Digital Commons Network^™

Optimization Of Fire Emergency Preparedness In Underground Mining Environments: An Agent-Based Evacuation Approach, Oluwafemi Babatunde Salami

Doctoral Dissertations

"Underground mining environments present a complex interplay of thermal and non-thermal hazards, with fires constituting a significant risk due to the release of heat smoke from incomplete combustion. The propagation of these hazards through the ventilation networks underscores the critical need for understanding fire scenarios and their interaction with the underground environment. Existing knowledge regarding past mine fire disasters, and quantification of associated hazards and risks are insufficient for optimizing emergency evacuation strategies in the event of an underground fire emergency.

This research endeavors to bridge this gap by developing advanced quantitative risk assessment and evacuation models tailored specifically for …

In Situ Infrared Thermographic Inspection In Additive Manufacturing, Tao Liu

Doctoral Dissertations

"Laser Powder Bed Fusion (LPBF) is a key technique in metal additive manufacturing and has undergone extensive research over the past few decades. It enables the fabrication of complex geometries directly from digital design models. The solidification process in LPBF is heavily influenced by the characteristics of the powder layer, including its thickness and thermal transport properties. Additionally, the performance of the printed part is impacted by the temperature history during solidification and the final residual stress field. While these topics have been the focus of many studies, almost all research has concentrated on ex-situ measurement and testing. These ex-situ …

Topography Of The 410 And 660 Km Discontinuities Beneath The Tibetan Plateau And Adjacent Areas, Zexin Miao

Doctoral Dissertations

"The Tibetan Plateau represents the ongoing geotectonic aftermath of a continental collision initiated approximately 65 million years ago. Despite numerous seismological studies, controversies remain regarding the structure, evolution, and dynamics of the crust and mantle beneath Tibetan Plateau. In this study, we used teleseismic broadband data to investigate the topography of the mantle transition zone (MTZ) discontinuities. A total of ~655,000 receiver functions from 735 stations was utilized to image the 410 and 660 km discontinuities bordering the MTZ. Combining the observed and velocity corrected results, several areas in the central Tibet exhibit a typical d410 and an anomalously deep …

Critical Behavior And Dynamics Of The Superfluid-Mott Glass Transition, Jack Russell Crewse

Doctoral Dissertations

This work studies the effects of disorder on the thermodynamic critical behavior and dynamical properties of the superfluid-Mott glass quantum phase transition. After a brief introduction covering relevant fundamentals, we present the dissertation in the form of four separate but related publications. In the first two publications, we calculate the thermodynamic critical exponents of the superfluid-Mott glass quantum phase transition in both two and three spatial dimensions. The undiluted transition exhibits critical exponents that violate the Harris criterion, and thus the critical behavior is expected to change upon introducing disorder. We confirm this behavior via Monte Carlo simulation of a …

High-Resolution Spectroscopy Of Interstellar Lines And Comets, Chemeda Tadese Ejeta

Doctoral Dissertations

"The study of interstellar molecules such as CO is crucial because interstellar ices in the core of a pre-solar molecular cloud provide the starting point for volatile evolution in the protoplanetary disk. A record of the initial volatile composition of the protoplanetary disk can be obtained from the study of the chemical composition of cometary nuclei. Because of their long residence in the Oort cloud and infrequent passage through the inner solar system, long-period comets are one of the most primitive bodies in our solar system that can tell us about the composition of the early solar system. High-resolution infrared …

Adversarial Transferability And Generalization In Robust Deep Learning, Tao Wu

Doctoral Dissertations

Despite its remarkable achievements across a multitude of benchmark tasks, deep learning (DL) models exhibit significant fragility to adversarial examples, i.e., subtle modifications applied to inputs during testing yet effective in misleading DL models. These meticulously crafted perturbations possess the remarkable property of transferability: an adversarial example that effectively fools one model often retains its effectiveness against another model, even if the two models were trained independently. This research delves into the characteristics influencing the transferability of adversarial examples from three distinct and complementary perspectives: data, model, and optimization. Firstly, from the data perspective, we propose a new method of …

