Engineering Commons^™

Auto-Tuning And Applications Of Transient Voltage Suppressor Models In Full-Wave Simulations, Daniel Peter Szanto

Masters Theses

System efficient electrostatic design (SEED) combines full-wave geometry information with SPICE models of non-linear protection devices, typically transient voltage suppression (TVS) diodes, to allow optimization and validation of electrostatic design (ESD) protection early in the design process. TVS models have previously been developed which may be used in SPICE simulation tools like Keysight ADS, but these models could not be used directly in full-wave simulation tools like CST Studio. A process was developed for converting existing ADS models of TVS devices to a form that can be used within a CST full wave/SPICE hybrid simulation. Three TVS models were converted …

Frequency-Tracker And Power Supply For Piezoelectric Lunar Dust Removal Actuator, Praneeth Uddarraju

Masters Theses

"This work presents a reconfigurable phase-locked loop (PLL)-based control system for the resonant excitation of piezoelectric actuators aimed at automated removal of particulate contaminants from photovoltaic (PV) surfaces—particularly in extraterrestrial environments such as the lunar surface. Regolith or lunar dust buildup on solar panels is a serious hazard to the effectiveness of energy harvesting on extended missions. By using high-frequency structural excitation and inertial forces the suggested system removes surface impurities. Tunable Sallen-Key low-pass filters for reliable feedback conditioning are used in conjunction with a digitally implemented PLL on an FPGA (XLR8 platform) to precisely lock the drive frequency to …

An Experimental Study Into The Methods Of Water Coupling And Their Impact On Kinetic Energy And Blast Over Pressure Through The Use Of A Ballistic Pendulum, Jeremiah Alan Cohn

Masters Theses

Water coupled charges utilize the material properties of water to alter their behavior for reductions in overpressure and increases in kinetic energy. Although water coupling has been studied directly, combined usage of the two primary methods of water coupling, tamping and pushing, hinders further research. This study addresses the gap in literature by comparing ballistic pendulum and blast data for charges with water tamping and pushing to determine differences in kinetic energy, peak overpressure, impulse, noise and duration of fireball. The results showed that water tamping provided a 69.1% increase in kinetic energy, an 18.6% reduction in incident overpressure, a …

Selective Surface Activation And Flotation Of Pyrite For The Recovery Of Tellurium From Sulfide Tailings, Mulenga Mutema Chibesa

Masters Theses

Copper sulfide tailings from past and present mining operations are important secondary sources of critical elements such as tellurium (Te), a key component in cadmium–telluride photovoltaic solar cells. Characterization of tailing streams from copper porphyry (CP) ore flotation revealed that Te-bearing minerals are predominantly hosted in pyrite, which is usually depressed and discarded. Enhancing pyrite recovery is therefore a critical first step toward concentrating Te minerals for downstream extraction. However, pyrite flotation is often hindered by hydrophilic surface complexes formed during prior processing. This research investigated selective flotation of Te-bearing pyrite from CP tailings using micro flotation and bench-scale flotation, …

Aerodynamic Design Workflow Optimization For Fsae: Advanced Cfd And Hpc Automation, Kyle Maynor

Masters Theses

This research identifies and resolves inefficiencies in the Computational Fluid Dynamics (CFD) workflow of the Missouri S&T Racing Formula SAE Team’s aerodynamic development. Key bottlenecks were found in simulation runtime, laborious simulation preparation, an overly manual simulation submission process, and unchecked mesh quality. A fully reimagined workflow was implemented with simulation parameters to adjust vehicle attitudes. From this, an automated design sweep could be executed to generate aero maps of the developing vehicle using the Design Manager Project. A Python-based submission app handles the terminal interfacing and macro editing that significantly slowed the job submission process before. Using a university …

Design Of A Spacecraft Power System Experiment, Jay Bakulkumar Kamdar

Masters Theses

This research delves into the design, implementation, and analysis of a controlled experimental framework for photovoltaic cell characterization and its application in spacecraft power systems. Such a system was simulated and validated by benchmarking characteristics of a photovoltaic module and implementing them in a system design simulation yielding performance data for comparative analysis. A hardware setup was developed to perform IV characterization tests under steady state thermal conditions. Experiments conducted across various thermal regulation profiles helped quantify the effects of temperature on the photovoltaic performance parameters. Active cooling reduced the steady state cell temperature by 17.9% and improved the cell …

Enabling Drone-Integrated Active Microwave Thermography Via A Slot Antenna Design, Alec P. Fitzmaurice

