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2025

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Articles 6841 - 6870 of 8606

Full-Text Articles in Engineering

Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan Jan 2025

Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a unified framework for the safe and optimal control of heterogeneous quadrotor unmanned aerial vehicles (QUAVs) in formation, enabling multitask missions without requiring precise system dynamics. To address partial state observability, a multilayer neural network (MNN) observer is designed to estimate unmeasured states. Reinforcement learning (RL) is employed for optimal control utilizing an MNN ensuring adaptability. Barrier Lyapunov Functions (BLFs) are integrated into the RL framework to enforce safety by maintaining QUAVs within predefined constraints. An enhanced continual learning (ECL) method is proposed to improve the adaptability of MNNs. This method enables effective multitask learning while mitigating …

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Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang Jan 2025

Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Radiated emissions from the noise-generating components in modern electronic devices are a significant concern for both electromagnetic interference and RF interference. Shielding cans are commonly used to suppress emissions from noise sources, but accurate shielding effectiveness evaluation requires a clean, well-defined radiation source that can reliably mimic real emissions for repeatable measurements. Slot-backed microstrip antennas provide a practical alternative to loop antennas, offering zero height, low parasitic radiation, and seamless printed circuit board integration. This article proposes an analytical model for estimating the magnetic dipole moment of slot-backed microstrip structures. The model captures both the discontinuity effects and radiated characteristics …

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Centralized And Federated Heart Disease Classification Using Uci Dataset: A Benchmark With Interpretability Analysis, Mario Padilla Rodriguez, Eyiara Oladipo, Mohamed Nafea Jan 2025

Centralized And Federated Heart Disease Classification Using Uci Dataset: A Benchmark With Interpretability Analysis, Mario Padilla Rodriguez, Eyiara Oladipo, Mohamed Nafea

Electrical and Computer Engineering Faculty Research & Creative Works

Cardiovascular disease (CVD) is a leading cause of global mortality, highlighting the need for accurate diagnostic methods. This study benchmarks centralized and federated learning (FL) algorithms for heart disease binary classification using the UCI dataset, which includes 920 patient records from four hospitals in the USA, Hungary, and Switzerland. Our benchmark is supported by Shapley-value as well as Local Interpretable Model-agnostic Explanations (LIME) interpretability analyses to quantify feature importance for classification. In the centralized setup, various classification algorithms are trained on pooled data, with the Naive Bayes classifier achieving the highest test accuracy of 81.1%. Further, FL algorithms with four …

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Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea Jan 2025

Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea

Electrical and Computer Engineering Faculty Research & Creative Works

Cardiovascular disease (CVD) is a leading cause of global mortality, accounting for an estimated 17.9 million deaths annually. CVD is broadly defined as a group of medical conditions influenced by modifiable or non-modifiable risk factors that affect the heart's ability to function properly. Machine learning (ML) has emerged as a powerful tool for analyzing complex medical data, aiding in early detection and accurate diagnosis of CVD and improving patient outcomes. Recent studies proposed various deep learning (DL) architectures for detecting CVD, yet there is a lack of robust benchmarks for comparing their performance on large-scale databases. In this work, we …

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Corona Discharge To Touchscreen Modeling Using Nonlinear Time-Dependent Corona Streamer Propagation Model In Spice, Zhekun Peng, Daniel Szanto, Jianchi Zhou, Darryl Kostka, David Pommerenke, Daryl G. Beetner Jan 2025

Corona Discharge To Touchscreen Modeling Using Nonlinear Time-Dependent Corona Streamer Propagation Model In Spice, Zhekun Peng, Daniel Szanto, Jianchi Zhou, Darryl Kostka, David Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

SPICE-based methods for predicting coupling from an ESD-induced corona streamer to printed-circuit board (PCB) structures beneath a touchscreen display are evaluated in this paper. Results demonstrate that the non-linear time-dependent propagation model can capture the coupling much better than other models and accurately predict the overall current waveform.