Deep Reinforcement Learning Based Strategies For Inverter Dominated Microgrids, Oroghene Oboreh-Snapps

Doctoral Dissertations

The integration of inverter-based distributed generators (IBDGs) in modern power systems has ushered in a new era of renewable energy utilization, prompting the rise of Microgrid (MG) architectures. Nevertheless, as IBDG penetration increases, a host of challenges surface. Foremost among these challenges are issues related to frequency stability stemming from the inherent lack of inertia in IBDGs, and inaccurate sharing of reactive and active power, particularly evident in parallel IBDG networks with mismatched feeder impedance. This research presents novel solutions to these challenges by adopting deep reinforcement learning (DRL), specifically, the twin delayed deep deterministic policy gradient (TD3) algorithm, to …

Crystal Structure Prediction Of Metal Chalcogenides, Qi Zhang

Doctoral Dissertations

A novel crystal structure prediction (CSP) method has been developed to predict energetically favorable (stable) structures based on targeted chemical compositions. It leverages the structural characteristics of recurring motifs featured in many crystals and symmetry restrictions from space groups to effectively lower the degrees of freedom of a system when conducting CSP simulations. The proposed method is applied to predicting low-energy structures of two metal chalcogenide systems: Li₃PS₄ and Na₆Ge₂Se₆. Both systems feature rigid bodies in their structures as building blocks, making them particularly suited to the proposed method. The validity …

High Viscosity Friction Reducer Evaluation At High Temperature And High Tds Environments, Ghith Ali Ahmed Biheri

Doctoral Dissertations

"In unconventional reservoirs, proppant transport during hydraulic fracturing treatments could be successful when the proppant is placed further within the reservoir's fracture networks. This could increase the reservoir formation conductivities and improve the productivity of the wells. This job of improving the reservoir conductivity by distributing and transporting proppant can be conducted by reliable fracture fluids with excellent fluid rheology (e.g., viscosity and elasticity). However, several challenges, including the high temperatures and the presence of high TDS in produced water, may limit the capability of fracture fluids to transport proppant. Additionally, the use of fracture fluid has raised fears regarding …

Adaptive Critic Optimal Control Of An Uncertain Robot Manipulator With Applications, Ravi Prakash, Laxmidhar Behera, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Realistic manipulation tasks involve a prolonged sequence of motor skills in varying control environments consisting of uncertain robot dynamic models and end-effector payloads. To address these challenges, this article proposes an adaptive critic (AC)-based basis function neural network (BFNN) optimal controller. Using a single neural network (NN) with a basis function, the proposed optimal controller simultaneously learns task-related optimal cost function, robot internal dynamics, and optimal control law. This is achieved through the development of a novel BFNN tuning law using closed-loop system stability. Therefore, the proposed optimal controller provides real-time, implementable, cost-effective control solutions for practical robotic tasks. The …

Towards Explainability Of Dimension Reduction Plots Of Unsupervised Learning Model Outcomes, Tony E.Astuhuaman Davila, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

Dimension reduction methods are used to visualize the output of unsupervised learning models when applied to complex data. These techniques improve interpretability by transforming a high-dimension space to a lower-dimension space (usually 2D or 3D). The results are typically viewed as 2D scatter plots, and class centroids may be added to increase interpretability. Although useful, the relationship of these class centroids to the underlying feature space remains opaque. The innovative aspect of this work is to create a strong link between the dimension-reduced space and the underlying high-dimension feature space by adding selected feature centroids to the 2D scatter plots. …

Evaluation Of Transfer Learning Models On Traumatic Brain Injury Severity Classification, Ngoc Do, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

After traumatic brain injury (TBI), clinicians use the Glasgow Coma Scale (GCS) to classify patients by severity and radiologists use the Rotterdam score and the Marshall score to classify CT scans by severity. This work investigates a viable efficient low-cost transfer learning model to use MRI images to predict GCS, Rotterdam, and Marshall severity class after TBI. The enhanced transfer learning model architecture integrates multiple fine-tuning steps in which a few layers of the pre-trained model is unfrozen in each iteration so that the neural network is able to learn layer by layer further aspects of the image for better …

