Engineering Commons^™

Advancing Multi-Physics Modeling For Microwave Heating: Application In Micro-Reactor Design And Optimization, Raghav Adhikari

All Theses

Microreactors are a type of small-scale chemical reactors for achieving reduced volume, improved product selectivity and higher reaction rate. It allows precise temperature control, which is crucial for sensitive chemical processes. Microreactors can be employed as key components of conducting small-scale reactions with improved reactor configuration and process efficiency. It is important to identify a localized and precise heating mechanism to trigger and control the corresponding chemical reactions.

In fact, microwave heating has gathered significant attention in recent years due to its ability to deliver efficient, rapid, and localized heating, which can accelerate reaction rates and enhances the reaction selectivity. …

Impact Of Non-Uniform Surface Temperature On The Apparent Radiative Properties Of Cavity Receivers, Ehsan Mofidipour, Matthew R. Jones, Brian D. Iverson

Faculty Publications

Radiative surface properties play a critical role in the design, analysis and optimization of solar–thermal systems. Cavity receivers increase the efficiency of solar–thermal energy systems through the cavity effect. The cavity effect refers to increased absorption of radiation due to multiple reflections within a cavity. Apparent radiative surface properties of a cavity characterize the effective interactions of radiation passing through an imaginary surface covering the cavity aperture. In this study, we investigate the extent to which the apparent emissivity of a cavity with a non-uniform surface temperature profile may be estimated using an isothermal enclosure model. A cylindrical cavity was …

Controlling Electroless Deposition On Polymer Interfaces Towards Discrete Functional Particle Synthesis, Grecia Pierina Alvarado Munoz

Graduate Theses and Dissertations

Electroless deposition is a process that facilitates the formation of metal layers on surfaces through the reduction of metal ions onto a surface in the presence of a sacrificial reducing agent. This process can be applied to synthesize conductive metal layers on insulators such as glass or polymers. The kinetics of heterogeneous deposition depend on the interfacial surface chemistry, including the presence of added catalyst materials, as well as the bulk chemical environment, such as the concentration of metal ions and sacrificial reductants. Furthermore, the homogeneous formation of metal nanoparticles may compete with the deposition reaction, adversely affecting the control …

Examining Shock Wave Flow Past The Brim Of A Helmet Using Schlieren Imaging, Cody Thomas, Catherine E. Johnson

Mining Engineering Faculty Research & Creative Works

Increasing the protection a helmet provides the user from shock waves can help reduce the prevalence of blast induced traumatic brain injury (bTBI). Previous research has shown that air enters and gets trapped in the helmet-head cavity and can increase the overpressure experienced by the wearer. The brim design of the helmet has yet to be studied to understand how shock waves flow into the helmet. By studying a variety of brims, it is possible that the design can be modified to minimize shock wave flow into the helmet. This paper investigated a shock wave impacting interior and exterior facing …

Predicting Miner Localization In Underground Mine Emergencies Using A Hybrid Cnn-Lstm Model With Data From Delay-Tolerant Network Databases, Patrick Nonguin, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

Underground mining environments are highly hazardous, often prone to gas explosions, cave-ins, and fires that may trap miners during emergencies. The accurate, real-time localization of miners is vital for effective self-escape and rescue operations. Although the Mine Improvement and New Emergency Response (MINER) Act of 2006 mandates communication and tracking systems, most current solutions rely on low-power devices and line-of-sight methods that are ineffective in GPS-denied, dynamic subsurface conditions. Delay-Tolerant Networking (DTN) has emerged as a promising alternative by supporting message relay through intermittent links. In this work, we propose a deep learning framework that combines Convolutional Neural Networks (CNNs) …

Evaluation Of Performance Characteristics And Groundwater Contamination Risks Associated With On-Farm Swine Carcass Disposal Via Composting And Shallow Burial With Carbon, Gustavo Castro Garcia

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation evaluates the performance of three on-farm swine carcass disposal methods: whole carcass composting (WCC), ground carcass composting (GCC), and shallow burial with carbon (SBC), focusing on biosecurity factors and groundwater contamination risks. Foreign animal diseases (FADs), such as African swine fever and classical swine fever, pose severe economic and animal well-being risks if introduced to the United States. With confirmation of an FAD, swine movement will be halted, creating an urgent need for practical, biosecure, and environmentally responsible on-farm disposal strategies for swine carcasses. Nebraska, as a leading swine-producing state, exemplifies the vulnerability of high-density livestock regions to …

