot ulcers, puts a large population at risk for complications such as infection, amputation, and even death. Peripheral neuropathy leading to late diagnoses, patient non-compliance, and lack of holistic treatment options all contribute to complications with the incidence of new ulcer formation after treatment reaching 50%. This work explores the design, development, and in vitro evaluation …

Time-Lapse Observation Of Sarcomeric Addition In Hypertrophic Models Based On A Tissue Like Cardiomyocyte Culture, Ailin Wei

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Cardiac hypertrophy is the response of the heart to increased mechanical stress exerted on the heart. In a hypertrophic heart, the muscles elongate or/and thicken with cardiomyocytes growing sizes. It is assumed that cardiomyocytes elongate by adding sarcomeres in series; the cardiomyocytes thicken with the addition of sarcomeres in the parallel position.

In this study, a tissue-like culture model was achieved with step-like ICDs. Uniaxial static stretch has been applied to our unique culture model for studying mechanical-load-induced cardiac hypertrophy. Hypertrophic responses of these cardiomyocytes have been confirmed on transcriptional and translational levels in our tissue-like model. The two-photon excitation …

An Algorithm For Biobjective Mixed Integer Quadratic Programs, Pubudu Jayasekara Merenchige

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Multiobjective quadratic programs (MOQPs) are appealing since convex quadratic programs have elegant mathematical properties and model important applications. Adding mixed-integer variables extends their applicability while the resulting programs become global optimization problems. Thus, in this work, we develop a branch and bound (BB) algorithm for solving biobjective mixed-integer quadratic programs (BOMIQPs). An algorithm of this type does not exist in the literature.

The algorithm relies on five fundamental components of the BB scheme: calculating an initial set of efficient solutions with associated Pareto points, solving node problems, fathoming, branching, and set dominance. Considering the properties of the Pareto set of …

Deep Learning Based Speech Enhancement And Its Application To Speech Recognition, Ju Lin

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Speech enhancement is the task that aims to improve the quality and the intelligibility of a speech signal that is degraded by ambient noise and room reverberation. Speech enhancement algorithms are used extensively in many audio- and communication systems, including mobile handsets, speech recognition, speaker verification systems and hearing aids. Recently, deep learning has achieved great success in many applications, such as computer vision, nature language processing and speech recognition. Speech enhancement methods have been introduced that use deep-learning techniques, as these techniques are capable of learning complex hierarchical functions using large-scale training data. This dissertation investigates the deep learning …

Quantification Of Compound And Cascading Hydroclimatic Extreme Events, Sourav Mukherjee

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Compound and cascading hydroclimatic extreme events have garnered much attention in recent studies. The combined effects of interconnected extremes can cause widespread damage, with a higher potential impact than individual extremes. Both anthropogenic warming and natural climate variability affect these extremes, which is why detecting past extreme events, understanding the underlying mechanisms, and assessing their future impacts can aid in mitigation efforts to reduce their overall impact. However, thus far, identifying such events is oversimplified and the propagation of their impact as cascades from the physical to human systems remains partly explored.

The overreaching goal of this thesis is to …

Multistage Stochastic Programming: Algorithms, Modelling And Applications, Murwan Siddig

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This dissertation comprises four di˙erent topics related to multistage stochastic program-ming (MSP) algorithms, modeling, and applications.

First, we extend the adaptive partition-based approach for solving two-stage stochastic programs with a fixed recourse matrix and a fixed cost vector to the MSP setting, where the stochastic process is assumed to be stage-wise independent. The proposed algorithms integrate the adaptive partition-based strategy with a popular approach for solving multistage stochastic programs, the stochastic dual dynamic programming (SDDP) algorithm, according to two main strategies. These two strategies are distinct from each other in the manner by which they refine the partitions during the …