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Articles 1231 - 1260 of 75008

Full-Text Articles in Engineering

Dynamic Direct Voltage Control Under Maximum Torque Per Ampere For Interior Pmsms, Mohamad Alzayed, Hicham Chaoui, Alaref Elhaj Jan 2026

Dynamic Direct Voltage Control Under Maximum Torque Per Ampere For Interior Pmsms, Mohamad Alzayed, Hicham Chaoui, Alaref Elhaj

Electrical & Computer Engineering Faculty Publications

A novel method for controlling the speed of interior permanent magnet synchronous motors (IPMSMs), known as the current-sensing-based dynamic direct voltage control method under the maximum torque per ampere (MTPA) concept, is introduced. This technique achieves precise tracking of machine velocity by determining the optimal combination of voltage amplitude and angle for each specific motor velocity and current/load condition. Unlike previous studies, this approach takes into account the transient model of the machine, resulting in improved accuracy during dynamic operating conditions compared with existing methods in the literature. Moreover, a comparative analysis is conducted involving different direct voltage MTPA speed …

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Qubit Lattice Algorithm Simulations Of The Scattering Of A Bounded Two Dimensional Electromagnetic Pulse From The Infinite Planar Dielectric Interface, Min Soe, George Vahala, Linda Vahala, Efstratios Koukoutsis, Abhay K. Ram, Kyriakos Hizanidis Jan 2026

Qubit Lattice Algorithm Simulations Of The Scattering Of A Bounded Two Dimensional Electromagnetic Pulse From The Infinite Planar Dielectric Interface, Min Soe, George Vahala, Linda Vahala, Efstratios Koukoutsis, Abhay K. Ram, Kyriakos Hizanidis

Electrical & Computer Engineering Faculty Publications

Qubit lattice algorithm (QLA) simulations are performed for a two-dimensional spatially bounded pulse propagating onto a plane interface between two dielectric slabs. QLA is an initial value scheme that consists of a sequence of unitary collision and streaming operators, with appropriate potential operators, that recover Maxwell equations in inhomogeneous dielectric media to the second order in the lattice discreteness. For the case of total internal reflection, there is transient energy transfer into the second medium due to the evanescent fields as the Poynting unit vector of the pulse is rotated from its incident to reflected direction. Because of the finite …

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Recent Advances In Bioceramics, Fundamental Properties And Future Perspective In Biomedical Applications ‒ A Review, Ayesha Younas, Muhammad Umar Aslam Khan, Mohd Faizal Binte Abdullah, Lobat Tayebi, Shuanghu Wang, Abdalla Abdal-Hay, Yichi Xu Jan 2026

Recent Advances In Bioceramics, Fundamental Properties And Future Perspective In Biomedical Applications ‒ A Review, Ayesha Younas, Muhammad Umar Aslam Khan, Mohd Faizal Binte Abdullah, Lobat Tayebi, Shuanghu Wang, Abdalla Abdal-Hay, Yichi Xu

Electrical & Computer Engineering Faculty Publications

Bioceramics are important biomaterials in biomedical engineering because of their biocompatibility, bioactivity, osteoconductivity, and structural resemblance to actual bone tissue. In recent years, materials science and nanotechnology have enabled the use of bioceramics in bone regeneration, dental restoration, tissue engineering, drug delivery systems, and implantable medical devices. This comprehensive review covers advances in bioceramics, including calcium phosphates, hydroxyapatite (HAp), tricalcium phosphate, bioactive glasses, zirconia, alumina, and multifunctional ceramic nanocomposites. Priority is given to techniques such as additive manufacturing, 3D printing, sol-gel processing, electrospinning, and nanostructuring to improve mechanical strength, porosity, bioactivity, and cell interactions. Recent advances include ion doping, surface …

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Metagenomic Polymorphic Toxin Effector And Immunity Profiling Predicts Microbiome Development And Disease-Related Dysbiosis, Hunter W. Schroer, Francesco Beghini, Juan Antonio Raygoza Garay, Nicholas A. Christakis, Dustin E. Bosch Jan 2026

Metagenomic Polymorphic Toxin Effector And Immunity Profiling Predicts Microbiome Development And Disease-Related Dysbiosis, Hunter W. Schroer, Francesco Beghini, Juan Antonio Raygoza Garay, Nicholas A. Christakis, Dustin E. Bosch