Mechanisms For Unwanted Magnetic Field Coupling To A Shielded Magnetic Near-Field Probe, Xin Yan, Wei Zhang, Sajjad Sadeghi, Mehdi Gholizadeh, David J. Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Unwanted field coupling is a major concern when using magnetic near-field probes for high-frequency scanning. The unwanted coupling of the tangential electric field to a tangential magnetic field probe has been studied extensively. This article shows a second unwanted coupling mechanism: coupling from a vertical magnetic field. The standing wave of a shorted pure TEM microstrip in air is utilized to separate the magnetic and electric field coupling. Simulations show that the eddy currents induced within the probe by the vertical magnetic field couple inductively to the pickup loop if the layer stack up is not symmetric. The unwanted magnetic …

Virtual Inertia Scheduling (Vis) For Microgrids With Static And Dynamic Security Constraints, Buxin She, Fangxing Li, Jinning Wang, Hantao Cui, Xiaofei Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Microgrids feature a high penetration of inverter-interfaced distributed energy resources (DERs). The low inertia characteristic and fast dynamics of DERs pose challenges to conventional decoupled static economic operation and dynamic control design within microgrids. Hence, this paper proposed virtual inertia scheduling (VIS) for microgrids, aiming to ensure both economy and security. First, a unified framework for device-level control and grid-level operation is introduced, with VIS serving as a key application to address low inertia issues. VIS actively harnesses the controllability and flexibility of DERs to effectively manage microgrid inertia. It updates the conventional economic operation framework by incorporating the virtual …

Coupling-Informed Data-Driven Scheme For Joint Angle And Frequency Estimation In Uniform Linear Array With Mutual Coupling Present, Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Peifeng Ma, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel coupling-informed data-driven algorithm tailored for the concurrent estimation of frequency and angle within a uniform linear array (ULA), while addressing the complicating influence of mutual coupling. Leveraging the hybrid dynamic mode decomposition (DMD) methodology, termed as averaged DMD, we incorporate moving average techniques to achieve effective denoising. The averaged DMD further decomposes the received signal into eigenvalues and corresponding eigenvectors. The frequency information is derived from the eigenvalues and the corresponding eigenvectors represent the steering vectors of sources. Subsequently, mutual coupling is informed into the calibration of the steering vector for each source. Specifically, the …

Design Of The Tm010 Mode Cylindrical Cavity Resonator For Pcb Dielectric Characterization, Reza Asadi, Chaofeng Li, Seyedmehdi Mousavi, Seyed Moastafa Mousavi, Reza Vahdani, Xiaoning Ye, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the study of the TM₀₁₀ mode cylindrical resonator, which can be used for printed circuit board (PCB) material properties extraction, e.g., the dielectric constant (Dk) and the loss tangent (Df) extraction. The theoretical formulas of the resonance frequency and Q-factor of the resonator are presented. In real measurement, the TM₀₁₀ mode cylindrical cavity resonator needs to be excited by the probe. The study emphasizes the impact of probe orientation, location, and field distribution on the accuracy of material property extraction. The relationship between cavity dimensions and resonance frequency is explored, highlighting the influence of cavity …

A Tensor-Based Data-Driven Approach For Multidimensional Harmonic Retrieval And Its Application For Mimo Channel Sounding., Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Ping Yuan, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

In wireless channel sounding, accurately estimating multiple parameters within a multipath signal, such as azimuth, elevation, Doppler shift, and delay, necessitates addressing the challenges posed by the multidimensional harmonic retrieval (MHR) problem. To overcome these complexities, we propose a framework based on high-order dynamic mode decomposition (HODMD) that designed for robustly estimating frequencies of interest from high-dimensional sinusoidal signals, particularly in additive white Gaussian noise conditions. The HODMD approach, a hybrid algorithm amalgamating high-order singular value decomposition (HOSVD) and dynamic mode decomposition (DMD), operates by initially decomposing observed tensorial data into a core tensor and R mode matrices through HOSVD. …

