Engineering Commons^™

Heat-Pipe-Based Thermal Management System Design For A 250-Kw Gan-Based Integrated Modular Motor Drive, Seyed Iman Hosseini Sabzevari, Salar Koushan, Armin Ebrahimian, Towhid Islam Chowdhury, Nathan Weise, Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

Integrated modular motor drive (IMMD) is an effective approach for realizing high-efficiency, high-power-density, and fault-tolerant electric machines. However, designing an efficient thermal management system (TMS) for the motor drive becomes a challenge, particularly due to space constraints. This article presents the design of a TMS based on 3-mm heat pipes for a 250-kW IMMD intended for aviation applications. The power electronics module is simulated using PLECS software where an electrothermal analysis is conducted. A simplified thermal resistance model of the system is developed to estimate the die junction temperature of gallium nitride (GaN) semiconductors. The performance of the proposed TMS …

Robust Online Inertia Estimation In Power Systems Using Ambient Data In The Presence Of Inverter-Based Resources, Narges Ghiasi

All Dissertations

The increasing penetration of Inverter-Based Resources (IBRs) in power systems has significantly altered system dynamics, reducing the system's effective rotational inertia and challenging frequency stability. Accurate online inertia estimation is essential for maintaining system reliability under these evolving conditions. This paper introduces a robust methodology for online inertia estimation using ambient data collected during normal system operation. The proposed method employs a state-space model to represent system dynamics and introduces synthetic step changes to simulate disturbances. By analyzing the frequency response and applying advanced signal processing techniques, the methodology estimates system inertia without requiring real large-scale disturbances. The approach is …

Advancing Smart And Adaptive Living Spaces Through Design And Development Of Reconfigurable Multifunctional Robot Rooms, Nithesh Kumar

All Dissertations

This work explores and introduces prototype hardware for a new category of robots: ‘Robot Rooms’, in an effort to refine the concept of traditional smart spaces and human-robot interaction. Unlike traditional robots that tend to be compact and exist within a space, this new category of robots is designed to be expansive: they do not exist within a space but rather shape space around them. We present several design concepts for potential robotic elements of a Robot Room. We then develop and demonstrate, at full scale, a new and novel concept: a ‘slice’ of a Robot Room. This slice changes …

Replacement Optimization For Offshore Wind Turbine Farms, Morteza Soltani

All Dissertations

This dissertation is concerned with devising optimal replacement policies for offshore wind turbines with a focus on minimizing the costs associated with major component replacements and production losses due to downtime. Like their onshore counterparts, offshore wind turbines are subject to progressive degradation due to normal operations, as well as the influence of dynamic environmental conditions that influence their rate of degradation. Due to their proximity, wind farm turbines share common environmental conditions, as well as specialized maintenance resources. Their common exposure to the environment and need to share resources introduce both stochastic and economic dependence between the wind turbines. …

Resilient Control Framework For Ev Motor Drive System Subject To Cyber-Physical Security, Ali Arsalan

All Dissertations

The electric drive system (EDS) in electric vehicles (EVs) is one of the key safety-critical components. As IoT-enabled communication infrastructure for modern cyber-physical automotive systems continues to evolve, the importance of securing EDS against cyber threats along with physical faults, has become increasingly prominent. Among physical faults, power switches are particularly vulnerable and exhibit the highest susceptibility to open-circuit faults (OCFs). A compromised EDS, whether due to cyber threats or physical issues, can lead to excessive mechanical vibrations, increased thermal stress, fluctuations in electromagnetic torque, and elevated total harmonic distortion. These factors can substantially undermine traction control stability and jeopardize …

Designing Self-Healable Aromatic Copolymers And Olefinic Composites, Samruddhi Yashwant Gaikwad

All Dissertations

Self-healing polymers capable of recovering from mechanical damage are promising materials for advanced applications, especially those involving mechanical and/or physical fatigue. In these studies, we have developed techniques to achieve autonomous self-healing in commodity Styrene/n-butyl acrylate copolymers. The mechanism of self-healing in the designed polymers involves inter-and/or intrachain non-covalent interactions between π-cloud and polar linkages of acrylic nBA in random/preferentially alternating copolymers. A combination of spectroscopic tools, thermo-mechanical analysis, and molecular dynamics (MD) simulations has been used to elucidate the mechanism of self-healing. These studies further show the incorporation of dipolar C-F groups to understand the effect of having fluorinated …

