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Phase Field Modeling Of Fracture And Phase Separation Using Numerical Methods And Machine Learning, Revanth Mattey

Dissertations, Master's Theses and Master's Reports

Phase field modeling is a crucial tool in scientific and engineering disciplines due to its ability to simulate complex phenomena like phase transitions, interface dynamics, and pattern formation. It plays a vital role in understanding material behavior during processes such as solidification, phase separation, and fracture mechanics. Particularly in fracture mechanics, phase field modeling can be utilized to predict the crack path in complex materials. Understanding the failure behavior is vital for applications of any material. The specific contributions to the field of phase field fracture mechanics, are, Firstly, we propose a novel phase field fracture model to simulate the …

Comprehensive Review And Development Of A High-Pressure Hydraulic Impedance Tube For Vibroacoustic Attenuator Characterization, Matthew D. Beals

Dissertations, Master's Theses and Master's Reports

This research establishes a versatile test bench for characterizing hydraulic vibroacoustic attenuators. The primary evaluation metric is the transfer matrix, determined experimentally, with an emphasis on key properties such as transmission loss. To ensure accuracy and broad applicability, the methodology is based on industry-standard techniques for determining the transfer matrix. A comprehensive literature review consolidates existing approaches for hydraulic attenuator characterization. The test bench features a hydraulic impedance tube equipped with eight dynamic pressure transducer (DPT) taps strategically positioned before and after the sample interface. This setup accommodates arbitrary samples terminated with standard hydraulic fittings. Using ASTM E2611, the transfer …

Data To Physics: Bridging Modeling Frameworks For Metastructures, Hrishikesh Suhas Gosavi

Dissertations, Master's Theses and Master's Reports

The effective attenuation of wave propagation in specific frequency ranges, known as bandgaps, makes metastructures valuable in various engineering applications. Traditionally, bandgap estimation has relied on physics-based models, which present challenges for complex metastructures where accurate material properties and geometric complexities make precise modeling difficult. This work introduces data-driven techniques for bandgap estimation, leveraging the dynamic behavior, particularly the Frequency Response Functions (FRFs) of unit cells, to calculate dispersion relations and couple unit cells through dynamic substructuring. This approach addresses the limitations of traditional methods by directly utilizing experimental data to characterize both longitudinal and flexural bandgaps.

To evaluate data-driven …

Analytical And Machine Learning Modeling Of Direct Carbonation Of Natural Silicate Minerals, William Hanson

Dissertations, Master's Theses and Master's Reports

The climate-altering effects of atmospheric CO₂ make it necessary to develop innovative technologies that can remove it from the atmosphere. Mineral carbonation is a scalable technology to sequestrate and store CO2 in a stable carbonate mineral form. The efficiency of the mineral carbonation process depends on both feed mineralogy and process parameters. Comprehensive modeling and prediction of mineral carbonation efficiency for different CO₂ – reactive rocks has not been achieved in the past. In this thesis work, analytical and machine learning models are developed to predict the carbonation efficiency of dunite reactions. It is found that random forest …

Molecular Modeling Of Phenolic Resin For Carbon-Carbon Composites, Ivan Gallegos

Dissertations, Master's Theses and Master's Reports

One of the most difficult challenges associated with space exploration is terrestrial atmospheric reentry due to the high thermal loads generated. Carbon carbon (C/C) composites have been used as heat shielding materials due to their high strengthto- weight ratio and thermal properties and their applications include heat shielding for various high temperature environments. C/C composites are manufactured by polymer-infiltration pyrolysis (PIP) via cycles of curing and pyrolysis of a prepreg which can be costly and take up to several days. Thus, C/C composites ideal candidates for computationally-driven optimization techniques, such as a multiscale Integrated Computational Materials Engineering (ICME) approach, by …

Two-Dimensional Flood Modeling Of Huron Creek In Houghton, Michigan, Sara Khoshnevis

Dissertations, Master's Theses and Master's Reports

Hydraulic models and inundation maps serve as essential tools for implementing proactive measures against potential infrastructure damage from flood events, thereby reducing economic losses and enhancing public safety. This research combines hydraulic modeling and geospatial technology in a case study of the Huron Creek Watershed in Houghton, Michigan. Specifically, a preliminary two-dimensional unsteady flow model was developed in the Hydrologic Engineering Center River Analysis System (HEC- RAS) based on estimated conditions of the 2018 Father's Day Flood. By utilizing high-resolution topographic data, and hydraulic infrastructure information, this study aims to simulate flood behavior throughout the urbanized portion of the watershed. …