Resilience Of Interdependent Transportation And Healthcare Systems: A Simulation-Driven Framework Incorporating Social Equity And Facility Optimization, S. Yasaman Ahmadi

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The overarching goal of this dissertation is to develop an integrated, simulation-driven framework to assess and enhance the resilience of interdependent transportation and healthcare systems before, during, and after natural hazards. By examining how spatial disruptions, social vulnerability, operational constraints, and infrastructure interdependencies affect access to and functionality of hospitals, this research offers a multifaceted evaluation of system performance under stress. This dissertation examines the impact of natural hazards, particularly floods, on the interdependent transportation and healthcare systems. The proposed approach combines and advances GIS-based network analysis, graph-theoretical modeling, and discrete-event simulation to evaluate system performance under different scenarios. The …

The Advancement Of Automation In Beef Packaging Pack-Off Systems, Matthew Newman

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Marble Technologies has developed a new system for beef, pork, and lamb producers that improves quality and worker experience in the packing of products. This work explores the augmentation of this system with the introduction of robotic packing to further reduce labor, increasing worker availability for value-added tasks.

Experimentation conducted to date has explored handling delicate meat products in the standard Marble system and the proposed robotic systems. These mechanical subsystems are critical intermediaries in safely and reliably delivering products to robots and from robots to boxes. Two case studies are presented to walk through the process and challenges of …

Intelligent Multi-Layer Optical Network Design And Network Softwarization, Boyang Hu

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The growing demand for high-capacity, low-latency services has placed significant pressure on the design and operation of optical transport networks. Multi-layer optical network design—which coordinates the physical layer with higher-layer protocols—has emerged as a critical strategy to enhance resource efficiency, service flexibility, and fault resilience. Enabled by advancements in software-defined networking (SDN) and network softwarization, intelligent multi-layer architectures allow for adaptive, cross-layer control of routing, grooming, and protection mechanisms, ultimately reducing both capital and operational expenditures.

This dissertation investigates the intelligent design and simulation of multi-layer optical networks through the integration of SDN, machine learning, and high-fidelity physical-layer modeling. We …

Low Energy Ion Irradiation Effects In Electronic Devices And Materials, David C. Mccall

All Dissertations

The physics and engineering of ion-solid interactions are governed by the ion beam characteristics (flux, charge, energy) and target(s) in question. Here I present work on two projects related to the extraction of a high flux of low charge state Argon ions from a commercial plasma source and the irradiation of an engineered target, a transistor, with high charge state Argon ions.

An end-Hall ion source that produces a a high current plasma of ions and electrons in a rough vacuum environment is characterized. Using a Langmuir probe and multiple pressure measurements, the ion and electron content of the source …

A Deep Learning Approach For Semantic Segmentation And Its Application On Ctc., Samir Farag Harb

Electronic Theses and Dissertations

This dissertation explores the modeling and analysis of medical images, focusing on the intricate task of colon segmentation and subsequent 3D reconstruction, which are critical steps in Computed Tomography Colonography (CTC) systems. The primary objective of this research is to develop precise segmentation approaches to enhance the accuracy of colon identification and reconstruction from abdominal CT scans. Three distinct segmentation approaches are proposed and evaluated: a Markov Random Field (MRF)-based approach, a convolutional neural network (CNN)-based deep learning (DL) approach, and a sequential episodic training with dual contrastive learning Approach (G-SET-DCL) that has a flavor of few-shot learning (FSL). To …

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 …

Examining The Effects Of Quercetin On Phenotypic Characteristics Of Human Mesenchymal Stem Cells, Thomas Needy, David Heinrichs, Vitali Maldonado, Ryan M. Porter, Hanna Jensen, C. Lowry Barnes, Rebekah Margaret Samsonraj

