Engineering Commons^™

Modeling And Simulations Of An Input Coupler For A High-Power Traveling Wave Tube Amplifier As A Preliminary Investigation Into A Multi-Stream Traveling Wave Tube Amplifier, Ethan Wade

Electrical and Computer Engineering ETDs

The University of New Mexico (UNM) is working on developing a multi-stream Traveling Wave Tube (TWT) amplifier. One of the first steps to be taken during the design of a TWT amplifier is to design an input coupler to couple power from a lower power High Power Microwave (HPM) seed source to the slow wave structure (SWS) of the amplifier. In order to aid in the development of a TWT which operates in X-band, multiple options for input couplers have been designed for use in a greater TWT project at UNM. The primary tasks to be addressed with these input …

Mg And Fe Co-Doped Perovskites For The Electrochemical Oxidative Coupling Of Methane In Solid Oxide Electrolyzers, Luke H. Denoyer

Chemical and Biological Engineering ETDs

More efficient usage of shale gas reserves and natural gas resources will allow for higher olefin yields and lower greenhouse gas emissions. The oxidative coupling of methane (OCM) is a direct pathway for converting methane to ethylene at temperatures >700 °C. The OCM process is typically regulated via the choice of catalyst, reactor conditions, temperature range and gas mixing. The electrochemical oxidative coupling of methane (E-OCM) is a modification to the OCM reaction by controlling the oxygen content via externally applied potentials to an SOEC. Perovskite oxide catalysts are useful for E-OCM due to their flexible bond networks and desired …

Performance-Based Full Depth Reclamation Design, Moatasem H. Algburi

Civil Engineering ETDs

The Full-Depth Reclamation (FDR) technique is a cold-mix asphalt (CMA) technology employed in New Mexico to rehabilitate existing pavements. It results in minor disruption to traffic, environmental advantages, and decreased construction period and costs. However, insufficient data on the material properties of FDR mixtures and their characterization limits the use of the mechanical-empirical (M-E) design method of FDR materials. The MEPDG develops performance models using the structural response of pavement layers to predict pavement structure systems based on material properties, climate models, and loading conditions. This study has developed MEPDG models to predict the long-term performance of FDR materials and …

Fail-Safe Logic Design Strategies Within Modern Fpga Architectures, Priya A. Bhakta

Electrical and Computer Engineering ETDs

Field Programmable Gate Arrays (FPGAs) are vulnerable to radiation-induced single event upsets (SEUs) and fault injection attacks, requiring the use of redundancy techniques such as fail-safe computing. Fail-safe computing refers to computing systems that revert to a non-operational safe state when a fault occurs. This work investigates circuit-level techniques and implements fail-safe computing processes as mitigation for SEUs and fault injection attacks on FPGAs. The analysis reveals vulnerabilities that exist in FPGAs over those in application-specific integrated circuits (ASIC); thus, requiring a more elaborate network of redundant circuits and checking logic. The reconfiguration capability of FPGAs adds complexity to fail-safe …

Source Detection And Automatic Modulation Classification For Modern Antenna Array Processing, Jayakrishnan Vijayamohanan

Electrical and Computer Engineering ETDs

Source detection and automatic modulation classification are two of the most important steps in any array processing task. In this research a novel deep learning model referred to as RadioNet, is proposed that is focused on solving both these problems by reformulating them as a multi-label classification problem. Traditional approaches to both these topics face challenges in scenarios with noise, interference, fewer number of snapshots, and high number of sources. The limitations of the conventional models are investigated and overcome by the proposed solution. RadioNet is also compared with other existing state-of-the-art machine learning based solutions. The introduced model is …

Simulation Studies Of Mvdc Power Cable For All Electric Aircrafts, Aban Samimi Motlagh

Electrical and Computer Engineering ETDs

MVCD power cable has a vital task in future commercial electric aircraft, which is power delivery. The temperature of the cable during the cable’s operation under low pressure is higher than the atmospheric pressure, which increases the cable losses. In this paper, the temperature and electric field across the insulator of the 5 kV DC Southwire cable is simulated up to 10 hours of cable operation. Furthermore, the temperature of the cable is shown with and without the presence of the chamber box. The other issue of the MVDC power cable is the cable joints and terminations. The electric field …

Theory And Algorithms To Learn, Propagate, And Exploit Uncertainty For Stochastic Optimal Control Of Dynamical Systems, Vignesh Sivaramakrishnan

