Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Missouri University of Science and Technology

Discipline
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 301 - 330 of 21777

Full-Text Articles in Engineering

Work-In-Progress: Evaluating Feasibility Of Band Matrix Solvers For Scaling Up Extreme Learning Machine Method, Anton Akusok, Kaj Mikael Björk, Amaury Lendasse, Leonardo Espinosa Leal Jan 2026

Work-In-Progress: Evaluating Feasibility Of Band Matrix Solvers For Scaling Up Extreme Learning Machine Method, Anton Akusok, Kaj Mikael Björk, Amaury Lendasse, Leonardo Espinosa Leal

Engineering Management and Systems Engineering Faculty Research & Creative Works

This work presents the results of the potential of band linear system solvers for improving the scalability of the Extreme Learning Machine (ELM) method at large model sizes. The model is tested on the standard MNIST dataset with a range of solvers provided by the SciPy Python library. The results are analyzed taking into consideration the overall performance and the performance impact of band solvers across different matrix bandwidths, as well as the performance versus runtime analysis. The findings show potential in applying the proposed method to very large ELM models with narrow band matrices.


Sme Ai Outreach In Finland—A Case Study, Kaj Mikael Björk, Anton Akusok, Amaury Lendasse, Leonardo Espinosa-Leal Jan 2026

Sme Ai Outreach In Finland—A Case Study, Kaj Mikael Björk, Anton Akusok, Amaury Lendasse, Leonardo Espinosa-Leal

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents a project (work in progress) where entrepreneurship and higher education in AI (from Master level to postdoc level) are integrated in order to produce a dual effect; helping SMEs to gain insight in how AI can aid in the corporate environment and to expose AI researchers to the real-life situations in the company world. If successful, the companies are made ready for the AI revolution and the researchers more equipped for corporate settings. The project is ongoing, so this paper addresses a work-in-progress project. The paper reflects on the project as well on some aspects that need …


A Combined Stochastic And Physical Framework For Alloys And Metal Casting Processes Modeling, Simon N. Lekakh, Oleg Neroslavsky Jan 2026

A Combined Stochastic And Physical Framework For Alloys And Metal Casting Processes Modeling, Simon N. Lekakh, Oleg Neroslavsky

Materials Science and Engineering Faculty Research & Creative Works

High temperature metal casting processes have dualistic nature and conceptually consist of two parts of distinct processes: the first type is deterministic, strictly obeying the physical law, while the second type is stochastic. Therefore, the metal casting processes are not precisely predictable, and deterministic considerations cannot provide exact outcomes. To solve this problem, the combined stochastic and deterministic framework was suggested. The local processes were described using deterministic models for several parameter arrangements, while the distribution of these arrangements on macro level was calculated using stochastic approaches. The approach was used for cast alloy design, investment casting process optimization, and …


Thermal Transformations And Mechanical Properties Of All-D-Metal Mn2fecu Heusler-Type Shape Memory Alloy, Choji J. Daches, Joseph W. Newkirk, Mario Buchely Jan 2026

Thermal Transformations And Mechanical Properties Of All-D-Metal Mn2fecu Heusler-Type Shape Memory Alloy, Choji J. Daches, Joseph W. Newkirk, Mario Buchely

Materials Science and Engineering Faculty Research & Creative Works

All-d-metal Heusler alloys are emerging functional materials in which magnetic ordering, lattice distortion, and mechanical behavior are strongly coupled through d–d electronic interactions. This study systematically investigates the structural, thermal, magnetic, and mechanical properties of Mn₂FeCu synthesized within a Heusler-type compositional framework. SEM/EDS revealed a dual-phase FCC-based microstructure consisting of Mn–Fe–rich and Mn–Cu–rich domains, while XRD confirmed FCC symmetry with compositional partitioning rather than full L2₁ ordering. Differential scanning calorimetry identified partial melting of the Cu-rich phase near ~ 900 °C. Dilatometry showed a thermoelastic FCC → FCT transformation at ~ 770–780 °C with a recoverable strain of ~ 0.067%. …


Design Of Novel Gating Systems For Steel Castings, K. Balasubramanian, Laura Bartlett, M. Xu Jan 2026

Design Of Novel Gating Systems For Steel Castings, K. Balasubramanian, Laura Bartlett, M. Xu