Assessment Of Surface Waviness In A Wire Arc Additive Manufacturing Process, Shammas Mahmood Shafi

Dissertations, Master's Theses and Master's Reports

Wire Arc Additive Manufacturing (WAAM) is increasingly recognized for its ability to produce metal components with high deposition rates and efficiency, particularly in the aerospace and automotive sectors. However, one significant challenge that WAAM faces is achieving surface quality that complies with industry standards, as well as creating geometries that closely resemble the initial design. A crucial factor contributing to this challenge is surface waviness, which is an inherent characteristic of the WAAM process. This waviness arises from the geometry of the weld beads and the overlap distance between them. It can adversely affect the fusion quality of successive layers, …

Interplay Of Discharge Rates, Slope, And Sediment Size In River Meandering Dynamics: Insights From Experimental Studies, Yifan Zhang

Dissertations, Master's Theses and Master's Reports

Sinuosity is an important concept in various fields including hydrology, geomorphology, and ecology. It not only presents the degree of curviness of a river channel but also reflects the ecological sustaining ability. By studying the sinuosity of a stream or river channel, important implications could also be found including the transportation and deposition of the sediments, the habitats of the riverbanks, and the types of species that are able to live on the watershed and river. To study the factors that could heavily affect the sinuosity of a river channel, a full set of laboratory experiments was designed to perform …

Electrification Of A Heavy-Duty Off-Road Material Handler: Energy Savings And Emission Reductions, Bryant Goodenough

Dissertations, Master's Theses and Master's Reports

Federal regulations are driving the adoption of electrification technologies to reduce carbon dioxide equivalent (CO₂e) emissions, a metric that quantifies the global warming potential of various greenhouse gases in terms of carbon dioxide (CO₂). Although no specific CO₂ regulations exist for heavy-duty off-road machines, future reductions are likely, given stricter emissions standards for on-road vehicles. The heavy-duty off-road sector offers significant fuel-saving potential, as its focus has traditionally been on reliability and performance rather than fuel efficiency. This dissertation examines fuel and CO₂e savings opportunities on a heavy-duty off-road material handler, the Pettibone …

Enhancing Privacy While Revealing Vulnerabilities: Strategies For Adaptation, Optimization, And Model Extraction, Madhureeta Das

Dissertations, Master's Theses and Master's Reports

In the evolving landscape of machine learning and artificial intelligence, this dissertation presents a series of innovative contributions spanning several critical areas: embracing semi-supervised domain adaptation for secure knowledge transfer, enhancing the model performance of tiny models, and executing model stealing attacks via diversified prompts. The overarching goal is to enhance the performance, scalability, and security of AI models across various applications.

The first research focus is on semi-supervised domain adaptation within federated learning frameworks. By leveraging semi-supervised learning techniques, this work addresses the challenge of adapting models trained on a source domain to perform effectively on a target domain …

Synthesis Of Long Oligodeoxynucleotides, Yipeng Yin

Dissertations, Master's Theses and Master's Reports

Synthetic long oligodeoxynucleotides (ODNs) have found wide applications in diverse fields such as chemical biology, synthetic biology, and genes and genomes synthesis. Those applications leading to a significant demand for their production. However, traditional methods for purifying synthetic ODNs present notable drawbacks, particularly their inability to purify long ODNs, rendering long ODN synthesis challenging. To address these issues, chemical synthesis techniques for long ODNs coupled with non-chromatographic purification methods have been developed. This technology makes the purification of long synthetic ODNs feasible and offers a viable pathway for producing genes and genomes with extensive repeats or stable secondary structures, which …

Implementing Associative Learning Using Neuromorphic Robot, Vinay Kumar Pillalamarri

Dissertations, Master's Theses and Master's Reports

Associative learning, a key cognitive process seen across the animal kingdom, enables organisms to form connections between stimuli and adapt their behaviors based on past experiences. A particularly powerful example is fear conditioning, where animals learn to associate a neutral stimulus with an aversive one, allowing them to predict and avoid potential threats. Inspired by this mechanism, this project implements associative learning on an unmanned ground vehicle (UGV) to develop adaptive behavior through neuromorphic principles. Utilizing Nengo for neural modeling, the UGV learns to associate visual (red color) and tactile (vibration) stimuli through Hebbian learning, a biologically inspired synaptic adaptation …