Modeling Of Power Distrubition Network (Pdn) Noise Coupling Induced Clock Phase Noise, Zhekun Peng, Junyong Park, Chaofeng Li, Joey Stecher, Srinivas Venkataraman, Xu Wang, Granthana Rangaswamy, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

Phase noise analysis is important to clock design. Noise sources of spurs shown on the phase noise result are challenging to find out due to the unknown source locations and coupling mechanisms. Noise from power distribution network (PDN) is one of the most troublesome sources. A behavioral modeling methodology is proposed to simulate the clock phase noise induced by PDN noise coupling for two different mechanisms: PDN-to-clock additive coupling and PDN-to-PDN up-conversion modulation. The thermal noise and 1/f flicker noise are simplified to provide a straightforward view of spur level. The model can be applied to both single-ended clock and …

Cascading Of 2d And 3d Simulations Of Asic Substrate Interconnect Up To 100 Ghz, Zhekun Peng, Junyong Park, Sathvika Bandi, Santosh Pappu, Srinivas Venkataraman, Xu Wang, Granthana Ranzaswamy, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

A method of cascading 3D models and 2D models to model the full channel of ASIC package substrate interconnects is proposed, showing good match to full-wave results in S-parameter and TDR up to 100 GHz.

Enhancing Diversity And Inclusion In Computer Science Undergraduate Programs: The Role Of Admissions, Ouldooz Baghban Karimi, Giulia Toti, Mirela Gutica, Rebecca Robinson, Lisa Zhang, James Paterson, Peggy Lindner, Michael O'Dea

Engineering Management and Systems Engineering Faculty Research & Creative Works

Despite continued efforts to further the participation of women in Computer Science (CS), progress has been limited during the past decades. Recent efforts have been focused on recruitment and retention, with a notable gap in exploring the impact of admissions processes on diversity and inclusion. Through an extensive literature review, contextual analysis of public admissions data from 40 universities across four regions around the world, and qualitative and quantitative analysis on surveys and interviews, we explored the role of admissions in enhancing diversity and inclusion in CS undergraduate programs. Our findings highlight the role of financials, the possible positive effects …

Resonance Raman Spectra And Excited State Properties Of Methyl Viologen And Its Radical Cation From Time-Dependent Density Functional Theory, Umut Ozuguzel, Adelia J.A. Aquino, Reed Nieman, Shelley D. Minteer, Carol Korzeniewski

Chemistry Faculty Research & Creative Works

Time-dependent density functional theory (TDDFT) was applied to gain insights into the electronic and vibrational spectroscopic properties of an important electron transport mediator, methyl viologen (MV2+). an organic dication, MV2+ has numerous applications in electrochemistry that include energy conversion and storage, environmental remediation, and chemical sensing and electrosynthesis. MV2+ is easily reduced by a single electron transfer to form a radical cation species (MV•+), which has an intense UV–visible absorption near 600 nm. the redox properties of the MV2+/MV•+ couple and light-sensitivity of MV•+ have made the system appealing for photo-electrochemical energy conversion (e.g., solar hydrogen generation from water) and …

Microwave-Photonic Vernier Effect Enabled High-Sensitivity Fiber Bragg Grating Sensors For Point-Wise And Quasi-Distributed Sensing, Chen Zhu, Osamah Alsalman, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This paper reports a sensitivity-improved fiber Bragg grating (FBG) sensor system based on microwave-photonic interferometry and the Vernier effect. an incoherent microwave photonics system based on a broadband light source is employed to interrogate the FBG sensor using the wavelength-to-delay mapping technique combined with interferometry. Specifically, the sensing FBG together with a reference FBG is used to construct a microwave photonics Michelson interferometer (MI). Changes in the Bragg wavelength of the sensing FBG subject to external perturbations are encoded into the spectral shifts of the microwave interferogram of the MI. a virtual interferometer is then generated from the sensing MI …

