Engineering Commons^™

Enhancing Irs Localization Via Ml-Driven Aoa And Distance Estimation, Nikhila Kotlapara Surendran

Theses and Dissertations

Intelligent Reflecting Surfaces (IRSs) are transforming next-generation wireless networks by enabling dynamic control of the propagation environment for improved localization and security. This thesis advances Angle-of-Arrival (AoA) and distance estimation in IRS-assisted systems using a hybrid architecture with active sensing and passive reflecting elements. A modified MUSIC algorithm, optimized for near-field localization, decouples 2‑D AoA and 1‑D range estimation using a grid-and-peak pseudo-spectrum scan, achieving sub-degree AoA (0.003 rad) and sub-meter range (0.05 m) accuracy with over 100× lower complexity than classical 3D MUSIC.

The study further applies the algorithm to the DeepMIMO dataset (O1_28 scenario, 3.5 GHz) using …

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 …

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 …

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 …

Analytical Model Of The Ac-Ac Dab Converter In The Egam Framework, Arnold A. Fernandes, Kartikeya Jayadurga Prasad Veeramraju, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper develops an analytical model of the bidirectional AC-AC Dual Active Bridge (DAB) converter. The passive components of the AC-AC DAB are subject to grid, switching, and sideband harmonics. Thus, it is impossible to model via the conventional Generalized Average Method (GAM). It has been numerically shown that Extended GAM (EGAM) can be used to model the AC-AC DAB converter. In this paper, an analytical sixteenth order EGAM-model has been developed that considers only grid harmonics at the filter components and only sideband harmonics for the transformer leakage inductor. A closed-form expression is developed for the 2D convolution product. …

Active Microwave-Thermographic Signal Reconstruction With Adaptive Polynomial Regression, Logan M. Wilcox, Alexander Hook, 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). The inspection surface of the SUT is imaged with an infrared (IR) camera over the inspection time. As the thermal excitation originates from a spatially varying radiated power density, a nonuniform thermal excitation results within (or on the surface of) the SUT that is directly related to this power density. This nonuniform heating causes uncertainty in defect detection and has the potential to lead …

Distributed Sapphire Fiber Bragg Grating-Based Thermal Profiling Of Submerged Entry Nozzles, Farhan Mumtaz, Hanok W. Tekle, Bohong Zhang, Xiaodong Li, Sunday Abraham, Bryant Mathis, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This article focuses on the application of sapphire fiber Bragg gratings (FBGs) for instrumentation in submerged entry nozzles (SENs) within the steelmaking industry. The SEN is pivotal for transferring molten steel from a tundish to a mold, while preventing the infiltration of oxygen and nitrogen from the surrounding environment. Maintaining optimal flow conditions in the mold is crucial for ensuring casting process stability and maintaining high-quality steel. Sapphire FBG sensors have been instrumented in SENs to enable distributed thermal mapping for monitoring the health of the SEN. The optical sensor comprises three cascaded sapphire FBGs inscribed using femtosecond (FS) laser …

Ms-Yolo: Infrared Object Detection For Edge Deployment Via Mobilenetv4 And Slideloss, Jiali Zhang, Thomas S. White, Haoliang Zhang, Wenqing Hu, Donald C. Wunsch, Jian Liu

Mathematics and Statistics Faculty Research & Creative Works

Infrared imaging has emerged as a robust solution for urban object detection under low-light and adverse weather conditions, offering significant advantages over traditional visible-light cameras. However, challenges such as class imbalance, thermal noise, and computational constraints can significantly hinder model performance in practical settings. To address these issues, we evaluate multiple YOLO variants on the FLIR ADAS V2 dataset, ultimately selecting YOLOv8 as our baseline due to its balanced accuracy and efficiency. Building on this foundation, we present MS-YOLO (MobileNetv4 and SlideLoss based on YOLO), which replaces YOLOv8's CSPDarknet backbone with the more efficient MobileNetV4, reducing computational overhead by 1.5% …

Performance Evaluation And Multiphysics Process Modeling Of Carbon Fiber Reinforced Thermoset Composites Using Microwave And Autoclave, Nayan Pundhir, Patrick Schwartzkopf, K. Chandrashekhara, Logan Wilcox, Kristen M. Donnell, Jim Lua, Rui Li