Materials Science and Engineering Faculty Research & Creative Works

Gating systems play an important role in determining the quality and mechanical properties of castings. To understand the efficiency of gating systems, four systems, namely pressurized system, non-pressurized system, naturally pressurized system with a side riser and a naturally pressurized system with a top riser, were studied. The naturally pressurized systems were provided with overflows which collected the incoming metal swirl. Parameters like velocity of metal flow, air entrapment, microporosity and Niyama criterion were considered, and a design was developed with a common pouring basin. 8630 alloy was poured into two molds using a teapot ladle. The inclusion analysis revealed …


Microstructure And Properties Of Oxide Dispersion-Strengthened Alloys, Ertugrul Demir, Seung Min Ha, Anish Ranjan, Xingshuo Zhang, Aaron Penders, Mukesh Bachhav, Xiaochun Li, Lin Shao, Alexander Demblon, Haiming Wen, Enrique Lavernia Jan 2026

Microstructure And Properties Of Oxide Dispersion-Strengthened Alloys, Ertugrul Demir, Seung Min Ha, Anish Ranjan, Xingshuo Zhang, Aaron Penders, Mukesh Bachhav, Xiaochun Li, Lin Shao, Alexander Demblon, Haiming Wen, Enrique Lavernia

Materials Science and Engineering Faculty Research & Creative Works

Oxide dispersion-strengthened (ODS) alloys are a critical class of structural materials for extreme environments, owing to their unique combination of high-temperature strength, thermal stability, and radiation tolerance, enabled by a very high density of nanoscale oxide dispersoids. These features make ODS alloys attractive for advanced nuclear systems, aerospace applications, and other harsh-service conditions where conventional alloys rapidly degrade. Despite decades of development, key challenges remain in understanding how nanoscale oxides interact with matrix microstructures, alloy chemistry, and irradiation-induced defects to control macroscopic performance. This review provides a focused, mechanism-based synthesis of the microstructural features that govern the properties of ODS …


High Temperature Diffraction From Aerodynamically Levitated Materials, Chris J. Benmore, Stephen K. Wilke, David Lipke, Richard Weber Jan 2026

High Temperature Diffraction From Aerodynamically Levitated Materials, Chris J. Benmore, Stephen K. Wilke, David Lipke, Richard Weber

Materials Science and Engineering Faculty Research & Creative Works

Aerodynamic levitation combined with laser beam heating has become an established technique for studying the structure of materials at ultra-high temperatures and under non-equilibrium conditions. This article briefly highlights some recent technical and scientific advancements in understanding the relationships between a material's behavior and its structure, investigated using diffraction methods. It focuses on three evolving frontiers: sophisticated sample environments for accessing metastable states and reactive chemistries, high-flux photon and neutron probes to reveal atomic structure, and advanced computational modeling frameworks. Free from contamination, containerless processing (levitation) can minimize heterogeneous nucleation at the interface, enabling access to deeply supercooled melts or …


Elevated Temperature Flexure Behavior Of Continuous Carbon Fiber Reinforced Zrb2–Zrsi2 Ultrahigh Temperature Ceramic Matrix Composites, Jacob Stacy, Aaron Ginsparg, Jason Lonergan, Jeremy Watts, Gregory Hilmas Jan 2026

Elevated Temperature Flexure Behavior Of Continuous Carbon Fiber Reinforced Zrb2–Zrsi2 Ultrahigh Temperature Ceramic Matrix Composites, Jacob Stacy, Aaron Ginsparg, Jason Lonergan, Jeremy Watts, Gregory Hilmas

Materials Science and Engineering Faculty Research & Creative Works

Ultrahigh temperature ceramic matrix composites (UHTCMCs) were fabricated from unidirectional prepreg tapes consisting of a matrix of ZrB2 with 5, 10, and 15 vol.% ZrSi2 additions and continuous polyacrylonitrile carbon fibers and were densified at 1600°C in a hot press. The relative matrix densities ranged from 88% to 93% with interlayer spacings of ∼72 µm and fiber volume fractions between 30% and 36%. Phenolic resin additions were utilized to react with ZrSi2 acting as a transient sintering aid to form ZrC and SiC phases. Elastic moduli of the UHTCMCs decreased with increasing temperature during 4-pt flexure testing. …