Electrical and Computer Engineering ETDs

Non-Gaussian uncertainty frequently arises in learning and control problems involving stochastic dynamical systems, particularly in autonomous vehicles, UAVs, satellites, and robotics. In this dissertation, we propose a new framework that leverages characteristic functions that provides a frequency-domain representation of random variables. The dissertation is structured into three key areas. First, we address model-based stochastic optimal control for linear systems with non-Gaussian noise, demonstrating that characteristic functions can be used to enforce chance constraints and control systems toward desired distributions. Second, we explore data-driven stochastic control, utilizing empirical characteristic functions to handle systems with unknown disturbances. In addition, we derive several …

Targeting Myeloid Cell Iron Metabolism In Salmonella-Induced Colitis, Mariella Arcos Padilla

Biomedical Engineering ETDs

Salmonellosis is a severe infection caused by Salmonella enterica serovar Typhimurium, leading to significant global morbidity and mortality.

Previous studies have shown that mice lacking the iron storage protein ferritin heavy chain (FTH1) in myeloid cells exhibit worsened Salmonella infection. Nuclear receptor co-activator 4 (NCOA4) directs FTH1 autophagic degradation to release iron from storage during conditions of low iron. However, the role of myeloid NCOA4 in regulating bacterial infections remains unclear.

Here, we found that myeloid NCOA4 deficiency augments spleen iron levels and increases cellular iron accumulation, oxidative stress, and ferroptosis in bone marrow-derived macrophages (BMDM) cells. This deficiency also …

Evaluation Of Electrode Configurations For (0,2) Piezoelectric Ultrasound Transducers, Abdul Qayoum Popal

Mechanical Engineering ETDs

Piezoelectric micro ultrasound transducers (PMUT array) are pivotal in MEMS applications. They typically operate in the fundamental (0,1) acoustic mode and are not significantly researched for higher modes (0,2) and (0,3). Similarly, vibrating mesh atomizers (VMAs) demand the second (0,2) mode and third mode (0,3) for effective aerosol generation, highlighting the need for optimized electrode configurations—a relatively unexplored area. This study presents the first comprehensive analysis of how electrode designs influence PMUT performance in the (0,2) mode for VMA applications.

Utilizing COMSOL multiphysics finite element modeling (FEM) with residual stress considerations alongside experimental validation, we demonstrate that optimized electrode configurations …

Modelling V-Band Atmospheric Loss With Deep Learning, Ralph Lyndon Gesner

Electrical and Computer Engineering ETDs

Modelling atmospheric loss is fundamental to implementation of future mm-wave terrestrial and earth space communication links. Atmospheric losses have traditionally been estimated by calculating the contributions of individual weather phenomena through in-situ meteorological measurements and statistically derived models for estimating localized atmospheric water content. Collecting data for all points along the propagation path and calculating the physical effects of gases, clouds, and precipitation individually is both time consuming and impractical for large-scale use cases.

In response to these present limitations, this work proposes the use of novel deep learning models for estimating atmospheric losses from tabular meteorological sensor data and …

Rational Design Of Nanoparticles For Overcoming Barriers Of Nucleic Acid Delivery: Applications In Cancer Therapeutics, Angelea M. Maestas-Olguin

Chemical and Biological Engineering ETDs

The use of exogenous nucleic acid technologies to modulate aberrant protein expression resulting from genetic mutations is a promising therapeutic approach for the treatment of diseases such as cancer. The promise of nucleic-based therapeutics is dependent on the development of platforms that effectively protect nucleic acids from nuclease degradation and deliver the nucleic acids to specific intracellular locations (nucleus or cytosol) of target cells. The application of nanotechnology for development of nucleic acid-based nanomedicines is poised to revolutionize the clinical landscape of cancer. In this dissertation, I demonstrated the rational design, synthesis and evaluation of a lipid coated mesoporous silica …

Energy Efficiency Optimization In Integrated Sensing And Communication Networks, Arianna M. Santamaria Penafiel

Electrical and Computer Engineering ETDs

In the emerging landscape of Integrated Sensing and Communication (ISAC) networks, achieving energy efficiency while concurrently performing sensing and communication tasks remains challenging. This paper introduces a new framework, a novel solution that empowers User Equipment (UEs) to make informed decisions regarding their transmission power allocation, optimizing the energy efficiency of sensing, communication, and data reporting to the gNB (gNodeB) functions. Initially, a novel ISAC network paradigm is proposed, where the gNB employs rewards, such as monetary incentives, to motivate UEs to engage in sensing, data collection, and reporting within its coverage area based on the principles of Contract Theory. …