Computational Analysis Of Vascular Aneurysms, Seyedmostafa Rezaeitaleshmahalleh

Dissertations, Master's Theses and Master's Reports

Vascular aneurysms, such as intracranial aneurysms (IAs) and abdominal aortic aneurysms (AAAs), pose significant health risks, particularly upon rupture. Disturbed hemodynamics, characterized by swirling flow patterns, can lead to cellular and structural changes that disrupt normal physiological processes and contribute to destructive vascular remodeling. Integrating hemodynamic analysis into clinical assessments of aneurysms has become crucial, especially through patient-specific computational fluid dynamics (CFD) simulations based on medical imaging. However, the complexity of CFD tools presents challenges in model creation and post-simulation analysis, limiting their accessibility to clinicians.
This project aimed to advance aneurysm management by exploring the role of intraluminal thrombus …

Wet-Carbonation Of Rcas For Improved Carbonation Efficiency And Mechanical Properties Of Rca And Recycled Concrete, Zhao. Xiang

Dissertations, Master's Theses and Master's Reports

RCA typically exhibits weak interfacial transition zones (ITZ), high porosity, and micro-cracks due to residual mortar layers, resulting in suboptimal performance when reused in structural applications. To address these challenges, this study developed a wet carbonation process using glycine acid as an inducer. Glycine acid, containing carboxyl and amino functional groups, forms stable complexes with Ca²⁺ ions in RCA, increasing calcium ion solubility and thereby accelerating carbonation. RCA samples underwent carbonation in a glycine acid solution, followed by characterization using X-ray diffraction and scanning electron microscopy to evaluate mineralogical transformations and microstructural enhancements. The carbonation process promoted the formation of …

Integrated Study Of Heat Transfer And Local Gas Dynamics In A Pebble Bed Very High Temperature Nuclear Reactor Using Advance Measurement Techniques, Muhna N. Alshammari

Doctoral Dissertations

"The aim of this study, pebbles of diameter of 5 cm and a pebble-to-diameter ratio (aspect ratio) of 6 were used. In part I, the local gas velocities were studied at different radial and axial locations in the pebble bed using a sophisticated hot wire anemometry (HWA) technique, which was supported with a novel probe-protector case to protect the fragile probe, allowing the measurements to be taken between the pebbles for the first time. The local gas velocities were found to be significantly higher in the near wall region due to the higher void fractions in the near-wall region, compared …

Understanding Catalyst Design Principles In Transition Metal Mixed Anionic Chalcogenides For Electrocatalytic Energy Conversion, Ibrahim Abdullahi

Doctoral Dissertations

"This research focused on the synthetic design of transition metal mixed anionic chalcogenide catalysts containing various ligand types around the central metal atom (chalcogen anion and chalcogen-based organic ligand) generating diverse crystal structure types applied for water splitting and carbon dioxide reduction reactions (CO₂RR).

A series of catalysts were synthesized starting with isolated metal complexes (ME_n) with a central metal core (M = Co, Ni, Cu, and Cr) through molecular clusters, to bulk nanostructured solids of similar M-E coordination. Bis(dichalcogenoimidodiphosphinato) were employed as ligands in the metal complexes, and anionic chalcogen (E = S, Se, and …

Applications Of Computational Intelligence And Data Fusion Techniques For Biomedical Images, Anand Krishnadas Nambisan

Doctoral Dissertations

"The realm of melanoma diagnosis has been significantly advanced by deep learning (DL) techniques, yet the current approaches are not without limitations, including missed diagnoses and the challenge of interpreting these "black box" models. The research is comprised of three studies, each contributing uniquely towards advancing melanoma detection accuracy and interpretability. The first study focuses on improving the detection of specific dermoscopic structures through a deep learning-based segmentation approach, while the second study builds upon this by employing a fusion technique that combines traditional image features with advanced deep learning models. This method significantly improves melanoma detection, particularly in recall …

Development And Testing Of High Strength Scalable High Entropy Alloys, Hans Jakob Pommerenke

Doctoral Dissertations

"High entropy alloys have shown promise through their ability to be tailored to specific scenarios. From highly corrosive environments to precipitation strengthened alloys to radiation environments high entropy alloys allow tailor made alloys for every solution. New compositions are developed and tested but little work focuses on the processing effect choosing rather than using processing as a steppingstone to achieve properties without investigating the processing effects. This work focuses on single phase face-centered cubic alloys strengthened by processing and precipitation strengthening. In conjunction with the development of these alloys, the ability to scale production will be investigated and characterized to …