Quantitative Grain Structure And Texture Analysis Of Hot-Pressed Zrb2 Via 3d Ebsd, Randi Swanson, Michael Chapman, Yue Zhou, Ashley Hilmas, Lisa Rueschhoff, Michael Uchic, William Fahrenholtz, Scott J. Mccormack Jan 2026

Quantitative Grain Structure And Texture Analysis Of Hot-Pressed Zrb2 Via 3d Ebsd, Randi Swanson, Michael Chapman, Yue Zhou, Ashley Hilmas, Lisa Rueschhoff, Michael Uchic, William Fahrenholtz, Scott J. Mccormack

Materials Science and Engineering Faculty Research & Creative Works

Understanding and controlling the grain structure of ZrB2 is critical for optimizing its mechanical and thermal performance in high-temperature applications. Fully dense ZrB2, densified by hot pressing at 2150˚C and 32 MPa, was analyzed in three dimensions using electron backscattered diffraction, electron and optical microscopy, and mechanical polishing serial sectioning. Grain size followed a gamma distribution, with extreme deviations observed only in the largest 0.1% of grains. Large grains exhibited plate-like morphologies, with the shortest-to-longest axis ratio converging to ∼0.4 as grain volume increased. This work revealed a crystallographically controlled growth mechanism orthogonal to [0001] that is …


Simulated Lunar Gravity Testing Of A Magnetic And Electrostatic System For Beneficiating Lunar Regolith, Blake A. Coffman, Gabriel Porter, Lindsay Manteufel, Mitchell Cottrell, Jeffrey D. Smith, David J. Bayless, William Shonberg, Frank D. Han, Fateme Rezaei, Kirby Runyon Jan 2026

Simulated Lunar Gravity Testing Of A Magnetic And Electrostatic System For Beneficiating Lunar Regolith, Blake A. Coffman, Gabriel Porter, Lindsay Manteufel, Mitchell Cottrell, Jeffrey D. Smith, David J. Bayless, William Shonberg, Frank D. Han, Fateme Rezaei, Kirby Runyon

Materials Science and Engineering Faculty Research & Creative Works

We present the design and testing of a lunar regolith beneficiation device that utilizes magnetic and electrostatic separation methods to concentrate desired minerals by removing unwanted material, such as the mineral anorthite, from bulk lunar regolith. The beneficiated materials would have value for downstream in-situ resource utilization (ISRU) processes such as metal extraction, oxygen extraction, and metal oxide additive manufacturing processes. The apparatus uses a dual-strength magnet system with N52 and N42 neodymium magnets to separate particles by magnetic susceptibility. The electrostatic separation system, which acts like a sieve, sorts the regolith simulant by particle size using a single-phase 50% …


The Effects Of Mold Flux Contamination On Oxide Scale Formation And Hydro-Descaling Efficiency During Steel Processing, Tochukwu Princewill Ojiako, Richard Osei, Mario Buchely, Haiming Wen, Simon Lekakh, Ronald O'Malley Jan 2026

The Effects Of Mold Flux Contamination On Oxide Scale Formation And Hydro-Descaling Efficiency During Steel Processing, Tochukwu Princewill Ojiako, Richard Osei, Mario Buchely, Haiming Wen, Simon Lekakh, Ronald O'Malley

Materials Science and Engineering Faculty Research & Creative Works

Oxide scale formation during thin-slab continuous casting has a complex structure, which is influenced by mold flux contamination, that modifies interfacial reactions during solidification, subsequent reheating, and descaling. While individual aspects of the oxidation behavior of carbon steel have been previously examined, the synergetic effects of mold flux contamination during continuous casting and subsequent reheating on scale modification and the efficiency of hydraulic descaling remain inadequately studied. This study quantitatively examines the effect of flux composition on oxide scale evolution, adhesion, and hydraulic removal in low-carbon steel under simulated industrial conditions. Slab samples with as-cast, cleaned, and flux-coated surfaces were …


Upconversion Photoluminescence In Wsse Alloy Monolayer Under Uniaxial Tensile Strain, Shrawan Roy, Jie Gao, Xiaodong Yang Jan 2026