Masters Theses

Civil infrastructure inspection quality and inspector safety may be enhanced from the advancement in the capabilities of nondestructive testing and evaluation of remote or otherwise hard-to-reach areas such as nuclear power plants, wind turbines, bridges, or other civil infrastructure using drone-based Active Microwave Thermography (AMT). AMT is a nondestructive testing technique that utilizes high frequency energy (often radiated from an antenna) to induce heating in a specimen. Following this thermal excitation, an infrared camera is used to measure the resulting surface thermal profile. From this, defect indications may be detected. To enable drone-based deployment of AMT, where the antenna size …

Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty, Michael David Parrish

Doctoral Dissertations

"Every good leader is a good manager, but not every good manager is a good leader. The difference between the leader and the manager is critical decision-making. Today’s decision-making environment is characterized as Volatile, Uncertain, Complex, and Ambiguous (VUCA). With the exponential increase in the technical capabilities of systems, the human has become the weakest link in the use of such systems. To remain relevant, good leaders must continuously adapt to new advances in technology and processes.

The research contributions of this work provide several unique and novel solutions for leaders to utilize artificial intelligence tools to improve and optimize …

Process-Structure-Property Relationships In Laser Powder Bed Fusion Produced 17-4 Ph Steel, Ben Brown

Doctoral Dissertations

Laser powder bed fusion (LPBF) is a metal additive manufacturing method that produces non-traditional microstructures as a result of the rapid solidification and thermal cycling inherent to the process. When using LPBF-produced material in application, these unique microstructures challenge the applicability of well-developed mechanical property databases achieved by conventional heat treatments. For wider adoption of this technology, a more holistic understanding is necessary on how process attributes develop material structure, which dictate mechanical properties. This dissertation explores the process structure-property relationships in LPBF 17-4 PH steel through systematic evaluation of atmospheric processing and heat treatment effects on microstructure and mechanical …

Phase-Field Modeling Of Rapid Solidification Processes, Nima Najafizadeh

Doctoral Dissertations

"Many advanced manufacturing processes such as additive manufacturing utilize rapid solidification of alloys, as it enables the formation of exotic non-equilibrium microstructure and thus improved properties. However, the interrelationship between the processing parameters and the resulting microstructure in rapid solidification is yet to be fully understood. We aim to investigate the microstructure evolutions during the rapid solidifications using phase-field modeling. The phase-field method assumes a diffuse interface, which avoids tracking the moving interface and hence enables efficient numerical simulations for complex microstructure evolution. A phase-field model with coupled solute-thermal diffusion and solute trapping effect is developed to investigate the rapid …

Lifelong Machine Learning With Adaptive Resonance Theory, Sasha Petrenko

Doctoral Dissertations

"This publication option dissertation is composed of three papers concerning the study of the problem lifelong machine learning with Adaptive Resonance Theory (ART) algorithms. Lifelong learning (L2) is a challenging machine learning paradigm that both encompasses and formalizes the fields of continual learning and incremental learning. The field is concerned with the mitigation of the phenomenon of catastrophic forgetting whereby learning agents that are faced with incrementally novel information deleteriously overwrite previous knowledge if that learning process is not regularized to counteract this consequence. ART algorithms solve this stability-plasticity dilemma by optimally assigning learning to categories or instantiating new knowledge …

Exploring The Feasibility Of Innovative Integration Of Phase Change Materials For Thermo-Adaptive Asphalt Pavements, Farshad Saberi Kerahroudi

Doctoral Dissertations

"Current research examined the feasibility and efficiency of employing phase change materials (PCMs) in asphalt pavement materials to result in thermo-adaptive asphalt pavement. The PCM was introduced to the asphalt materials in three different scales, including asphalt binder, asphalt mastic, and asphalt mixture. After investigating asphalt at different scales, mix blending method was found as the easiest method without any complexity to mix asphalt binder with PCM. The testing results could reveal an improvement in the high temperature performance of asphalt binder without sacrificing the low temperature performance with the presence of PCM and Gilsonite. Also, introducing PCM to asphalt …

Systematic Esd Analysis And Modeling For Electronic Device, Zhekun Peng

Doctoral Dissertations

Systematic ESD analysis provides good pre-compliance to ESD robustness evaluation on the electronic device from device level to component/system level to on-chip level. The whole process involves corona discharge on display, system level ESD analysis on PCB for race condition and transient response and 3D IC package impact to on-die ESD.