Decision Making And Performance Optimization In Distributed Cyber Physical Networks, Md Sahabul Hossain

Electrical and Computer Engineering ETDs

Cyber-Physical Systems (CPSs) integrate computation, networking, and physical processes, while Cyber-Physical Networks (CPNs) enable communication and coordination among components. With advances in IoT and smart devices, CPSs are increasingly vital for applications such as smart grids, industrial automation, and autonomous vehicles. This dissertation explores decision making and performance optimization in Distributed Cyber-Physical Networks (DCPNs), focusing on efficiency, reliability, decentralization, and security. Using network economic theories (e.g., game theory, contract theory) and machine learning (e.g., Reinforcement Learning, Federated Learning), it addresses key problems: 1) a cost-effective positioning system with Reconfigurable Intelligent Surfaces (RISs) and RL, 2) energy-efficient task offloading in Multi-access …

Training Machine Learning Algorithms For The Transient Startup Of A Long-Life Modular Microreactor, Ahmad N. Shaheen

Nuclear Engineering ETDs

There is an increasing interest in developing and deploying small modular nuclear reactors (SMRs) and micro modular reactors (MMRs). They could be operated with minimal on-site personnel or remotely with a high degree of autonomy. This can be enabled through the use and application of Artificial Intelligence (AL) and Machine Learning (ML) algorithms and methods. The objective of the present work is to train machine learning algorithms for remote control mimicking the transient startup of the Very-Small, Long-LIfe, Modular (VSLLIM) microreactor. This walk-away safe microreactor design and a fully integrated transient model have been developed at the University of New …

Custom Cathode Optimization For Electropolishing Additively Manufactured 316l Stainless Steel, Kasandra Escarcega Herrera

Mechanical Engineering ETDs

Laser powder bed fusion (LPBF) has become increasingly popular for its ability to rapidly manufacture complex metallic parts. However, the surface properties of as-built LPBF parts may degrade overall performance due to tortuous surface features. Consequently, post-processing like electropolishing (EP) to reduce the surface asperities is often needed for LPBF parts to perform as expected. Utilizing experimental and computational approaches, this project aims to more uniformly EP complex shaped parts made from LPBF 316L. For the experimental approach, parts with a three-dimensional T-shape were printed out of 316L stainless steel and EP using an acidic-based and a polyethylene glycol/NaCl-based electrolyte. …

Ge/Sige Quantum Wells: Material For The Post-Moore Era, Troy Alexander Hutchins-Delgado

Optical Science and Engineering ETDs

This dissertation demonstrates high-quality germanium quantum wells on a 200 mm silicon wafer platform, enabling novel device possibilities. Partnering with a commercial silicon-germanium epitaxy supplier, we obtained shallow, undoped germanium quantum wells with high-crystalline quality, confirmed through x-ray diffraction, secondary ion mass spectroscopy, high-resolution scanning transmission electron microscopy, and energy dispersive x-ray spectroscopy. Hall bar devices fabricated on single quantum wells revealed that surface preparation can tune transport properties while maintaining peak mobilities around 10⁵ cm²V⁻¹s⁻¹. Manganese-germanide spintronic contacts were integrated via solid-state reaction, with contact quality assessed through Schottky diodes, transfer length …

Soc-Based Control System Performance Analysis For Trapped-Ion Quantum Computing, Tiamike Dudley

Electrical and Computer Engineering ETDs

Scatter-gather dynamic-memory-access (SG-DMA) is utilized in applications that require high bandwidth and low latency data transfers between memory and peripherals, where data blocks, described using buffer descriptors (BDs), are distributed throughout the memory system. The data transfer organization and requirements of a Trapped-Ion Quantum Computer (TIQC) possess characteristics similar to those targeted by SG-DMA. In particular, the ion qubits in a TIQC are manipulated by applying control sequences consisting primarily of modulated laser pulses. These optical pulses are defined by parameters that are (re)configured by the electrical control system. Variations in the operating environment and equipment make it necessary to …

Analyzing The Key Characteristics And Benefits Of Ccpr (Cold Central Plant Recycling) In Road Rehabilitation And Sustainability, Bassam Abou Yassine

Civil Engineering ETDs

Cold mix asphalt (CMA) technologies are being used in the United States and have environmental benefits. However, these technologies are not fully developed. We do not yet know their resilient and dynamic modulus, which are important for designing pavement thickness. They have not being used widely because we do not know also their performance. This study looks at three Cold Central Plant Recycling (CCPR) materials to help fill this gap. We conducted several lab tests, including the Hamburg Wheel Tracking Test (HWTT), Semi-Circular Bending Test (SCB), and Texas Overlay Test (TOT). We also tested the mechanical properties of the CCPR …