Biomedical Engineering Faculty Publications and Presentations

Introduction A significant obstacle to mesenchymal stem cell (MSC) potency and therapeutic utility is in vitro senescence, an irreversible cessation of replication associated with age-related complications. Senolytic drugs, such as quercetin, may be helpful in selectively culling senescent cells while leaving non-senescent cells unaffected, thereby increasing potency of high-passage MSCs. Methods The phenotypic, genotypic, and immunomodulatory effects of quercetin were assessed using in vitro models. Senescent cells, created through repeated subculturing of MSCs in vitro, and non-senescent cells were treated with 10 mu M quercetin, differentiated into osteocytes, adipocytes, and chondrocytes, and analyzed to observe the effect of quercetin. Results …

Experimental Evaluation And Comparison Of Football-Related Head Impacts Among Ovine, Human, And Hybrid Iii Headforms, Madysn D. Cardinal

All Dissertations

Concussions and traumatic brain injury (TBI) remains a significant public health concern, especially in American football, where repeated head impacts pose long-term risks to athlete health. While current helmet testing standards rely heavily on the Hybrid III surrogate headform to evaluate protective performance, these surrogate models lack anatomical accuracy and exclude the presence of a brain component, limiting their ability to capture the true mechanics of concussion. To address this limitation, this research developed and validated a novel inverted impact testing method that allows the impact testing of a Hybrid III headform and a cadaveric specimen. Additionally, this fixture preserves …

Robust Adaptive Rigid Body State And Mass Property Estimation Via Unscented Kalman Filter On Tse(3) With Process Noise Estimation, Herman Gunter

Doctoral Dissertations and Master's Theses

Mass property estimation, including mass, center of mass, and moment of inertia, is a crucial yet challenging problem in spacecraft autonomy and astrodynamics. Knowledge of mass properties of a spacecraft is essential for future astronautical missions, as changes in the mass properties of a spacecraft due to a shift in cargo distribution often require a careful and costly recalculation to ensure applied control inputs produce the desired results. As spacecraft missions grow in both duration and number, meeting the need for precise and accurate measurements becomes increasingly complex. Stochastic effects, such as angle and velocity random walks, along with persistent …

Discovery Of High-Performance Cathode Materials For Protonic Ceramic Fuel Cells, Liang Han

All Dissertations

Environmental pollution and rapid energy consumption have become common problems in global development and will continue to grow with the world population. PCFCs use proton-conducting ceramics as electrolytes, with low activation energy and high ionic conductivity at intermediate temperatures, enabling them to operate at intermediate-temperature conditions, which can effectively solve the problems of poor stability and high cost of exotic materials of traditional solid oxide fuel cells. However, as the operating temperature decreases, the electrocatalytic activity of the cathode decreases significantly, seriously affecting PCFC’s performance. Therefore, developing high-performance cathode material suitable for working under intermediate-temperature conditions has become the key …

Secure Control And Trust Evaluation Framework For Autonomous Transportation Systems, Grace Muriithi

All Dissertations

This dissertation advances the cybersecurity of hybrid tracked vehicles (HTVs) and ship power systems (SPSs) by developing innovative cyber-attack models and corresponding defence frameworks. First, we formulate stealthy false-data-injection attacks (FDIAs) on HTV energy-management systems as a partially observable Markov decision process (POMDP) solved via deep reinforcement learning. A novel sniffing-based reward function guides the attacker to covertly degrade battery capacity and energy efficiency, which we evaluate using custom stealth–impact metrics and a sliding-window anomaly detector (Isolation Forest with Dynamic Time Warping). Additionally, we model sophisticated control-layer attacks in HTVs, including reinforcement-learning-optimised replay attacks and denial-of-service (DoS) attacks targeting generator-speed …

Understanding The Elements Of Sterile Processing Workflow: Or, Sterilization And Personnel, Sayed Rezwanul Islam

All Dissertations

The Sterile Processing Department (SPD), also known as the Central Sterile Services Department (CSSD), is an essential part of hospitals and healthcare facilities and is responsible for ensuring the cleanliness, sterility, and proper functioning of medical instruments. Sterile processing departments (SPDs) are key drivers of productivity, effectiveness, safety, and infection control in hospitals. A well-designed SPD workflow can enhance patient safety, reduce operating room (OR) delays, and improve productivity. To understand the flow of sterile processing and interactions between the OR and SPD, process maps and task analyses were developed through direct observations of the basic SPD functions: decontamination, assembly, …