Upconversion Photoluminescence In Wsse Alloy Monolayer Under Uniaxial Tensile Strain, Shrawan Roy, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The optical responses of monolayer transition metal dichalcogenides (1L-TMDs) can be tuned effectively by using mechanical strain. In this work, the tuning of upconversion photoluminescence (UPL) emission in 1L-WSSe alloy by applying uniaxial tensile strain is investigated. When the uniaxial tensile strain is changed from 0 % to 1.02 %, the peak position of UPL emission has a redshift of around 25.6 nm, and the UPL intensity goes up with an exponential function of the applied strain as the upconversion energy difference is varied from −197 meV to −131 meV. The sublinear power dependence for UPL emission in 1L-WSSe alloy …


Multi-Period Coordinated Planning Of Xfcs In Coupled Tn-Pdn Networks: Integrating Demand Charge Reduction And Pre-Existing Infrastructure, Waqas Ur Rehman, Siyuan Wang, Liheng Lv, Jonathan W. Kimball, Rui Bo Jan 2026

Multi-Period Coordinated Planning Of Xfcs In Coupled Tn-Pdn Networks: Integrating Demand Charge Reduction And Pre-Existing Infrastructure, Waqas Ur Rehman, Siyuan Wang, Liheng Lv, Jonathan W. Kimball, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate charging infrastructure support. This paper aims to address the latter bottleneck and proposes a strategic multi-period coordinated planning model to optimally site and size battery energy storage system (BESS) assisted extreme fast charging stations in a highway transportation network and solar systems in a power distribution network. The proposed approach accounts for pre-existing charging stations, the increasing EV penetration levels, decreasing technology costs, and technological advancements in the future and …


Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang Jan 2026

Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Metal-coated optical fibers are widely employed in sensing applications owing to their superior mechanical strength and corrosion resistance. However, their calibration at elevated temperatures is hindered by hysteresis, manifested as discrepancies between heating and cooling cycles, primarily caused by residual strain from mismatched thermal expansion coefficients (TECs) between the metal coating and silica cladding. This research introduces an optimal heat treatment procedure aimed at minimizing the impact of the mismatch in TECs between the cladding and the coating materials that causes the residual strain in gold (Au) and copper (Cu) coated fibers for achieving reliable distributed high temperature sensing up …


Integrating Optical And Radiofrequency Interferometry For Enhanced Phase Sensing, Ruimin Jie, Zhaopeng Zhang, Chen Zhu, Jie Huang Jan 2026

Integrating Optical And Radiofrequency Interferometry For Enhanced Phase Sensing, Ruimin Jie, Zhaopeng Zhang, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Interferometry is a crucial investigative technique used across diverse fields to achieve high-precision measurements. It works by analyzing the phase difference between two interfering waves, which results from variations in optical path lengths within an interferometer. We introduce a novel method for directly measuring changes in the phase difference within an optical interferometer, importantly, with the added advantage of a controllable enhancement factor. This approach is achieved through a two-step process: first, the optical phase difference is encoded into a sub-GHz radiofrequency (RF) signal using microwave-photonic manipulation; then, RF interferometry-assisted phase amplification is implemented at the destructive interference point. In …


Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems, Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok Jan 2026

Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems, Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In sensor-driven dynamic systems, missing data can severely degrade parameter estimation accuracy. This article investigates the impact of missing data on phase estimation in a mass-spring-damper system using an information-theoretic framework based on the Cramér-Rao Lower Bound (CRLB). Closed-form CRLB expressions are derived for four scenarios: complete data, missing completely at random (MCAR) deletion, MCAR-based imputation, and missing at random (MAR) missingness via a selection-weighted formulation. These bounds are used as theoretical benchmarks to evaluate classical imputation methods (last observation carried forward (LOCF), linear interpolation) and advanced approaches (Kalman filtering, Rauch-Tung-Striebel (RTS) smoothing, Bayesian inference, and transformer-based imputation) through Monte …


Online Lifelong Optimal Adaptive Control Of Partially Uncertain Strict Feedback Discrete-Time Systems With Application To Quadrotor Uavs, Maxwell Geiger, Sarangapani Jagannathan Jan 2026