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Bacteria use antagonistic interbacterial weapons, such as polymorphic toxin secretion systems (TSS), to compete for niches in the human gut microbiome. We hypothesized that TSS influence gut microbiome development and disease-related dysbiosis. We developed a bioinformatic marker gene approach (PolyProf) to quantify TSS including ~200 effector and immunity genes and applied it to ~15,000 publicly available human metagenomes. PolyProf alpha and beta diversity readily distinguished 12 different human disease states and enabled the construction of highly accurate linear regression classifier machine learning models. Elastic net machine learning models integrating bacterial taxonomy with PolyProf had strong predictive value for 12 disease …

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Development Of Feature Tokenizer Deep Learning Model For Fault Diagnosis In Marine Propulsion System, Pratik Anand Deshpande, J. Preetha Roselyn, Prabha Sundaravadivel Jan 2026

Development Of Feature Tokenizer Deep Learning Model For Fault Diagnosis In Marine Propulsion System, Pratik Anand Deshpande, J. Preetha Roselyn, Prabha Sundaravadivel

Electrical Engineering Faculty Publications and Presentations

The fault diagnostics in Brushless Direct Current (BLDC) motor drive system is critical for operational safety and system lifespan in propulsion system applications. However, signature parameters such as currents, voltages, speed, and torque have provided nonlinear behavior, which limits the usefulness of traditional model-based approaches. This research provides a deep learning based intelligent system to monitor the failures in marine propulsion system. Each signal feature is represented as a structured token, with a specific class token used to collect global contextual information. The proposed model captures both local temporal dynamics and global inter-feature interdependence multi-layer self-attention processes, allowing for the …

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Using Network Models To Understand Biological Signaling Architecture, Russ White, Emily Brown Reeves, Gerald L. Fudge Jan 2026

Using Network Models To Understand Biological Signaling Architecture, Russ White, Emily Brown Reeves, Gerald L. Fudge

Faculty Publications

Engineers have developed abstract network models to better understand the recurring problems faced by communication systems. This paper argues that these models can be generalized to describe biological communications systems given that they share many requirements with human-designed systems, including functional requirements and physical constraints. Leveraging collaboration, biologists and engineers can work together to use well-understood communication systems, designed to carry data across a computer network, as a model for analyzing less well-understood biological communication systems in order to make predictions and uncover previously unknown functionalities. To illustrate this approach, we apply the Recursive Internet Network Architecture model (RINA) to …

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Performance Of Shcc Brick Infill And Nsm Reinforcement Systems For Strengthening Rc Deep Beams With Large Openings, Ahmed Badr El-Din, Mohamed Ghalla, Galal Elsamak, Ayman El-Zohairy Jan 2026

Performance Of Shcc Brick Infill And Nsm Reinforcement Systems For Strengthening Rc Deep Beams With Large Openings, Ahmed Badr El-Din, Mohamed Ghalla, Galal Elsamak, Ayman El-Zohairy

Faculty Publications

The presence of large web openings in reinforced concrete (RC) deep beams often disrupts the natural load-transfer mechanism, leading to severe reductions in shear strength and premature failure. This study introduces a novel hybrid strengthening system incorporating strain-hardening cementitious composite (SHCC) bricks, stainless-steel and galvanized-steel sheets, and near-surface-mounted (NSM) steel reinforcements to restore and enhance the shear performance of RC deep beams with large openings. A comprehensive experimental program was conducted on sixteen beams under concentrated loading to evaluate the influence of different infill and strengthening configurations on load capacity, stiffness, ductility, and energy absorption. The results revealed that the …

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Dynamic Modeling Of The Earth's Trapped Proton Environment, Xiaojing Xu, Steve R. Blattnig, Francis F. Badavi, Martha S. Clowdsley, Edward J. Semones Jan 2026

Dynamic Modeling Of The Earth's Trapped Proton Environment, Xiaojing Xu, Steve R. Blattnig, Francis F. Badavi, Martha S. Clowdsley, Edward J. Semones

Physics Faculty Publications

Context: Reliable prediction of space radiation exposure is critical for safeguarding spacecraft systems and ensuring astronaut health during missions. Accurate radiation risk assessment for space mission requires advanced models of the Earth’s trapped proton environment. These models must reflect temporal variations driven by geomagnetic field evolution and solar cycle modulation. Existing static models, such as AP8 and IRENE-AP9, are not designed to fully capture these evolving conditions. Aims: This paper presents a dynamic modeling method for the prediction of trapped proton fluxes, which incorporate time-dependent variations due to geomagnetic field evolution and solar cycle fluctuations. Methods: The …