Many-Body Quantum Chaos In Stroboscopically-Driven Cold Atoms, Ceren B. Dağ, Simeon I. Mistakidis, Amos Chan, H. R. Sadeghpour

Physics Faculty Research & Creative Works

In Quantum Chaotic Systems, The Spectral Form Factor (SFF), Defined As The Fourier Transform Of Two-Level Spectral Correlation Function, Is Known To Follow Random Matrix Theory (RMT), Namely A 'ramp' Followed By A 'plateau' In Late Times. Recently, A Generic Early-Time Deviation From RMT, So-Called The 'bump', Was Shown To Exist In Random Quantum Circuits As Toy Models For Many-Body Quantum Systems. We Demonstrate The Existence Of 'bump-Ramp-Plateau' Behavior In The SFF For A Number Of Paradigmatic And Stroboscopically-Driven 1D Cold-Atom Models: Spinless And Spin-1/2 Bose-Hubbard Models, And Nonintegrable Spin-1 Condensate With Contact Or Dipolar Interactions. We Find That The …

An Optimized Search For Dark Matter In The Galactic Halo With Hawc, A. Albert, R. Alfaro, C. Alvarez, J. C. Arteaga-Velázquez, D. Avila Rojas, H. A. Ayala Solares, E. Belmont-Moreno, K. S. Caballero-Mora, T. Capistrán, A. Carramiñana, S. Casanova, O. Chaparro-Amaro, U. Cotti, J. Cotzomi, E. De La Fuente, R. Diaz Hernandez, B. L. Dingus, M. A. Duvernois, M. Durocher, J. C. Diaz-Velez, C. Espinoza, M. M. Gonzalez, J. A. Goodman, J. P. Harding, D. Huang, F. Hueyotl-Zahuantitla, A. Iriarte, V. Joshi, G. J. Kunde, J. Lee, H. Leon Vargas, J. T. Linneman, A. L. Longinotti, G. Luis-Raya, J. Lundeen, K. Malone, O. Martinez, J. Martinez-Castro, J. A. Matthews, E. Moreno, M. Mostafa, A. Nayerhoda, L. Nellen, A. Peisker, E. G. Perez-Perez, C. D. Rho, D. Rosa-Gonzalez, H. Salazar, D. Salazar-Gallegos, A. Sandoval, J. Serna-Franco, R. W. Springer, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Urena-Mena, L. Villasenor, Xiaojie Wang, H. Zhou, C. De Leon

Physics Faculty Research & Creative Works

The Galactic Halo is a key target for indirect dark matter detection. The High-Altitude Water Cherenkov (HAWC) observatory is a high-energy (∼300 GeV to >100 TeV) gamma-ray detector located in central Mexico. HAWC operates via the water Cherenkov technique and has both a wide field of view of ∼ 2 sr and a >95% duty cycle, making it ideal for analyses of highly extended sources. We made use of these properties of HAWC, and a new background-estimation technique optimized for extended sources to probe a large region of the Galactic Halo for dark matter signals. With this approach, we set …

Insight Into The Binding Of Argon To Cyclic Water Clusters From Symmetry-Adapted Perturbation Theory, Carly A. Rock, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

This work systematically examines the interactions between a single argon atom and the edges and faces of cyclic H (Formula presented.) O clusters containing three–five water molecules (Ar(H (Formula presented.) O) (Formula presented.)). Full geometry optimizations and subsequent harmonic vibrational frequency computations were performed using MP2 with a triple- (Formula presented.) correlation consistent basis set augmented with diffuse functions on the heavy atoms (cc-pVTZ for H and aug-cc-pVTZ for O and Ar; denoted as haTZ). Optimized structures and harmonic vibrational frequencies were also obtained with the two-body–many-body (2b:Mb) and three-body–many-body (3b:Mb) techniques; here, high-level CCSD(T) computations capture up through the …

Mesenchymal Stem Cells In The Treatment Of Osteogenesis Imperfecta, Erica Lang, Julie A. Semon