Enhancing Emotional Accuracy And Behavioral Novelty In Robot Behaviors: A Generative-Discriminative Approach, Rista Baral

Boise State University Theses and Dissertations

Recent advancements in language modeling have improved robotic emotion expressiveness, yet several challenges remain. Many existing robotic expression models rely on fixed rules and static frameworks, which limit their ability to capture the dynamic nature of emotional expression. Additionally, these systems often struggle to balance emotional accuracy with generating novel and varied behaviors. These limitations underscore the need for method capable of delivering both emotionally accurate and diverse robot behaviors.

In this thesis, we addresses these challenges by introducing a new framework for expressive behavior generation in robots. We develop a generative model that generates robot behavior sequences that align …

Aging Effect On Effective Connectivity Within The Prefrontal-Motor Network And Postural-Related Muscle Responses During Dual-Task Paradigms, Jiahao Pan

Boise State University Theses and Dissertations

Falls are a significant global public issue for older adults, leading to severe health and social impacts. To understand the underlying mechanism of increased fall risk with aging, loss of postural automaticity has been suggested as increased prefrontal cortex and motor cortices activation, as well as worse balance performance in response to the secondary cognitive task. However, the interaction within these cortical regions and its effects on postural-related muscle responses are poorly understood. This dissertation investigated age-related changes in effective connectivity within the prefrontal-motor network, postural related lower limb muscle response, and biomechanical characteristics in response to the secondary cognitive …

Considerations For Developing Dna-Templated Dye-Aggregate Systems, Simon Kristopher Roy

Boise State University Theses and Dissertations

Molecular excitons have been the subject of significant research interest for nearly 100 years. Molecular excitons arise when conjugated organic molecules (dyes) are excited such that the resulting excitation is delocalized over multiple dyes in a wavelike manner. The shared excited states that allow the excitation energy to hop between molecules is of particular interest for applications that can make use of the wavelike properties of excitons, including applications in quantum information science. A key challenge for developing materials for these advanced applications is to overcome the knowledge gaps associated with precisely templating dyes with spatial control of their aggregation, …

Data-Driven Koopman Theory For Transient Stability And Safety Analysis Of Power Systems With Renewable Penetration, Bhagyashree Umathe

All Dissertations

This dissertation presents a novel approach to analyzing and controlling nonlinear systems using the Koopman operator framework and data-driven methods. Nonlinear power systems, characterized by complex behaviors and sensitivity to initial conditions, pose significant challenges for stability and safety assessment, especially during transient events.

The first part of this work focuses on reachability analysis using the spectral properties of the Koopman operator. By leveraging eigenfunctions extracted from sampled trajectory data, the approach computes forward and backward reachable sets efficiently, even in high-dimensional nonlinear systems, without requiring dense state-space sampling. This method is validated through numerical examples, demonstrating its ability to …

Development Of A High-Performance, Cost-Effective Architecture For Real-Time Fourier Transform Analysis On An Efinix Trion Fpga, Luke Cashwell

Honors Theses

This project presents the development of a high-performance, cost-effective, and powerefficient pipelined architecture designed to execute 10,000 Fast Fourier Transforms (FFTs) per second on an Efinix Trion T120 FPGA. Each FFT processes 4096 signed 13-bit elements, facilitating real-time data analysis for a Time-Domain Impedance Probe (TDIP) operating at a maximum data rate of 490 Mbit/s. The algorithm utilizes the built-in multipliers and dual-port memory cells of the FPGA to optimize data storage, transfer, and processing. It achieves this high performance while only using approximately 4% of the Look-Up Tables (LUTs), 7% of the integrated RAM cells, and 15% of the …

Data-Driven Stochastic Programming For Disaster Housing Logistics Planning, Sheng-Yin Chen

All Dissertations

This dissertation develops an integrated modeling and solution framework for direct temporary disaster housing logistics under demand uncertainty. The proposed framework addresses the problem from short-term, long-term, and computational perspectives. First, a two-stage chance-constrained stochastic programming (TSCC) model is developed for short-term housing logistic planning, with demand scenarios generated via a data-driven spatial regression model that captures the relationship between housing demand, hazard exposure, and socioeconomic factors. A case study based on Hurricane Ian demonstrates that the TSCC model outperforms deterministic and traditional scenario-based models in both solution quality and robustness. Second, to address long-term housing logistics planning, a multi-horizon …