Investigation Of Solid-State Reactive Sintering And Rapid Laser Reactive Sintering For Al-Doped Li7la3zr2o12 Solid-State Electrolyte, Aaron Santomauro

All Dissertations

As a society, we’ve exhausted an extreme amount of fossil fuels and put an overwhelming strain on Earth’s natural resources. From this, it is critical to think about the successful future of our planet and ourselves by developing energy devices such as all-solid-state lithium-ion batteries (ASSLIBs). These devices offer a greener and more efficient alternative to power our daily lives, such as electric vehicles (EVs), portable electronics, medical devices, grid-scale energy storage, and aerospace/aviation. ASSLIBs are an excellent alternative to liquid-state batteries, which pose dangerous safety concerns (e.g., flammability, electrolyte leakage, etc.). These ASSLIBs are known to have generally high …

Advancing Lithium-Ion Batteries Through Exploration Of Novel Physico-Chemical Phenomena, Peshal Karki

All Dissertations

Lithium-ion batteries (LIBs) power a wide range of modern devices, from smartphones to electric vehicles. This dissertation integrates materials characterization and electrochemical testing to develop novel Si-based electrode materials, investigate separator effects, and improve electrochemical impedance spectroscopy (EIS) modeling. First, I synthesized Si@CC composites using bio-based carbon sources and discovered a novel in situ disorder reduction in the amorphous carbon cloud during cycling, attributed to Si volume fluctuations and mesoporous carbon structure, which enhanced capacity retention. A binder-free electrode (Si@CC@BP) using bucky paper further improved gravimetric and areal capacities while reducing weight and manufacturing complexity.

Next, I investigated how separator …

Structural Design Using Conditional-Gan Fused With Property Text Information: A Case For Masonry Structures, Arash Teymori Gharah Tapeh

All Dissertations

Structural design, by nature, is a complex process that requires a considerable amount of time, expertise, and knowledge. In such a process, the structural designer must navigate various codal provisions to crystallize a proper and adequate design. As the role of automation continues to shape the domain of structural engineering over the past few decades, a new front leverages artificial intelligence (AI). Currently, AI acts as a "copilot," collaborating to advance workflow speed and accelerate the design process. Among all the different collaborations between humans and AI, GANs (Generative Adversarial Networks) are seen to complement human creativity by automating specific …

An Investigation Into The Impact Of Inverter Based Resources On Critical Clearing Time, Trupal Patel

All Dissertations

Renewable energy sources, mainly inverter-based resources (IBRs) such as solar and wind plants are being connected in large numbers to the bulk power grid in the United States and around the world. Additionally, generation using fossil fuels are being phased out, which results in the loss of rotor inertia, a key contributor to the transient stability of power systems. Therefore, the large-signal behavior of IBRs and its impact on transient stability must be studied.

This work studies this impact through the metric of critical clearing time (CCT). Impact of grid topology, generation mix and control modes of IBRs on CCT …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Bilevel Network Interdiction Models For Human Trafficking Disruption, Daniel Bruno Lopes Da Silva

All Dissertations

In this dissertation, we study a series of bilevel network interdiction problems motivated by applications in human trafficking disruption. First, we consider a bilevel network interdiction problem where the follower aims to maximize the amount of flow from the source node to the sink node and the leader aims to minimize the number of arcs from a critical set that have positive flow on them in the solution obtained by the follower. This problem models the situation where an anti-trafficking agent wants to minimize the number of people affected by the trafficking operations whereas the trafficker wants to maximize trafficking …

Modeling Disaster Resilience Through A Human-Centered Lens: Exposure, Vulnerability And Adaptation, Tong Liu

All Dissertations

The core of reframing and operationalizing disaster resilience with a human-centered lens is to incorporate concepts from socio-ecological resilience into engineering resilience to better understand the humans’ capability for disaster adaptation. Existing studies have drawn practical implications by identifying actionable thresholds for infrastructure systems under disasters, which can be easily applied by policymakers, emergency managers and municipal agencies. However, how individuals interact with, respond to, or adapt under these infrastructure thresholds remain understudied. This hinders the operationalization of disaster resilience at the human scale.