Online Lifelong Optimal Adaptive Control Of Partially Uncertain Strict Feedback Discrete-Time Systems With Application To Quadrotor Uavs, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal adaptive tracking control of partially uncertain strict feedback discrete-time (DT) systems with application to quadrotor uncrewed aerial vehicles (UAVs). First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of the tracking error dynamics. The optimal adaptive tracking control problem is solved using an augmented system approach, where a horizon of future bounded reference trajectory points is used in the augmented state, when compared to using a single point. It is assumed that the internal dynamics of the strict feedback system are unknown, but the …


Effect Of Process Parameters On Thermal Response Of An Oxy-Fuel Burner/Injector Panel In An Electric Arc Furnace Via Fiber Optic Sensors, Mobashir Ahmed, Rony Kumer Saha, Koustav Dey, Todd Sander, Jie Huang, Ronald J. O'Malley Jan 2026

Effect Of Process Parameters On Thermal Response Of An Oxy-Fuel Burner/Injector Panel In An Electric Arc Furnace Via Fiber Optic Sensors, Mobashir Ahmed, Rony Kumer Saha, Koustav Dey, Todd Sander, Jie Huang, Ronald J. O'Malley

Electrical and Computer Engineering Faculty Research & Creative Works

Modern oxy-fuel burner/injectors in electric arc furnaces (EAFs) play a critical role in scrap melting, liquid steel refining, and slag foaming. However, varying operational modes, combined with dynamic process conditions, such as arcing and slag behavior, can expose the injector panel surface to intense thermal conditions that can compromise efficiency and safety. Conventional monitoring techniques, including cooling water temperature measurements and thermocouples, fail to capture localized thermal anomalies due to their limited spatial resolution and susceptibility to electromagnetic interference. In this study, four high-resolution Rayleigh backscattering-based fiber optic sensors, interrogated via optical frequency domain reflectometry, were embedded in top and …


Sapphire Optical Fiber Bragg Grating Sensors Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jie Huang Jan 2026

Sapphire Optical Fiber Bragg Grating Sensors Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Sapphire fiber Bragg gratings (SFBGs) have attracted growing interest for high temperature sensing in harsh environments, yet their interrogation typically relies on optical spectrum measurements, demanding a high-resolution optical spectrum analyzer (OSA) that is bulky, expensive, and constrained in acquisition speed. Moreover, the inherently multimode nature of sapphire fiber further complicates spectrum-based demodulation, thereby limiting the achievable sensing resolution. In this paper, we propose and experimentally demonstrate a microwave-photonic interrogation approach for SFBG sensors. Instead of measuring the optical reflection spectrum, the complex frequency response in the microwave domain of an SFBG is acquired using a vector network analyzer (VNA) …


Corrections To: Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems (Ieee Transactions On Instrumentation And Measurement (2026) 75 (1–12) Doi: 10.1109/Tim.2026.3676091), Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok Jan 2026

Corrections To: Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems (Ieee Transactions On Instrumentation And Measurement (2026) 75 (1–12) Doi: 10.1109/Tim.2026.3676091), Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In the above article [1], a wording ambiguity appears in Proposition 4 regarding the description of the missing at random (MAR) mechanism. The published sentence states that the probability of observing the kth sample depends on the realized measurement value. This wording may be interpreted as dependence on the current unobserved value y[tk], which could suggest a missing not at random (MNAR) mechanism. The intended MAR mechanism is that the observation probability for the kth sample depends only on previously observed measurement information, such as y[tk-1], and not on the current unobserved value y[tk]. Therefore, the corrected wording clarifies that …


Resolving Stiffness Trade-Offs In Simultaneous Pressure And Vibration Sensing Using A Corrugated-Tube Fiber-Optic Sensor, Yizheng Chen, Yan Tang, Jie Huang, Qi Zhang, Biyao Shi, Zewei Wu Jan 2026

Resolving Stiffness Trade-Offs In Simultaneous Pressure And Vibration Sensing Using A Corrugated-Tube Fiber-Optic Sensor, Yizheng Chen, Yan Tang, Jie Huang, Qi Zhang, Biyao Shi, Zewei Wu