Biological Sciences Faculty Research & Creative Works

Osteogenesis Imperfecta (OI) is a Disease Caused by Mutations in Different Genes Resulting in Mild, Severe, or Lethal Forms. with No Cure, Researchers Have Investigated the Use of Cell Therapy to Correct the Underlying Molecular Defects of OI. Mesenchymal Stem Cells (MSCs) Are of Particular Interest Because of their Differentiation Capacity, Immunomodulatory Effects, and their Ability to Migrate to Sites of Damage. MSCs Can Be Isolated from Different Sources, Expanded in Culture, and Have Been Shown to Be Safe in Numerous Clinical Applications. This Review Summarizes the Preclinical and Clinical Studies of MSCs in the Treatment of OI. Altogether, the …

Space-Time-Frequency Characterization In Electromagnetic Near-Field Scanning: A Data-Driven Approach, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Near-field scanning has become a widely used tool for diagnosing electromagnetic compatibility and electromagnetic interference issues. However, the transient signal of the device under test often contains multiple frequency bands and exhibits nonstationarity, which poses a challenge for near-field scanning analysis. To address this issue, this article presents a method for analyzing time-resolved near-field radiation based on multiresolution dynamic mode decomposition (MRDMD). The MRDMD approach recursively and hierarchically applies the traditional dynamic mode decomposition (DMD) method. The distribution of DMD eigenvalues determines the slow and fast modes in each level's decomposition, where the slow modes are preserved, and the fast …

Data-Driven Scheme For Joint Estimation Of Direction-Of-Arrival And Frequency With Uniform Linear Array, Yanming Zhang, Lijun Jiang, Hsi Tseng Chou

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents a two-step dynamic mode decomposition (TSDMD) approach to estimate the direction of arrival (DOA) and frequency for multiple narrow-band sources with single uniform linear array (ULA). The proposed algorithm first decomposes the receiving spatial-temporal data into temporal dynamic modes and corresponding spatial spectrum that yields the DOA information. Then the decomposed temporal dynamic modes are analyzed via the augmented DMD to retrieve the frequency information. The estimated DOAs and frequencies are automatically paired without the extra computational cost with such a temporal-spectral correlated decomposition scheme. Also, the obtained spatial spectrum distribution implies the actual number of the …

Bioelectrocatalytic Synthesis: Concepts And Applications, Dylan G. Boucher, Emily Carroll, Zachary A. Nguyen, Rohit G. Jadhav, Olja Simoska, Kevin Beaver, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Bio electrocatalytic synthesis is the conversion of electrical energy into value-added products using biocatalysts. These methods merge the specificity and selectivity of biocatalysis and energy-related electrocatalysis to address challenges in the sustainable synthesis of pharmaceuticals, commodity chemicals, fuels, feedstocks and fertilizers. However, the specialized experimental setups and domain knowledge for bio electrocatalysis pose a significant barrier to adoption. This review introduces key concepts of bioelectrosynthetic systems. We provide a tutorial on the methods of biocatalyst utilization, the setup of bioelectrosynthetic cells, and the analytical methods for assessing bio electrocatalysts. Key applications of bio electrosynthesis in ammonia production and small-molecule synthesis …

A Parallel Algorithm For Updating A Multi-Objective Shortest Path In Large Dynamic Networks, Arindam Khanda, S. M. Shovan, Sajal K. Das

Computer Science Faculty Research & Creative Works

In dynamic networks, where continuous topological changes are prevalent, it becomes paramount to find and update different graph properties without the computational burden of recalculating from the ground up. However finding or updating a multi-objective shortest path (MOSP) in such a network is challenging, as it involves simultaneously optimizing multiple (conflicting) objectives. In light of this, our paper focuses on shortest path search and proposes parallel algorithms tailored specifically for large incremental graphs. We first present an efficient algorithm that updates the single-objective shortest path (SOSP) whenever a new set of edges are introduced. Leveraging this SOSP update algorithm, we …