Modeling W/V-Band Satellite Communications In The Presence Of Noise Jamming, Ryan Michael Eckman

Electrical and Computer Engineering ETDs

Understanding the performance of wideband modulated signals under noise jamming conditions is important for advancing W/V-band military satellite communications. This research developed and validated models to predict performance degradation of a communication channel in the presence of wideband noise jamming. Channel models were developed that included both modulated communication signals and jammer signals. Integrated models included environmental link factors and practical implementation factors. Integrated models were verified and validated using outdoor radio frequency environments utilizing two W/V-band transceivers, a portable W-band jammer, and software defined radios. Experimental results demonstrated excellent agreement with integrated model predictions. Channel degradation due to the …

Trust-Me: Resource Allocation And Server Selection Based On Trust In Multi-Access Edge Computing, Sean Tsikteris

Electrical and Computer Engineering ETDs

Multi-access Edge Computing (MEC) is crucial for Internet of Things (IoT) applications by optimizing data processing and reducing latency. This thesis presents contributions to resource allocation and decision-making in edge computing environments. The TRUST-ME model is introduced, involving multiple edge servers and IoT devices (users) offloading computing tasks to MEC servers. A utility function is designed to assess latency and cost benefits for IoT devices using server resources. The core innovation is a novel trust model that evaluates IoT devices’ confidence in MEC servers by integrating both direct and indirect trust, based on interactions and feedback from other devices. In …

Antimicrobial Activity And Photostability Of Cationic Conjugated Polyelectrolytes, Mohammed Ismael Khalil

Chemical and Biological Engineering ETDs

Antimicrobial resistance is a growing global health concern, driving the need for novel

therapeutic strategies. This study explores the antimicrobial efficacy of conjugated

polyelectrolytes (CPEs) and oligo-phenylene ethynylenes (OPEs) in bacterial and viral

inactivation. Quantitative analysis revealed that light-activated CPEs and OPEs

effectively reduced bacterial viability within minutes, with significant log reductions

observed under both light and dark conditions. Additionally, the antiviral potential of a

cationic conjugated oligomer was investigated, demonstrating rapid and near-complete

inactivation of SARS-CoV-2 under visible light, both in solution and on filter materials.

Further analysis of their photophysical properties revealed that, even after

photobleaching, the compounds …

How Wildfires Threaten Water Resources: A Case Study Following The Largest Wildfire Recorded In New Mexico, Eric A. Joseph

Civil Engineering ETDs

Wildfire disturbance propagation along fluvial networks remains poorly understood. We use incident, atmospheric, and water-quality data from the largest wildfire in New Mexico’s history to quantify how this gigafire affected surface runoff processes and mobilized wildfire disturbances into fluvial networks after burning 1382 km². Surface runoff post-fire increased compared to pre-fire conditions, and precipitation events that are frequently observed in the affected watershed (<2-year recurrence) and fell during the post-fire first rainy season resulted in uncorrelated, less frequently observed runoff events (10-year recurrence). Wavelet coherence analysis highlighted that water quality disturbances propagated variably along the network, even at sites located >160 km downstream of the burn perimeter. Our findings emphasize the need to incorporate spatially resolved longitudinal sampling designs into wildfire water quality research and highlight the spatiotemporal co-dependency among atmospheric, terrestrial, aquatic processes …

Robust Data-Driven Run-To-Run Control Via One-Step Constrained Optimization For Automated Serial Sectioning, Rhianna M. Oakley

Mechanical Engineering ETDs

This Thesis develops a one-step predictive run-to-run controller (R2R-MPC) for automating a mechanical serial sectioning (MSS) system. MSS is a destructive material analysis process that iteratively removes slices of material and captures 2D images, reconstructing them into 3D representations. Commonly used in material science for characterizing materials and failure analysis, MSS typically operates in an open-loop fashion, which experiences high variability in material removal due to system disturbances. To address this, a robust closed-loop R2R-MPC is presented, modeling MSS process uncertainty using a linear differential inclusion identified from operational historical data. The R2R-MPC is posed as an optimization problem that …

Longitudinal Pedestrian Safety Trends By Vehicle Type And Model: A 2015-2022 Study Of Texas, Olivia Tafoya