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this study, IM7/Cycom 5320-1 unidirectional prepreg has been utilized to manufacture 16-layer laminated composites: a symmetric cross-ply ([0°/90°]4s) and a quasi-isotropic ([45°/90°/−45°/0°]2s) configuration. Microwave and autoclave curing processes have been employed to manufacture the laminated composites. The manufactured composite cure was assessed using differential scanning calorimetry (DSC). The quality and porosity of the microwave-cured parts were juxtaposed to those of autoclave-cured parts through optical microscopy and micro-computed tomography (micro-CT) scanning. Mechanical characterization of the microwave-cured panels was conducted using uniaxial tensile and flexural tests, with results juxtaposed to autoclave-cured samples. Experimental characterization revealed that the microwave-cured parts exhibited nearly …

The Effect Of Liquid Conductivity On A Helium Plasma Jet And The Hydrogen Peroxide Production, Edwin A. Oshin, M. Ziaur Rahman, Chunqi Jiang

Bioelectrics Publications

Understanding plasma-liquid interactions and the impact of the electrical conductivity (σ) of liquid on plasma is important for plasma applications in water treatment and medicine. Ultrapure water, phosphate-buffered saline (PBS) solution, biological media, and sodium chloride (NaCl) solutions at various concentrations were used in this study to provide a broad range of conductivity values ranging from 0.055 μS cm⁻¹ to 222 mS cm⁻¹. A helium atmospheric pressure plasma jet (APPJ) impinging on liquid was generated in ambient air using a hollow-needle electrode that was powered by 200 ns, 7 kV pulses at a pulse repetition frequency of …

Determining The Transient Electric Field And The Effect Of Pulse Repetition Frequency On The Field In A Repetitive 10-Ns Pulsed Discharge In A Quiescent Ch₄-Air Mixture, Chunqi Jiang

Bioelectrics Publications

The goal of this research is to understand the underlying physics enabled by nanosecond pulsed power in a discharge initiation and the following physicochemical processes that favor lean-fuel plasma ignition for combustion. The hypothesis of this project is that pulsed power waveforms such as the pulse repetition frequency (PRF), voltage amplitude, and dielectric surface alter the reduced electric field during the initiation of the discharge, resulting in different plasma properties, which will vary the physicochemical processes for efficient and selective radical productions. This is especially important for lean-burn combustion and reducing emission.

Ensemble Machine Learning Approaches For Bathymetry Estimation In Multi-Spectral Images, Kazi A. Islam, Omar Abdul-Hassan, Hongfang Zhang, Victoria Hill, Blake Schaeffer, Richard Zimmerman, Jiang Li

OES Faculty Publications

Traditional bathymetry measures require a large number of human hours, and many bathymetry records are obsolete or missing. Automated measures of bathymetry would reduce costs and increase accessibility for research and applications. In this paper, we optimized a recent machine learning model, named CatBoostOpt, to estimate bathymetry based on high-resolution WorldView-2 (WV-2) multi-spectral optical satellite images. CatBoostOpt was demonstrated across the Florida Big Bend coastline, where the model learned correlations between in situ sound Navigation and Ranging (Sonar) bathymetry measurements and the corresponding multi-spectral reflectance values in WV-2 images to map bathymetry. We evaluated three different feature transformations as inputs …

Optimizing Material Selection And Operational Conditions For Xhv Systems: Lessons From Aisi 1020 And 316l Comparative Studies, Aiman H. Al-Allaq, Md Abdullah Mamun, Matt Poelker, Abdelmageed Elmustafa

Mechanical & Aerospace Engineering Faculty Publications

In this study, AISI 1020 low-carbon steel was investigated as a cost-effective alternative to SS316L stainless steel for reaching extreme high vacuum (XHV) conditions. After being baked at 400°C, a vacuum chamber made of low-carbon steel material exhibited an outgassing rate approximately 2000 times smaller than a similar chamber made of stainless steel. Its activation energy for hydrogen diffusion (27 kJ/mol) is less than half that of stainless steel (60.3 kJ/mol), indicating more efficient hydrogen removal during bakeout. MolFlow+ simulations supported the experimental data and demonstrated the importance of system geometry optimization and minimizing stainless steel content for achieving optimal …