ESD to the display cover glass can damage touchscreen traces by sparkless corona discharges on the glass surface. A non-linear time dependent transmission-line model is proposed to model corona streamer propagation in terms of the coupling current and propagation speed. Results are highly promising to model the corona discharge …

Identifying Early Warning Signs Of Construction Labor Shortages, Ahmed Shiha, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Construction labor shortages constrain project-level objectives and national development plans. The goal of this study is to utilize the lagged effects of macroeconomic conditions as early warning signs of construction labor shortages. To this end, the authors adopted a methodology, encompassing (1) retrieval of publicly available data and preprocessing of construction labor shortage as the target variable and macroeconomic measures as the explanatory variables, (2) identification of short-term associations between shortages and economic cycles using the Granger causality test, (3) examination of long-term relationships between labor shortages and economic conditions using the Johansen cointegration test, and (4) estimation of the …

Visual Understanding Of Rock Wettability Distribution To Contact Angle Regions And Oil Displacement Patterns In The Silty Sand Reservoir Via 2d Pore-Scale Modeling, H. Al-Ajaj, W. Al-Bazzaz, Ralph E. Flori, S. Alsayegh, H. Almubarak, D. S. Ibrahim, H. Al-Saedi

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

This study, conducted using a silty sand reservoir rock extracted from a Kuwait-producing oilfield, provides crucial insights into fluid distribution patterns and mineralogy, as well as wettability contact angle preferences. The method used for visual identification not only captures rock physics but also suggests effective oil recovery displacement strategies. Visual identification is presented using 2D image technology and a Scanning Electron Microscope (SEM). Analytical data are presented from electron bombardments and backscattering reflections collected in the BSE detector. These analyses were used to characterize the various surface boundary morphology parameters of the silty sand mineral surfaces, including area, perimeter, mineral …

Topology And Parameter Joint Identification In Imbalanced Low-Voltage Distribution Networks Based On Load Characteristic Propagation, Yanan Zhang, Gan Zhou, Huan Mao, Wei Gu, Yanjun Feng, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Low-voltage distribution networks often suffer from incomplete or outdated network records, making it challenging to obtain the topology and line parameters under actual operating conditions. To address this issue, a joint identification method is proposed based on the propagation of load transient characteristics. First, the principle of load characteristic propagation is elaborated, and the concept of coupling impedance is introduced. Second, a set of linear regression equations is established based on the changes in current and voltage of the terminal measurements before and after load switching, and then these equations are solved using the least squares method to form the …

Transplant Surgeon Fuzzy Associative Memory (Tsfam): Model For Capturing Surgeon Perspective, Rachel Dzieran, Cihan H. Dagli, Robert J. Marley

Engineering Management and Systems Engineering Faculty Research & Creative Works

AI-driven healthcare decision-making is multi-faceted, requiring complex logic to adapt to evolving policies and societal demands. Effective change implementation by healthcare providers and multidisciplinary organ transplant teams depends on adaptive decision-making. The proposed Transplant Surgeon Fuzzy Associative Memory (TSFAM) model introduces a novel approach to Human-AI Teaming, keeping human expertise central while dynamically adjusting to changing requirements. TSFAM employs fuzzy logic to manage imperfect data and human ambiguity, integrating the transplant surgeon perspective with the AI deep learning decision-making tool, creating a resilient solution in this critical domain. By embedding adaptive capabilities into the architecture, TSFAM exemplifies the adaptability of …

Predictive Modeling For Optimal Gel Treatment Design In Brownfields Using Ensemble Machine Learning And Data Upsampling Via Generative Ai, Munqith Aldhaheri, Baojun Bai, Mingzhen Wei

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Efficiently designed gel treatments play a vital role in extending the lifespan of brownfields through rejuvenating oil production. Recently, a three-mode mathematical methodology named the VCR approach has been proposed for designing effective treatments. To optimize this approach, it is crucial to determine the appropriate design mode systematically rather than relying solely on the intuitive judgments of field operators. This study introduces an advanced methodology for predicting the optimal design type of gel treatments using 12 reservoir and production variables. The methodology integrates ensemble machine-learning (EML) models with historical data from 65 field projects across 11 countries (1985-2020). The Random …

Characterization And Leaching Feasibility Studies Of Copper Flue Dust For The Recovery Of Main And Trace Metals, Fardis Nakhaei, Marek Locmelis, Lana Alagha, Michael S. Moats, Carlos Eyzaguirre, Cory Smith