Lithospheric Drip And Mantle Thermal Upwelling Beneath Central Asia And The Southern Great Plains Of North America: Evidence From Receiver Function Imaging, Yangyang Liao

Doctoral Dissertations

"Investigating the depth of mantle transition zone (MTZ) discontinuities provides insights into mantle dynamics, including regional-scale downwelling of mantle lithosphere (i.e., lithospheric drip) and upwelling of thermal materials (i.e., mantle plume). In our study, we employ receiver functions to image the 410 km (d410) and 660 km (d660) mantle discontinuities and to ascertain thickness of the MTZ beneath Central Asia and the Great Plains in United States. The findings unveil a significantly thickened transition zone, exhibiting an average thickness of 284 km beneath East Sayan. When considered alongside geochemical observations, our results indicate that the descent of the lithosphere is …

Processing-Microstructure-Properties Relationships In Additively Manufactured Zrb2-Sic Ceramics, Marharyta Lakusta

Doctoral Dissertations

"The study explores the pressure less sintering (PS) and chemical compatibility of ZrB₂-30 vol.%SiC produced by additive manufacturing (AM) with CO₂. The oxidation kinetics and scale microstructures were compared for ZrB₂-SiC made by hot pressing (HP) and by AM coupled with PS. All specimens exhibited parabolic oxidation kinetics. The difference in oxidation behavior becomes evident at temperatures of 1100-1400°C (200-900h). Oxidation rates increased as grain size increased. Similar oxide scale morphologies were observed in both CO₂ and air, with an outer borosilicate layer and an inner porous ZrO₂ layer containing partially oxidized …

Annual Report: Fy 2024 Quality Of Kerosene And Motor Fuel In Tennessee, Tennessee. Department Of Agriculture

Annual Reports on Kerosene & Motor Fuel Quality

The annual report provides data on the effectiveness of the 1989 Kerosene and Motor Fuels Quality Inspection Act, consumer complaints, inspection data, and summary of enforcement.

Sustainable Cementitious Materials For Building And Sorption Applications, Sukanta Kumar Mondal

Doctoral Dissertations

"Ordinary Portland Cement (OPC) is the most widely used cement material, but it contributes over 8% of the global CO₂ emission and the process is energy intensive. Moreover, OPC faces durability challenges, particularly in aggressive environments. Hence, there is rapidly increasing interest in sustainable alternative cements with lower carbon footprint, lower energy consumption, and those that offer superior properties that are beneficial for specific applications. Two sustainable cementitious materials that are frequently researched as an alternative to OPC are calcium sulfoaluminate (CSA) cement and alkali-activated materials (AAMs). CSA cement lowers CO₂ emission by over 40% compared to OPC, …

Investigation Of Asphaltene Instability Under Gas Injection In Unconventional Reservoirs And Its Impact On Oil Recovery Performance, Mukhtar Elturki

Doctoral Dissertations

"Unconventional reservoirs, such as shale gas and tight oil formations, have become an important source of energy in recent years. However, these reservoirs often contain high levels of asphaltenes, which can lead to deposition and blockages in production wells and reduce the flow of hydrocarbons during gas enhanced oil recovery (GEOR) techniques. This study aims to experimentally evaluate the impact of miscible and immiscible carbon dioxide (CO₂) and nitrogen (N₂) on asphaltene deposition and its impact on oil recovery performance in unconventional shale reservoirs.

This research began with a comprehensive literature review and data analysis of GEOR methods in unconventional …

Monitoring And Control Of Coal Dust Exposure Using Low-Cost Pm Sensors And Computational Fluid Dynamics, Nana Kobina Amoako Amoah

Doctoral Dissertations

"Overexposure to respirable coal mine dust has been linked to causing serious health problems including coal workers pneumoconiosis (CWP) and chronic massive fibrosis. The prevalence of these health problems has been on the increase since the 2000s due to increased exposure levels with roof bolter operators having the highest exposure levels. The currently used PDM3700 is too expensive, heavy and bulky which limits their use only for regulatory monitoring failing to measure miners’ personal exposure levels. Also, since roof bolter operators are more prone to elevated coal dust levels, the canopy air curtain (CAC) was developed to protect then high …

Modeling And Analysis Methods For Esd And Emi Problems, Xin Yan

Doctoral Dissertations

"Electrostatic discharge (ESD) failures and Electromagnetic interference (EMI) problems are becoming more critical in electronic devices and large systems. In this work, four studies are presented to model and analyze ESD and EMI problems.