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes and experimentally demonstrates a corrugated-tube-based fiber-optic sensor capable of measuring pressure, vibration, or both simultaneously. To address the limited sensitivity of conventional diaphragm-based designs, the sensor incorporates an optimized corrugated tube that balances the conflicting stiffness requirements for pressure and vibration measurements. The corrugated tube, acting as a mechanical transducer, is integrated with an extrinsic fiber-optic Fabry–Perot interferometer (EFPI). The EFPI cavity is formed between a reflective surface at the sealed end of the corrugated tube and the cleaved end face of an optical fiber fixed within a mounting assembly. In this configuration, displacement of the corrugated …


Nash Equilibrium Strategies For Multicluster Pursuit–Evasion Game With Disturbances: A Prescribed-Time Convergence Approach, Lei Xue, Xian Yu, Yongbao Wu, Jian Liu, Changyin Sun, D. C. Wunsch Jan 2026

Nash Equilibrium Strategies For Multicluster Pursuit–Evasion Game With Disturbances: A Prescribed-Time Convergence Approach, Lei Xue, Xian Yu, Yongbao Wu, Jian Liu, Changyin Sun, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article investigates the problem of prescribed-time Nash equilibrium (NE) seeking for a multicluster pursuit–evasion game (PEG) subject to external disturbances. To mitigate the impact of disturbances and reach the NE within a user-defined prescribed time, a prescribed-time disturbance observer (PTDO) is devised to estimate and compensate for them. Based on this observation, a novel control algorithm is developed, which facilitates collaboration among multiple pursuers to capture multiple evaders within the prescribed time. It is theoretically demonstrated that the designed algorithm ensures prescribed-time convergence to the NE of the multicluster PEG with disturbances. Finally, numerical simulations are conducted to verify …


Lidar-Based Framework For Detecting Suspicious Human Activities, Ahd Aljumah, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Gianluca Setti Jan 2026

Lidar-Based Framework For Detecting Suspicious Human Activities, Ahd Aljumah, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

This study explores the development of Human Activity Recognition (HAR) systems capable of identifying suspicious activities to enhance security in public spaces. We propose an innovative solution that integrates LiDAR sensors with deep learning technologies. Our method employs advanced models operating on LiDAR point cloud, PV-RCNN for human detection, and LidarGait++ for classifying activities into categories such as standing or walking (non-suspicious) and sneaking or fighting (suspicious). Due to the scarcity of suitable real-world datasets for training such systems, we utilize a 3D simulation tool, Blender, to create realistic environments and generate labeled point cloud data. This synthetic dataset allows …


Deep Learning Approach For Microwave Imaging Based On Deep Convolutional Asymmetric Encoder-Decoder Structure And Physics-Induced Loss, He Ming Yao, Shiji Song, Michael Kwok Po Ng, Lijun Jiang Jan 2026

Deep Learning Approach For Microwave Imaging Based On Deep Convolutional Asymmetric Encoder-Decoder Structure And Physics-Induced Loss, He Ming Yao, Shiji Song, Michael Kwok Po Ng, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we introduce an innovative deep learning (DL) methodology designed for real-time quantitative microwave imaging (MWI). Our approach is centered around the utilization of a deep convolutional asymmetric encoder-decoder structure (DCAEDS), which requires only a single-frequency far-field measurement of the electromagnetic (EM) scattered field as input and subsequently predicts the contrasts (permittivities) of the target materials. During the offline training process, we incorporate an EM forward solver specifically crafted to compute the EM scattered field generated by the predicted target contrasts (permittivities) produced by the DCAEDS. The DCAEDS is seamlessly integrated with this EM forward solver to optimize …


Effect Of Sample Properties On Short-Circuited Waveguide Measurements For Materials Characterization, Alexander Hook, Jared Sinkey, Kristen M. Donnell Jan 2026

Effect Of Sample Properties On Short-Circuited Waveguide Measurements For Materials Characterization, Alexander Hook, Jared Sinkey, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave materials characterization measurements can be performed using a number of well-established approaches. One such approach, the filled transmission line approach featuring a short-circuited rectangular waveguide (SC-RWG) sample holder, is known to have sample placement restrictions related to measurement viability. This work focuses on this approach and addresses the measurement restrictions within the context of sample length and dielectric properties. The complex reflection properties, S11, of a sample placed in a SC-RWG sample holder are studied to quantitively define when a sample must be offset from the SC-end. The impact of the sample holder is also studied from a measurement …


Investigations In Hydrogen Ironmaking, Joseph William Govro Jan 2026

Investigations In Hydrogen Ironmaking, Joseph William Govro

Doctoral Dissertations

The purpose of this research is to contribute to the Grid Interactive Steelmaking with Hydrogen (GISH) project. This research investigates the viability of both producing and melting Direct-Reduced Iron (DRI) utilizing hydrogen. Conventional CO reduced DRI will be referred to as “C-DRI” and DRI produced using hydrogen gas will be referred to as “H-DRI”.