Revealing Spatiotemporal Neural Activation Patterns In Electrocorticography Recordings Of Human Speech Production By Mutual Information, Julio Kovacs, Dean Krusienski, Minu Maninder, Willy Wriggers

Mechanical & Aerospace Engineering Faculty Publications

Background

Spatiotemporal mapping of neural activity during continuous speech production has been traditionally approached using correlation coefficient (CC) analysis between cortical signals and speech recordings. A prior study employed this approach using electrocorticography (ECoG) data from participants who underwent invasive intracranial monitoring for epilepsy. However, CC cannot detect nonlinear relationships and is dominated by the correspondence between periods of silence and of non-silence.

New Method

We introduce the mutual information (MI) measure, which can capture both linear and nonlinear dependencies. We validated CC and MI on the sub-second spatiotemporal brain activity recorded during continuous speech tasks. To refine the results, …

Optimal Manipulation Motion Action Planner Enabled By Physics Informed Neural Networks, Jonathon E. Slightam, Logan E. Beaver

Mechanical & Aerospace Engineering Faculty Publications

Autonomous robotic manipulation in unstructured environments faces many challenges and is hindered by capabilities that bridge the gap between perception and acting on the world. Action plans that are centric to object motion rather than end-of-arm tooling behavior may aid this. This paper presents an autonomous action planner for a feedback linearizeable system comprised of three base motions that can be leveraged on their own or in combination to give custom motion plans. The optimization routine for the three different types of motion are presented, which are integrated into physics informed neural networks. A component of this is the autonomy …

A Large Electroencephalogram Database Of Freewill Reaching And Grasping Tasks For Brain Machine Interfaces, Bhoj Raj Thapa, John Boggess, Jihye Bae

Electrical and Computer Engineering Faculty Publications

Brain machine interfaces (BMIs) offer great potential to improve the quality of life for individuals with neurological disorders or severe motor impairments. Among various neural recording modalities, electroencephalogram (EEG) is particularly favorable for BMIs due to its noninvasive nature, portability, and high temporal resolution. Existing EEG datasets for BMIs are often limited to experimental settings that fail to address subjects’ freewill in decision making. We present a large EEG dataset, containing a total of 6808 trials, recorded from 23 healthy young adults (eight females and 15 males with an age range from 18 to 24 years) while performing reaching and …

Axial Flux Permanent Magnet Generators For Direct-Drive Wind Turbines - Review And Optimal Design Studies, Matin Vatani, Ali Mohammadi, Donovin D. Lewis, John F. Eastham, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents a comprehensive analysis of the feasibility, cost, and electromagnetic performance of five distinct types of axial flux permanent magnet (AFPM) generators designed for direct-drive wind turbines. The generator configurations investigated include a single-sided AFPM generator with a surface-mounted PM rotor (AFPMG), a double-sided AFPM generator featuring PMs on the stator and a reluctance rotor (AFPMG-RR), a coreless stator AFPM generator with surface PMs (CAFPMG-SPM), and a coreless stator AFPM generator with a Halbach PM array rotor (CAFPMG-Hal). Each generator’s operating principles and configurations are thoroughly explained and compared. Large-scale multi-objective design optimizations were conducted on each type, …

Review Of Coreless Axial Flux Permanent Magnet Machines With Applications Including Electric Aircraft Propulsion, Matin Vatani, Donovin D. Lewis, John F. Eastham, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Axial flux permanent magnet (AFPM) machines with entirely or stator coreless configurations offer significant advantages, including low rotational losses, the absence of cogging torque, minimal torque ripple, and the potential for high specific power density. Advances in permanent magnet (PM) technology and cooling techniques have enabled fully coreless AFPM machines to achieve high magnetic and current loadings without core saturation, making them suitable for high performance applications like electric aircraft propulsion. This paper reviews recent advancements in coreless AFPM machines, tracing their historical and chronological development. Various topologies, including single- and double-sided and multi-disk designs, are examined to identify the …