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Although copper smelter dust (CSD) is classified as hazardous waste, it also serves as a valuable secondary resource, offering potential for the recovery of critical elements. In this study, CSD samples were collected from the waste heat boiler (WHB) and electrostatic precipitator (ESP) units connected to the flash smelting furnace at a copper smelter. The representative samples were extensively characterized by particle size, and chemical and mineralogical analyses. Following sample characterization, leaching experiments were performed to evaluate the potential extraction of Cu, Fe, As, Zn, Pb, In, Ga, and Ge from the flue dusts. Distilled water, H2SO4, and HCl were …

Integration Of Physics-Informed Neural Networks And Transfer Learning For Rainfall Induced Landslide Forecasting, Shian Cao, Weibing Gong

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Rainfall-induced landslides are a significant geological hazard, causing severe economic losses and casualties. Accurate forecasting of these events is particularly challenging due to the complex interactions of spatial and temporal factors governing slope stability. The Iverson model, which uses the Richards equation to describe water infiltration in unsaturated soils, is a widely adopted framework for analyzing rainfall-induced landslides. However, its reliance on traditional numerical methods limits its scalability and efficiency, particularly for complex boundary conditions and transient behaviors near slope failure. To address these limitations, we propose a physics-informed neural network (PINN) enhanced with transfer learning (TL-PINN) to solve the …

Microwave Photonics-Assisted Interrogation Of Fiber-Optic Interferometric Sensors With Joint Frequency-Time Domain Analysis, Ruimin Jie, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Fiber-optic interferometers are widely used in localized sensing applications due to their compact size, high sensitivity, and immunity to electromagnetic interference. In this paper, we propose and experimentally demonstrate a novel interrogation scheme for fiber-optic interferometric sensors, utilizing microwave photonics (MWP) and joint frequency-time domain analysis. As a proof of concept, a miniature fiber in-line Fabry-Perot interferometer (FPI) is integrated with a microwave photonic single-passband filter, enhanced by a dispersion compensation module to improve sensing performance. By applying an inverse Fourier transform to the system's complex frequency response, the time-domain representation of the signal is obtained, translating spectral shifts of …

Fast Demodulation Of Ofdr-Based Distributed Sensing Based On Enhanced Buneman Frequency Estimation, Zhaopeng Zhang, Bo Liu, Xiao Liu, Caiyun Li, Osamah Alsalman, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Aiming at realizing high-efficiency distributed strain sensing through optical frequency domain reflectometry (OFDR), this paper introduces a fast demodulation algorithm to determine strain-induced spectral shifts from coarse Rayleigh backscattering (RBS) cross-correlation spectra. The proposed approach employs an enhanced Buneman frequency estimation (BFE) algorithm, enabling direct spectral shift analysis across coarse signals. By applying this algorithm, the need for dense interpolation in the conventional cross-correlation demodulation process - typically required for a finer spectral sampling interval but at the cost of demodulation efficiency - can be eliminated. Both theoretical analysis and experimental investigation reveal the equivalence of the BFE and conventional …

Miniaturized Wearable Biosensors For Continuous Health Monitoring Fabricated Using The Femtosecond Laser-Induced Graphene Surface And Encapsulated Traces And Electrodes, Homayoon Soleimani Dinani, Tatianna Reinbolt, Bohong Zhang, Ganggang Zhao, Rex E. Gerald, Zheng Yan, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Wearable sensors are increasingly being used as biosensors for health monitoring. Current wearable devices are large, heavy, invasive, skin irritants, or not continuous. Miniaturization was chosen to address these issues, using a femtosecond laser-conversion technique to fabricate miniaturized laser-induced graphene (LIG) sensor arrays on and encapsulated within a polyimide substrate. The femtosecond laser-converted conductive traces can have a size of 20 to 2 μm compared to the traditionally larger CO2 laser dimensions of around 300 to 100 μm. This marks a 93-98% decrease in trace size when using a femtosecond laser. This miniaturization allows for the ability to process temperature, …

Mapping Biomedical Ontology Terms To Ids: Effect Of Domain Prevalence On Prediction Accuracy, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

This study evaluates the ability of large language models (LLMs) to map biomedical ontology terms to their corresponding ontology IDs across the Human Phenotype Ontology (HPO), Gene Ontology (GO), and UniProtKB terminologies. Using counts of ontology IDs in the PubMed Central (PMC) dataset as a surrogate for their prevalence in the biomedical literature, we examined the relationship between ontology ID prevalence and mapping accuracy. Results indicate that ontology ID prevalence strongly predicts accurate mapping of HPO terms to HPO IDs, GO terms to GO IDs, and protein names to UniProtKB accession numbers. Higher prevalence of ontology IDs in the biomedical …