Crevice Corrosion Mechanisms Of Cocrmo Alloys In Orthopedic Implants: Retrieval Analysis, Nano-Tribocorrosion And Cellular Responses, Hwaran Lee

All Dissertations

Mechanically assisted corrosion and non-mechanically (chemically) driven corrosion in modular junctions of orthopedic implants using cobalt-chromium-molybdenum (CoCrMo) alloys remain clinical concerns and may contribute to implant failure. The underlying corrosion mechanisms are not yet fully understood, leaving a critical research gap. We hypothesized that corrosion in modular junctions may be driven by aggressive local environments, including fretting, metal ion release (cobalt ion, Co²⁺), low pH and reactive oxygen species (ROS). This dissertation aims to (1) analyze corrosion modes and potential causes in modular junctions; (2) identify chemically driven corrosion modes on CoCrMo alloys using simulated inflammatory modular taper …

Self-Poled P(Vdf-Trfe) Based Composites For Energy Harvesting And Wearable Sensor Applications, Lavanya Muthusamy

All Dissertations

The growing demand for flexible, low-power, and self-powered wearable electronic systems has accelerated research interest in polymer-based sensors and energy harvesting technologies. Among piezoelectric polymer materials, Poly(vinylidene fluoride-trifluoro ethylene) [P(VDF-TrFE)], over the years, has garnered significant attention due to its unique piezoelectric properties, high dielectric constant, mechanical flexibility, thermal stability, chemical resistance, biocompatibility and compatibility with scalable fabrication processes. Despite its advantages, conventional P(VDF-TrFE)-based devices often require external poling and face limitations in integration with low-cost, flexible substrates. To overcome these limitations, this research study explores the nanofiller approach, along with facile fabrication processes, and structural design strategies aimed at …

Simulation- And Machine Learning-Based Methods For Inland Waterway Operation And Maintenance Decision-Making, Maryam Aghamohammadghasem

Graduate Theses and Dissertations

The U.S. inland waterway transportation system (IWTS) is an essential part of the country's multimodal freight transportation network. In addition to seasonal droughts and floods, the operations of the IWTS may be disrupted by random malfunctions and scheduled maintenance of its critical components. Among these critical components, locks play a key role in the operation of navigable inland waterways, and lock-induced disruptions to the supply chains of related industries, such as agriculture and manufacturing, often result in significant economic losses. To assess the performance of the U.S. IWTS, we develop a PyNetLogo simulation tool to capture the movements and delays …

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 …

An Ant-Colony Approach To Scheduling Charging Sessions Of Electric Vehicle Fleets With Heterogeneous Scheduling Constraints, Derek D. Redmond

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles and electric-vehicle fleets are gaining widespread usage. A major challenge of managing an electric-vehicle fleet is scheduling when the vehicles can charge and when the vehicles can complete their tasks. Finding smart ways to schedule electric-vehicle charging reduces both the cost of charging vehicles and increases the health of the grid and the environment. This best-of-both-worlds outcome is because of the pricing structure that electric utility companies use. When minimizing the cost of charging the vehicles, it is important to consider that vehicle fleets have constraints on when they can charge. Vehicles are usually limited by the tasks …

Optimization And Utilization Of Microbial Electrolysis Cells In Waste To Product Applications, Hayden Harrison

All Graduate Theses and Dissertations, Fall 2023 to Present

As the world searches for cleaner and more sustainable energy solutions, turning waste into fuel is an increasingly attractive strategy. This research focuses on microbial electrolysis cells, a new technology that uses bacteria and a small amount of electricity to convert organic waste—like food scraps or wastewater—into useful gases such as hydrogen and methane. These gases can be used as energy sources to reduce dependency on more traditional fuels.

This thesis tackles two key challenges that limit the real-world use of microbial electrolysis systems. First, it introduces a simpler and more effective method to stop hydrogen losses in single-chamber cells. …