Speed Variation Based Power Regulation Concept For Dynamic Wireless Charging, Donovin D. Lewis, Sudarshan T. Harave, Omer Onar, Mostak Mohammad, Veda Prakash Galigekere, Gui-Jia Su, Dan Ionel

Electrical and Computer Engineering Graduate Research

On-road wireless charging of electric vehicles (EVs) in-motion could potentially reduce range anxiety or battery size with wide-spread deployment. The planning and implementation of such systems are greatly complicated due to their susceptibility to load variation inherent to traffic flow. This paper proposes a method for derisking the potential for traffic slowdowns by compensating for reduced vehicle speed and investigates how implementation may affect system performance. A load modeling case study is presented at 200kW for a mile of high-speed roadway employing speed-based power regulation with results indicating average power usage and maximum car hosting capability can be reduced by …

Fault-Tolerant High-Power Two-Phase Coreless Afpm Motor-Drive System Concept, Yaser Chulaee, Ali Mohammadi, Matin Vatani, Aaron M. Cramer, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper proposes a fault-tolerant, high-power two-phase coreless axial flux permanent magnet (AFPM) motor drive system concept. Initially, the performance of a two-phase variant of the coreless AFPM machine is compared with that of its three-phase counterpart using both 3D finite element analysis (FEA) and experiments. Thanks to the intrinsic unique features of coreless AFPM machines, the analysis of the results demonstrates that the two-phase configuration has comparable power density (kW/kg) and efficiency. In terms of fault tolerance, the two-phase configuration exhibits superior performance, as the mutual inductance between phases is zero, resulting in an electric machine with magnetically decoupled …

Two-Level Multi-Objective Design Optimization Including Torque Ripple Minimization For Stator Excited Synchronous And Flux Switching Machines, Ali Mohammadi, Oluwaseun A. Badewa, Yaser Chulaee, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Electric machine performance can be enhanced through torque ripple mitigation, which reduces mechanical vibrations and improves system stability and operation. This paper proposes a novel two-level optimization method for synchronous flux-switching and hybrid excitation machines, featuring an innovative multi-point spline shaping approach for torque ripple minimization. The study employs experimentally validated models based on a prototype with a similar topology. The optimization process is implemented on two distinct designs: a 20-pole inner rotor PM-excited stator machine and a 28-pole outer rotor DC-excited stator machine. Analysis results demonstrate that the proposed innovative method significantly reduces torque ripple in both configurations. Force …

Electromagnetic Design Characterization Of Synchronous Machines With Flux Switching Effect Employing Reluctance Rotors And Stators With Pms And Ac Concentrated Coils, Oluwaseun A. Badewa, Ali Mohammadi, Donovin D. Lewis, Somasundaram Essakiappan, Madhav Manjrekar, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper introduces an innovative design for a synchronous electric motor that has phase coils and permanent magnets (PM) embedded in the stator. The electric machine contains both concentrated winded phase coils in dedicated slots and spoke-type permanent magnets solely in the stator. The spoke-type magnet arrangement achieves a high flux intensity even with low remanence non-rare earth permanent magnets. As the rotor has no active electromagnetic components, the risk for demagnetization is reduced and advanced cooling applied to the stator can enable high-speed operation. The principle of operation and polarity of the motor are investigated with a unique approach …

A Framework For Fair And Trustworthy Multimodal Video Anomaly Detection: Fusion, Dataset Quality Auditing, Explainability, And Fairness, Omeshamisu Judith Anigala

Electronic Theses and Dissertations

No abstract provided.