First, I examined exposure by analyzing how configuration and distribution of urban infrastructure systems, such as …

Synthesis And Characterization Of Magnetic Nanoparticles To Study Effective Magnetic Anisotropy For Biomedical And Catalytic Applications, Alexander Malaj

All Dissertations

This dissertation focuses on understanding how to tune the magnetic properties of nanoparticles through controlling the effective magnetic anisotropy (Keff), which is a key variable in determining a nanoparticle’s Néel relaxation time, which will dictate its magnetic behavior in various applications. In this work, magnetocrystalline anisotropy is tuned by synthesizing tri-metallic substituted ferrite (Fe3-x-yMnxCoyO4) nanoparticles with specific metallic compositions that were informed by computer simulations using density functional theory (DFT) to target magnetocrystalline anisotropy values. A drip synthesis was used to control the size and composition of the tri-metallic ferrites, which were revealed to be monodisperse and compositionally mixed by …

Constructing A State: Canals And The Transformation Of The Economy, Politics, And Finance In Nineteenth-Century New York, Youwei Xing

All Dissertations

This dissertation consists of three essays in economic history, unified by a focus on one of America's earliest transportation infrastructures, the canal system, in nineteenth-century New York. Each chapter explores a different aspect of the state's transformation: its economy, politics, and finance, each of which helped construct New York as the Empire State.

The first chapter studies the economic impact of canals on economic modernization from three aspects: sectoral transition, urbanization, and banking development. Contrary to much of the modern literature finds transportation infrastructure leads to decentralization, I find the opposite-evidence of centralization. Specially: (1) canal towns experienced a transition …

Fleet Algorithm Design For Pooled Rideshare: Integrating Human Factors, Simulation, And Optimization, Joseph Paul

All Dissertations

This dissertation explores the study the integration of human factors modeling and rideshare fleet control algorithms. Pooled rideshare is a unique transportation mode offering that allows riders increased flexibility and accessibility over public transportation, and decreased cost relative to personal vehicles or traditional rideshare. Additionally, relative to personal vehicles, pooled rideshare offers reduced costs and options for those with difficulty obtaining transportation. Prior research in the space typically focused on modeling human behavior, or optimizing system performance, but a lack of integration of the concepts leads to unrealistic or underutilized outcomes. To tackle this problem, novel rideshare assignment, and repositioning …

Robustness Investigation, Detection, And Defense Of Deep Learning Models Against False Data Injection, Amirhossein Nazeri

All Dissertations

This dissertation addresses the critical challenge of adversarial robustness in deep learning systems, focusing on two fundamental domains: time-series prediction and object detection. As these AI systems become increasingly deployed in safety-critical applications from power grid management to autonomous vehicles their vulnerability to adversarial attacks poses significant risks to infrastructure and human safety.

The first contribution introduces a novel stealthy black-box False Data Injection (FDI) attack specifically designed for quasi-periodic time-series data. Unlike existing attacks that produce easily detectable anomalies, our method generates adversarial perturbations that preserve the underlying periodicity and statistical properties of the data, effectively bypassing traditional anomaly …

Curved Confinement Directs Anchoring-Mediated Structural Transitions In Highly Chiral Liquid Crystal Shells, Sepideh Norouzi, Jeremy Money, Stiven Villada-Gil, José Martínez-Gonález, Monirosadat Sadati

Faculty Publications

Cholesteric liquid crystals (CLCs) confined in curved geometries exhibit a rich spectrum of defectmediated morphologies governed by the interplay between chirality, curvature, surface anchoring, and confinement. This study systematically investigates structural transitions in highly chiral CLC shells under asymmetric anchoring conditions, focusing on the effects of shell thickness and curvature on pitch axis reorientation and defect formation. Utilizing microfluidic techniques, we generate core–shell droplets with independently tunable anchoring at inner and outer aqueous interfaces. Transitioning from planar–planar to planar-homeotropic boundary conditions via surfactant-mediated modulation induces profound reorganizations in the director field, giving rise to focal conic domains (FCDs), stripe patterns, …

3d Printing Of Short Fiber Reinforced Polypropylene: Novel Lattice Architecture And Material Characterization, Mohammad Ghazi Alshneeqat

Theses

This study explores the enhanced compressive behavior of 3D-printed single and double gyroid solid-networks lattices. Where the double gyroids are constructed from two intertwined single gyroid structures. These structures were designed by nTop implicit modeling tool and then fabricated by material extrusion additive manufacturing method at optimized printing parameters, including optimized nozzle temperature and raster angle. The main objective of this study is to reveal the compressive behavior of the novel double gyroid lattice structure and then to tailor its response through variable gyroid heights. Standard polymer tests were performed, considering thermogravimetric analysis, to confirm the thermal stability of the …

Dealuminated Metakaolin In Supplementary Cementitious Material And Alkali-Activated Systems: A Review, Amany G. Micheal Prof., Mostafa Adel Elsebaei Eng., Maria Mavroulidou Prof., Maria Centeno Assoc. Prof., Rabee Shamass Senior Lec., Ottavia Rispolio Mrs.