First, a simplified physical-based model for deep-snapback transient voltage suppressors (TVS) is developed. While based on physics, the number of parameters and components is minimized. Results show that the proposed model captures the most important behaviors of the TVS response using a limited number of parameters, allowing the model to be tuned relatively easily using data obtained only from package-level transient and quasi-static measurements. Second, a …

Control And Optimization Of Energy Storage System In Power Distribution System, Waqas Ur Rehman

Doctoral Dissertations

"The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate fast-charging infrastructure for long-distance trips. Extreme fast charging (XFC) technology can recharge EVs in less than 10 minutes for 200 miles range. Firstly, a novel robust optimization-based mixed integer linear programming model is proposed to size a battery energy storage system (BESS) and PV system in an XFCS. In this part, it is assumed that the sizing and location of the XFCS are known. Secondly, the aforesaid assumption is relaxed, …

Low-Shrinkage Fiber-Reinforced Concrete For Infrastructure Construction And Rehabilitation, Jingjie Wei

Doctoral Dissertations

"The aim of this study is to develop two classes of low-shrinkage high-performance concrete (HPC): fiber-reinforced super workable concrete (FR-SWC) for infrastructure construction and fiber-reinforced self-consolidating concrete (FR-SCC) for repair applications. HPC with excess content of shrinkage mitigation materials (SMMs), including shrinkage-reducing admixture (SRA), superabsorbent polymer (SAP), and expansive agent (EA) has a detrimental effect on mechanical performance. These classes of HPC were optimized to reduce shrinkage, enhance mechanical properties, and improve durability. The effect of fiber type (macro synthetic fiber, MSF; 5D steel fiber, 5D; 80% 3D + 20% short steel fibers; STST), SMMs, and plastic viscosity on bond …

Additive Manufacturing Of Steel And Aluminum Structures: Modeling And Experiments, Manoj Kumar Reddy Rangapuram

Doctoral Dissertations

"Additive manufacturing (AM) is defined as the process of joining materials to make objects from three-dimensional model data. Complex geometries can be easily manufactured compared to conventional subtractive methods with more freedom and flexibility in the design process. As the demand for AM process increased, it has become critical to understand the process and various parameters that constitute in affecting the quality of the manufactured part. Conducting experiments can be time intensive and costly to optimize a process. Modeling can be used as an aid to optimize, examine, and predict the process outcome.

The objective of this study is (i) …

Effects Of Processing Parameters And Thickness On Compression-Molded Pet/Gf Composites, Jacob Reinholz

Mechanical Engineering and Applied Mechanics

Polymer-matrix composites (PMCs) have become an integral material in many industries due to excellent strength-to-weight ratio and low cost. When semi-crystalline polymer thermoplastics, such as polyethylene terephthalate (PET), are heated past their melt temperature then cooled during compression molding, the long polymer chains in the amorphous regions unravel and align to form crystalline regions with improved strength and stiffness. This research aimed to understand the effect of compression molding processing parameters such as temperature, pressure, dwell, and cooling rate as well as the overall panel thickness on crystallinity and mechanical properties of unidirectional glass fiber-reinforced PET. It was found that …

The Impact Of N-Glycans On The Immune Response Of Plant-Produced Sars-Cov-2 Rbd-Fc Proteins, Theerakarn Srisangsung

Chulalongkorn University Theses and Dissertations (Chula ETD)

N-glycosylation is a crucial post-translational modification that significantly affects immune recognition. The plant-based platform, especially Nicotiana benthamiana, offers scalable and cost-effective production of therapeutic proteins with glycosylation patterns similar to mammalian cells. However, plant-specific N-glycans, such as α(1-3)-fucose and β(1-2)-xylose (XF), have the potential to trigger allergic reactions. This study investigates how various N-glycan structures on the RBD-Fc fusion protein influence the immune response in mice. The RBD-Fc fusion protein was used for vaccine formulation, produced in both wild-type (WT) and glycoengineered (∆XF) N. benthamiana plants. N-glycan analysis showed a predominance of mannose (Man) in RBD-Fc with an ER retention …