St-Hybrid: Dynamic Graph Learning With Multi-Scale Spatio-Temporal Attention For Traffic Forecasting, Dhe Yeong Ewaza Tchalla

Electronic Theses and Dissertations

Accurate short-term traffic forecasting is central to modern Intelligent Transportation Systems, supporting route guidance, adaptive signal control, and incident response. Yet producing reliable predictions remains difficult because traffic is highly non-stationary. The relationships among roadway sensors shift during congestion, incidents, weather changes, or fluctuations in demand, and the temporal structure of traffic spans several scales from abrupt minute-level variations to broader daily and weekly rhythms. Models that rely on fixed spatial graphs or a single temporal scale tend to miss these evolving and layered dependencies. This thesis addresses these challenges by developing a graph-learning framework that adapts to changing traffic …

Power Saving In Open Ran By Using Advanced Cpu Scheduling Algorithm, Saish Urumkar, Sachin Sharma

Conference papers

Open RAN is an emerging wireless technology that is gaining significant attention for its potential to enable flexi- ble, cost-efficient, and interoperable networks. Reducing power utilization in Open RAN, particularly for 5G base stations (gNodeBs) deployed in remote areas, remains a critical challenge due to limited power availability. In our previous work, we developed a CPU scheduling algorithm that optimized core allocation based on load conditions, reducing power utilization for gNodeB in a virtualized Open RAN environment. Extending our previous work, this paper introduces an advanced CPU scheduling for Open RAN designed to reduce power utilization in real hardware Open …

A Comprehensive Review Of Piezoelectric Pvdf Polymer Fabrications And Characteristics, Nadia Ahbab, Sidra Naz, Tian-Bing Xu, Shihai Zhang

Mechanical & Aerospace Engineering Faculty Publications

Polyvinylidene fluoride (PVDF) polymer films, renowned for their exceptional piezoelectric, pyroelectric, and ferroelectric properties, offer a versatile platform for the development of cutting-edge micro-scale functional devices, enabling innovative applications ranging from energy harvesting and sensing to medical diagnostics and actuation. This paper presents an in-depth review of the material properties, fabrication methodologies, and characterization of PVDF films. Initially, a comprehensive description of the physical, mechanical, chemical, thermal, electrical, and electromechanical properties is provided. The unique combination of piezoelectric, pyroelectric, and ferroelectric properties, coupled with its excellent chemical resistance and mechanical strength, makes PVDF a highly valuable material for a wide …

Ieee 802.11n And Ieee 802.11ax Networks Under Various Propagation Models, Jun Peng

Electrical and Computer Engineering Faculty Publications

IEEE 802.11n networks are the first generation of Wi-Fi networks to reach data rates of hundreds of megabits per second. They are also the first to use MIMO technologies in Wi-Fi networks. They can operate in both 2.4 GHz and 5 GHz frequency bands and use 20 or 40 MHz channel width. Similarly, IEEE 802.11ax networks can operate in both 2.4 GHz and 5.0 GHz frequency bands and use 20, 40, 80, or 160 MHz channel width. For channel access, IEEE 802.11ax networks use CSMA/CA, multi-user MIMO (MU-MIMO), and OFDMA. They can reach data rates of multiple gigabits per second. …

Powersynth 2: Automated Power Electronics Physical Design Synthesis With Custom And Heterogeneous Components, Mehran Sanjabiasasi, Alan H. Mantooth, Yarui Peng

Electrical Engineering and Computer Science Faculty Publications and Presentations

Electronics Design Automation (EDA) has shown significant importance in the power electronics industry. As power electronic circuits become more complex, the traditional trial-and-error approach in physical design becomes less effective and time-consuming. Novel packaging technologies and intelligent physical design automation solutions are crucial to overcome these challenges and produce reliable solutions. PowerSynth 2 is an EDA tool for generating and optimizing power module layouts. To extend the layout synthesis capability beyond power modules, the layout engine needs to consider various custom components such as capacitors, inductors, and gate drivers. This research presents a novel framework for the layout synthesis process …

Demonstrating The Impact Of Cpu Scheduling On Power Consumption In Virtualized Open Ran, Saish Urumkar, Sachin Sharma

Conference papers

Open RAN (Open Radio Access Network) is a next- generation wireless network gaining significant research interest globally due to its potential to provide a cost-efficient and scalable solution for growing network demands. Energy efficiency is an important area of focus in Open RAN deployments, as reducing power consumption while maintaining network performance is essential for sustainable wireless communication. This paper demonstrates the impact of CPU (Central Processing Unit) scheduling process priorities on power consumption and network performance in an Open RAN NodeB deployed on a testbed in the USA. The experimental results are demonstrated using two scenarios: (1) CPU Priority-Based …