An H-DRI pilot plant was constructed in Golden Colorado. The pilot plant was commissioned and successfully operated four campaigns. Process improvements were made throughout the campaigns and the process was optimized. In addition to running the pilot plant in a pure hydrogen condition, the pilot plant …


Zirconium Carbide Based Materials For Extreme Aerospace Environments, Nathaniel Hyman Blatt Jan 2026

Zirconium Carbide Based Materials For Extreme Aerospace Environments, Nathaniel Hyman Blatt

Doctoral Dissertations

This research focuses on the processing and properties of zirconium carbide-based materials to promote their use in extreme environment aerospace applications, including nuclear thermal propulsion and hyper sonics. Several carbide systems including ZrC, ZrC-Mo cermets, (Zr, Nb)C, and a high entropy carbide were developed. The ZrC-Mo cermet was studied extensively to understand the effect of starting carbide grain size on the final microstructure, composition, elastic moduli, hardness, fracture toughness, room and elevated temperature flexural strength, thermal diffusivity, electrical resistivity, thermal expansion coefficient, and thermal conductivity. It was shown that heat transport in the cermets was dominated by the ZrC phase …


Machine Learning Based Automation Of Pcb Pdn Design And Optimization, Haran Manoharan Jan 2026

Machine Learning Based Automation Of Pcb Pdn Design And Optimization, Haran Manoharan

Doctoral Dissertations

The rapid increase in power density and stringent power-integrity requirements in modern System-on-Chip (SoC) platforms have made Power Delivery Network (PDN) design an increasingly complex, multi-stage challenge. Critical decisions must be made both during pre-layout planning, such as stackup configuration, power-plane geometry, and early decoupling capacitor (decap) budgeting, and during post-layout refinements. Traditional heuristic and evolutionary optimization techniques struggle with scalability, require extensive manual iteration, leading to long runtimes and limited adaptability across varying board configurations. To address these challenges, this work proposes a unified reinforcement-learning-driven framework for automated PDN synthesis and decap optimization that spans both pre-layout and post-layout …


Incremental Cluster Validity Indices And Their Role In Interpreting Lifelong Learning Systems, Niklas Max Melton Jan 2026

Incremental Cluster Validity Indices And Their Role In Interpreting Lifelong Learning Systems, Niklas Max Melton

Doctoral Dissertations

Clustering and supervised learning are often treated as distinct paradigms, yet both rely on structure in feature space. This dissertation investigates the relationship between cluster validity indices (CVIs) and supervised learning in real-time and lifelong learning settings where data arrive incrementally and cannot be revisited. Across four studies, it develops methods for online cluster validation, uses supervised learning to improve their interpretability, and applies these ideas to evaluating performance degradation in continual learning.

The first study extends incremental cluster validity indices (iCVIs), enabling widely used validation metrics to operate in streaming environments. Experiments on synthetic and real-world datasets show systematic …


Advancing Coal Rib Support Design Through The Integration Of Field Studies And Numerical Simulations, Alper Kirmaci Jan 2026

Advancing Coal Rib Support Design Through The Integration Of Field Studies And Numerical Simulations, Alper Kirmaci

Doctoral Dissertations

Coal rib stability remains a major safety concern in U.S. underground coal mines, with rib failure-related injuries and fatalities still occurring. A key challenge is the lack of a standardized methodology for designing rib support systems that can address varying geological conditions. As a result, many mines rely on trial-and-error or traditional practices, leading to inconsistent designs. This research aims to develop a systematic methodology for rib support design to improve coal rib stability in U.S. mining operations.

The study consists of: i) field monitoring in active room-and-pillar coal mines, ii) in-situ pull-out tests on coal ribs, iii) numerical model …