Civil Engineering ETDs

We observed pickup trucks, SUVs, and passenger cars and their two most popular vehicle models across Texas from 2015 through 2022. For each vehicle type and model, we obtained all reported pedestrian crashes, counts of registered vehicles, and vehicle design characteristics. Results suggest that older vehicles are more likely to seriously injure or kill a pedestrian than newer ones. They also indicate that SUVs were more deadly, after controlling for exposure using the number of registered vehicles, than other vehicle types. Of the models studied, the full-size SUVs proved to be particularly dangerous for pedestrians, being 2.08 times more likely …

Design, Fabrication, And Characterization Of Electro-Optic Radio-Frequency Probes For High Field Environments, Michael D. Sherburne

Electrical and Computer Engineering ETDs

Design, Fabrication, and Characterization of Electro-Optic Radio-Frequency Probes For High Field Environments

Deterministic Transport Of Coupled Energetic Light-Ions And Neutrons With Application To Inertial Confinement Fusion, Kyle Beling

Nuclear Engineering ETDs

Numerical simulations of an inertial confinement fusion (ICF) target during the implosion process require high fidelity models of the radiation transport process. This work is interested in the transport of high-energy light-ions and neutrons in a background ICF plasma. As these energetic particles slow down, they experience knock-on (recoil) and thermonuclear (TN) collisions with the light-ions in the background plasma. These recoil and TN collisions excite the background light-ions causing them to transport through the plasma further exciting background light-ions. Mathematically, this cascading effect is described as a system of linear Boltzmann transport equations coupled through recoil and TN collision …

Physical Layer Entropy Analysis For Physical Unclonable Functions, Jenilee Jao

Electrical and Computer Engineering ETDs

Process variations within Field Programmable Gate Arrays (FPGAs) provide a rich source of entropy, making them well-suited for the implementation of Physical Unclonable Functions (PUFs). This dissertation presents three studies on FPGA-based PUFs. First, we explore a ring-oscillator (RO) PUF that leverages localized entropy from individual look-up table (LUT) primitives, analyzing design bias. Next, we investigate delay variations that occur through the routing network and switch matrices of FPGAs using a feature of Xilinx called dynamic partial reconfiguration (DPR). Finally, we evaluate entropy across FPGAs from Xilinx, Altera, and Microsemi using the Shift-Register Reconvergent-Fanout (SiRF) PUF architecture to compare path …

Advancing Drug Discovery And Disease Understanding Through Knowledge Graphs And Machine Learning Techniques, Swastika Tenkila Purushotham

Electrical and Computer Engineering ETDs

This thesis investigates knowledge graphs with particular reference to the NIH-funded Common Fund Data Ecosystem Data Distillery project. By combining data from nine Common Fund projects and other sources, this project has created a large knowledge graph using Neo4j. To find new and undiscovered drug targets, UNM’s Illuminating the Druggable Genome (IDG) Data Coordinating Center has supplied data and use cases. Condensed Knowledge Graph, a condensed version that is based on the Data Distillery Knowledge Graph, improves usability for IDG applications. Condensed Knowledge Graph research endeavors to enhance data organization through the categorization of disease terms, examination of Cerebellar Stroke …

Autonomous Coalition Formation For Energy Trading In Intelligent Grid Systems, Issiac Baca

Electrical and Computer Engineering ETDs

This paper introduces an interactive model and architectural framework for a smart grid system, emphasizing the prosumers dual roles as energy buyers and sellers within localized energy trading markets, i.e., coalitions. Initially, the utilities of both buyers and sellers are formulated to capture the benefits derived from their energy-related activities. Then, the paper presents the Approximate SMARTFORM (ASMARTFORM) mechanism, based on the principles of matching theory, to enhance the prosumers engagement in coalitions by addressing externalities influencing their decisions. To further improve the coalition formation process, the Accurate SMARTFORM (AccSMARTFORM) mechanism is formulated based on the theory of coalition games, …

Methods For Efficient Computation Of Neutron Multiplicity Distributions And Snm Sample Characterization, Jawad Ribhi Moussa

Nuclear Engineering ETDs

This dissertation advances neutron multiplicity counting (NMC) by developing a hierarchy of computational methods that combine deterministic and stochastic techniques with modern machine learning for improved special nuclear material (SNM) characterization. A system state-updating Monte Carlo method is introduced in addition to a dynamic point kinetic model based on a backward Master equation (BME) formulation. These models, along with newly developed distribution reconstruction methods, enable more efficient computation of neutron count distributions in a fixed detector time-gate. NMC limitations associated with finite-size and neutron phase effects are also addressed by extending the BME model to account for time-gated neutron count …