Architectural Engineering

This paper presents a comprehensive review of dealuminated metakaolin (DK), a hazardous industrial by-product generated by the aluminium sulphate (alum) industry and evaluates its potential as a component in cementitious systems for the partial or full replacement of Portland cement (PC). Positioned within the context of waste valorisation in concrete, the review aims to establish a critical understanding of DK formation, properties, and reactivity, particularly its pozzolanic potential, to assess its suitability for use as a supplementary cementitious material (SCM), or as a precursor in alkali-activated cement (AAC) systems for concrete. A systematic methodology is used to extract and synthesise …

Assessing The Robustness Of Test Selection Methods For Deep Neural Networks, Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Wei Ma, Mike Papadakis, Lei Ma, Yves Le Traon

Research Collection School Of Computing and Information Systems

Regularly testing deep learning-powered systems on newly collected data is critical to ensure their reliability, robustness, and efficacy in real-world applications. This process is demanding due to the significant time and human effort required for labeling new data. While test selection methods alleviate manual labor by labeling and evaluating only a subset of data while meeting testing criteria, we observe that such methods with reported promising results are simply evaluated, e.g., testing on original test data. The question arises: are they always reliable? In this article, we explore when and to what extent test selection methods fail. First, we identify …

Lithium Slag As A Supplementary Cementitious Material For Sustainable Concrete: A Review, Sajad Razzazan, Nuha S. Mashaan, Themelina Paraskeva

Research outputs 2022 to 2026

The global cement industry remains a significant contributor to carbon dioxide (CO2) emissions, prompting substantial research efforts toward sustainable construction materials. Lithium slag (LS), a by-product of lithium extraction, has attracted attention as a supplementary cementitious material (SCM). This review synthesizes experimental findings on LS replacement levels, fresh-state behavior, mechanical performance (compressive, tensile, and flexural strengths), time-dependent deformation (shrinkage and creep), and durability (sulfate, acid, abrasion, and thermal) of LS-modified concretes. Statistical analysis identifies an optimal LS dosage of 20–30% (average 24%) for maximizing compressive strength and long-term durability, with 40% as a practical upper limit for tensile and flexural …

Mxenes At The Forefront: Advances In Energy Storage And Nanofluidic Applications, Zafar Said, Maham Aslam Sohail, Hassina Tabassum, Imran Haider Sajid, Hafiz Muhammad Ali, Furqan Jamil, Yogendra Kumar Mishra, A. K. Pandey

Research outputs 2022 to 2026

This review summarizes recent studies on MXenes and their composites regarding energy storage and nanofluidic devices. MXenes are a new family of two-dimensional transition metal carbides and nitrides that have gained much attention in recent times due to their excellent physicochemical properties, such as its exceptionally high electrical conductivity, even more than that of metals, thermal stability, hydrophilicity, high energy and power densities, tunable structures, and large surface area along with abundant electrocatalytically active sites. These features, along with larger interlayer gaps compared with graphene, point to the emergence of MXenes as energy storage alternatives. Synthesis, properties, and applications of …

Mining Waste In Asphalt Pavements: A Critical Review Of Waste Rock And Tailings Applications, Adeel Iqbal, Nuha S. Mashaan, Themelina Paraskeva

Research outputs 2022 to 2026

This paper presents a critical and comprehensive review of the application of mining waste, specifically waste rock and tailings, in asphalt pavements, with the aim of synthesizing performance outcomes and identifying key research gaps. A systematic literature search yielded a final dataset of 41 peer-reviewed articles for detailed analysis. Bibliometric analysis indicates a notable upward trend in annual publications, reflecting growing academic and practical interest in this field. Performance-based evaluations demonstrate that mining wastes, particularly iron and copper tailings, have the potential to enhance the high-temperature performance (i.e., rutting resistance) of asphalt binders and mixtures when utilized as fillers or …