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Long Short-Term Memory (Lstm) -Based Neural Network Model For Optimizing Composite Manufacturing Process Using Autoclave, Sourav Bolar, Steven Corns, Nayan Pundhir, Kumbla Chandrashekhara Jan 2026

Long Short-Term Memory (Lstm) -Based Neural Network Model For Optimizing Composite Manufacturing Process Using Autoclave, Sourav Bolar, Steven Corns, Nayan Pundhir, Kumbla Chandrashekhara

Engineering Management and Systems Engineering Faculty Research & Creative Works

Producing high-quality fiber-reinforced composites requires precise temperature control during autoclave curing, as even small variations can lead to defects that compromise strength and reliability. At the same time, manufacturers aim to reduce energy use and shorten curing cycles without sacrificing material performance. To address these challenges, this study develops a data-driven Long Short-Term Memory (LSTM) neural network model capable of forecasting temperature evolution inside the autoclave throughout the curing cycle. The model is trained on time-series temperature data collected from multiple sensing locations, enabling it to learn the spatial and temporal trends that govern heat flow during curing. Data augmentation …

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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.

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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 …

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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 …

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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%. …

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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 …

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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 …

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Catalytic Hydropyrolysis Of Beetle Killed Trees For The Production Of Transportation Biofuels, Oluwanisola Makinde, Fernando L.P. Resende, Michael Asama, Demian F. Gomez Jan 2026

Catalytic Hydropyrolysis Of Beetle Killed Trees For The Production Of Transportation Biofuels, Oluwanisola Makinde, Fernando L.P. Resende, Michael Asama, Demian F. Gomez

Jasper Department of Chemical Engineering Faculty Publications and Presentations

We conducted catalytic hydropyrolysis of beetle-killed trees: Pine, Ash tree, and Redbay in a micro-pyrolyzer (Py/GC–MS) and investigated the performance of heterogeneous catalysts like HZSM-5, NiMo-HZSM- 5, and NiRe-HZSM- 5. We also investigated the effects of temperature, catalyst-to- biomass ratio, and hydrogen pressure on product yield. Our findings reveal that aromatic yields increase with temperature and catalyst-to- biomass ratio but decline at higher hydrogen pressures; additionally, higher catalyst acidity enhances both total hydrocarbon production and selectivity toward C7–C8 aromatics, with each feedstock exhibiting distinct optimal conditions. The type of metal doped on the HZSM-5 zeolite plays an important role in …

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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 …

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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. …

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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 …

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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% …

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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 …

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Stem-Fit And Soil-Fit: Integrated Plant And Soil Nitrogen-Hormone Sensing With Machine Learning-Based Forecasting For Next-Generation Precision Agriculture, Nafize I. Hossain, Mohammad Solaiman, A.K.M. Ahsanul Habib, Md Al Mahmud Hossain Al Hadi, Shawana Tabassum Jan 2026

Stem-Fit And Soil-Fit: Integrated Plant And Soil Nitrogen-Hormone Sensing With Machine Learning-Based Forecasting For Next-Generation Precision Agriculture, Nafize I. Hossain, Mohammad Solaiman, A.K.M. Ahsanul Habib, Md Al Mahmud Hossain Al Hadi, Shawana Tabassum

Electrical Engineering Faculty Publications and Presentations

Inefficient fertilizer application in agriculture leads to reduced crop productivity, nutrient losses, and reduced crop resilience, highlighting the urgent need for real-time monitoring of plant–soil nutrient and stress dynamics. This research aims to develop and validate a multiplexed sensing platform for real-time, in-situ measurement of key soil nutrients (Soil-FIT) and plant phytohormones (Stem-FIT) involved in nitrogen signaling and stress regulation. The proposed sensor suite integrates 3D-printed modules for continuous monitoring of nitrate, ammonium, and pH in both soil and plant sap, along with salicylic acid (SA), indole-3-acetic acid (IAA), methyl jasmonate (MeJA), and ethylene (ET) in plant sap. The sensors, …

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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 …

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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 …

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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 …

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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 …

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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 …

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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 …

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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 …

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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) …

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