An Extendable Soft-Switched Step-Up Interleaved Converter Integrated With Voltage Multiplier Cells, Amir Hasan Babanezhad, Koosha Choobdari Omran, Reza Beiranvand, Pourya Shamsi

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a multiphase high step-up interleaved converter is introduced, which ensures low-input current ripple, low-component currents, and voltage stresses. The proposed circuit guarantees ZVS operation for power switches and ZCS operation for power diodes, which significantly reduce converter switching losses and EMI emission and improve its efficiency. Therefore, its passive components volume can be reduced by using high switching frequencies. In addition, the interleaved technique reduces input current ripple and input filter volume and provides high-power density. High-voltage gain and low-voltage stresses on the components are also achieved due to the integration of the converter structure with the …

Online Learning-Driven Human Intent Estimation And Control For Human-Robot Interaction, Irfan Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a novel Stackelberg-game theoretic multilayer-online learning framework for cooperative control of nonlinear Physical Human-Robot Interaction (pHRI), where the human is modeled as the leader guiding a robot follower. This hierarchical interaction is captured as a dynamic Stackelberg game, with the human's intention estimated in real-time through online multilayer neural networks (MNNs). We introduce SVD-based weight update laws for actor-critic MNNs, which approximate value functions and control inputs for both human and robot, eliminating the need for predefined basis functions. In this framework, the human objective is first inferred and used to guide the robot actions by shaping …

Improved Optimal Tracking Of Uncertain Nonlinear Discrete-Time Systems Using Experience Replay, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper addresses the infinite horizon optimal tracking control problem for partially uncertain control-affine nonlinear discrete-time (DT) systems, where the control input dynamics are known. Multi-layer critic and actor neural networks (MNNs) are utilized for online estimation of the infinite horizon value function and optimal control input. The NN weights are tuned online using a direct temporal difference error (TDE)-driven learning approach, which modifies the singular values of the gradient with respect to the NN weights to accelerate their convergence. The critic NN uses a novel experience replay technique to improve sample efficiency without introducing biased TDEs and guarantee the …

Multi-Model Safe Neuro-Optimal Output Tracking Control Of Autonomous Surface Vessels With Explainable Ai, Behzad Farzanegan, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a safety-aware deep reinforcement learning (DRL)-based trajectory tracking control of autonomous surface vessels (ASVs). A multilayer neural network (MNN) observer estimates the ASV's state and uncertain dynamics. By utilizing the estimate state vector from the observer, a safety-aware DRL-based optimal policy is formulated using control barrier function (CBF) and Karush-Kuhn-Tucker (KKT) conditions. An actor-critic MNN with singular value decomposition (SVD)-based update mitigates vanishing gradients. To enhance adaptability, an online safe lifelong learning (SLL) scheme counters catastrophic forgetting across varying ASV dynamics. The Shapley Additive Explanations (SHAP) method identifies key features influencing the control policy. Simulations on an …

Online Adaptive Optimal Tracking Control Of Uncertain Strict Feedback Discrete-Time Systems With Hardware Verification Using A Quadrotor Uav, Maxwell Geiger, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal tracking control problem for discrete time (DT) partially uncertain strict feedback systems with application to quadrotor UAVs. First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of tracking error dynamics. The optimal tracking control problem is solved using an augmented system approach, where a horizon of future reference trajectory points are used in the augmented state, as compared to using a single point. The internal dynamics of the original nonlinear strict feedback system and the transformed affine system in terms of error dynamics are …

Active Microwave-Thermographic Signal Reconstruction, Logan M. Wilcox, Emma T. Bohannon, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a coupled electromagnetic (EM) and thermographic nondestructive testing and evaluation (NDT&E) technique. AMT utilizes a radiating EM source (e.g., an antenna) that induces dielectric/magnetic heating on a specimen under test (SUT) which is subsequently spatiotemporally imaged with an infrared (IR) camera. As all antennas have spatial variation in their radiated power density, a nonuniform thermal excitation results within (or on the surface of) the SUT. This nonuniform heating causes uncertainty in defect detection and has the potential to lead to false positives and/or negatives. To this end, thermographic signal reconstruction (TSR), a well-established thermographic signal …