Advancement Of Biocarbon Materials In Sustainable Thermal And Electrochemical Energy Storage With Future Outlooks, Md Shahriar Mohtasim, Barun K. Das

Research outputs 2022 to 2026

Biocarbon exhibits significant potential in thermal and electrochemical energy storage owing to its higher surface area, flexible porosity, and superior thermal stability, facilitating effective energy absorption, storage, and conversion. Additionally, its sustainable and cost-effective nature, derived from renewable biomass, aligns with the growing demand for eco-friendly solutions. There is not enough review work that offers comprehensive details on the unique properties of biocarbon (both animal and plant-derived), synthesis and characterization methods, the root level mechanism of biocarbon's interaction with phase change materials (PCMs) matrix, the generalization of thermal and electrochemical regulation with an emphasis on the benefits to the environment …

Linearized Rigid-Body Dynamics Of Asymmetric Aircraft, Troy A. Abraham

All Graduate Theses and Dissertations, Fall 2023 to Present

Most aircraft are symmetric about their mid-plane, which permits simplifying assumptions when modeling their aerodynamic and mass properties, as well as estimating their dynamic modes. This work considers methods for modeling asymmetric aircraft, including capturing the dynamic mode characteristics that result from their asymmetric properties. While the primary focus of this work is on the dynamic mode properties of these aircraft, a significant portion of the dissertation is dedicated to modeling their aerodynamic, mass, and trimmed flight characteristics. The linearized rigid-body aircraft equations of motion used for dynamic mode estimates are developed to include the effects of asymmetries in both …

Exploring Methods For Quantifying Uncertainty In Neural Network-Based Turbulence Closures, Cody Grogan

All Graduate Theses and Dissertations, Fall 2023 to Present

Machine Learning (ML) is a very promising field for data-driven modeling of different phenomena. In the field of Computational Fluid Dynamics (CFD), ML is an enticing alternative to traditional methods to improve the accuracy and computational efficiency of simulations. However, many ML models, like Neural Networks, don’t quantify their uncertainty or indicate their confidence in a prediction to those who wish to use them. This is especially important because the use of inaccurate ML predictions in a CFD simulation can greatly impact the validity of a simulation. However, with uncertainty quantification, an ML model can indicate to a modeler the …

Evaluating The Impact Of Maximum Aero-Thermal Heating On A High-Speed Fixed-Wing Atmospheric Aircraft Optimum Trajectory, Benjamin M. Ford

All Graduate Theses and Dissertations, Fall 2023 to Present

This study explores how extreme heating affects the flight paths of hypersonic aircraft—vehicles that travel at speeds many times faster than sound. Analyzing how to fly a high-speed aircraft without overheating it can prevent structural failure while operating at maximum possible performance. The results shown in this section indicate that it is possible to operate at very high speeds in an aircraft while keeping peak vehicle temperature below our limits while saving fuel.

Evaluating Cyanotoxins In Surface Water And Aerosols Near Utah Lake, Dylan R. Mcpeake

All Graduate Theses and Dissertations, Fall 2023 to Present

Utah Lake is a freshwater lake in Utah County near Provo, Utah. It is the third- largest lake in Utah and is important for recreation and local businesses. However, from June to October, the lake often has cyanobacteria harmful algal blooms (cHABs), which contain a toxin called cyanotoxin. These toxins can be dangerous to people who come into contact with the water. Government agencies regularly check for cHABs and warn people when the water is unsafe for activities like swimming. Collecting water samples to test for cHABs can be risky because it can possibly result in direct contact with the …

An Optimization Study Of Multi-Orifice Synthetic Jets, Rhett T. Parry

All Graduate Theses and Dissertations, Fall 2023 to Present

From the mixing of creamer into coffee, to the dynamics of a dust storm, or smoke rising from a chimney—everything is driven by turbulent fluid motion. Experimentalists bring the complex driving mechanism that is turbulence into a laboratory setting to fundamentally understand its behavior in response to certain test parameters. Researchers may choose various drivers, or “actuators”, of fluid motion to start the turbulent regime for their applications. However, in building an entire experimental apparatus, they miss the step of ensuring that an individual driver is performing as best as possible. A common actuator used in experimental studies is a …