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Ms-Yolo: Infrared Object Detection For Edge Deployment Via Mobilenetv4 And Slideloss, Jiali Zhang, Thomas S. White, Haoliang Zhang, Wenqing Hu, Donald C. Wunsch, Jian Liu Jan 2025

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

Mathematics and Statistics Faculty Research & Creative Works

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

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Graphite Particles Modified By Zno Atomic Layer Deposition For Li-Ion Battery Anodes, Ahmad Helaley, Han Yu, Xinhua Liang Jan 2025

Graphite Particles Modified By Zno Atomic Layer Deposition For Li-Ion Battery Anodes, Ahmad Helaley, Han Yu, Xinhua Liang

Chemical and Biochemical Engineering Faculty Research & Creative Works

Graphite, with a modest specific capacity of 372 mA h g−1, is a stable material for lithium-ion battery anodes. However, its capacity is inadequate to meet the growing power demands because the formation of an irregular solid electrolyte interphase (SEI) can result in unstable performance. In this research, we used a few cycles of atomic layer deposition (ALD) to deposit ZnO on graphite particles as an anode with improved electrochemical stability. Transmission electron microscopy revealed that ZnO was in the form of nanoparticles due to the inert surface properties of graphite and only a few cycles of ALD. Electrochemical characterization …

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Emulsion Liquid Membrane (Elm) Technique For Efficient Separation Of Heavy Metals From Acidic Solutions Including Phosphoric Acid: A Review, O. Karai, N. Y. Selem, K. Benabderazak, J. Mendil, H. Mazouz, M. H. Al-Dahhan Jan 2025

Emulsion Liquid Membrane (Elm) Technique For Efficient Separation Of Heavy Metals From Acidic Solutions Including Phosphoric Acid: A Review, O. Karai, N. Y. Selem, K. Benabderazak, J. Mendil, H. Mazouz, M. H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Heavy metal ions in aqueous and acidic solutions pose serious threats to ecosystems. Their effective removal is crucial, and emulsion liquid membrane (ELM) technology offers a promising solution. This review delves into ELM's principles, mechanisms, components, and performance indicators including stability for extracting heavy metals from acidic solutions including phosphoric acid., ELM's stability issues, such as internal phase coalescence, membrane leakage, and swelling, limit its efficiency. Thus, this review paper discusses previous research that analyzed ELM stability and heavy metal extraction efficiency from these acidic solutions. Furthermore, it assesses other techniques like Emulsion Ionic Liquid Membrane (EILM) and Pickering Emulsion …

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Enhanced Cholesterol Efflux And Atherosclerosis Regression Via Ceh Gene Delivery Using Galactose-Functionalized Dendrimeric Nanoparticles, Huari Kou, Jing Wang, Paul J. Yannie, Da Huang, William J. Korzun, Genta Kakiyama, Siddhartha S. Ghosh, Hu Yang Jan 2025

Enhanced Cholesterol Efflux And Atherosclerosis Regression Via Ceh Gene Delivery Using Galactose-Functionalized Dendrimeric Nanoparticles, Huari Kou, Jing Wang, Paul J. Yannie, Da Huang, William J. Korzun, Genta Kakiyama, Siddhartha S. Ghosh, Hu Yang

Chemical and Biochemical Engineering Faculty Research & Creative Works

Cholesteryl ester hydrolase (CEH) is a critical enzyme in cholesterol ester hydrolysis, influencing cholesterol metabolism and efflux. This study demonstrates that CEH overexpression promotes free cholesterol efflux from macrophages, thereby reducing the lipid burden in existing atherosclerotic plaques. To enable targeted delivery, galactose-functionalized polyamidoamine (PAMAM) dendrimeric nanoparticles were utilized as nanocarriers for hepatic delivery of the CEH expression vector. The therapeutic potential of CEH plasmid-loaded dendrimeric nanoparticles was evaluated in Ldlr-/- mice. Results showed a significant reduction in total lesion area (21%) and aortic arch lesion area (23%) compared to baseline. Lesion component analysis revealed marked decreases in total cholesterol …

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Characterizing Heat Transfer Performance In A Slurry Bubble Column Reactor Equipped With A Real Heat Exchanger, Dalia S. Makki, Hasan Sh Majdi, Amer A. Abdulrahman, Abbas J. Sultan, Bashar J. Kadhim, Muthanna H. Al-Dahhan Jan 2025

Characterizing Heat Transfer Performance In A Slurry Bubble Column Reactor Equipped With A Real Heat Exchanger, Dalia S. Makki, Hasan Sh Majdi, Amer A. Abdulrahman, Abbas J. Sultan, Bashar J. Kadhim, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Abstract: This study examines the impact of equipping a real heat exchanger in a slurry bubble column SBC on instantaneous and local heat transfer coefficients IHTC and LHTC, as well as the overall heat transfer coefficient U, employing advanced heat transfer techniques. The experiments were conducted in a 0.15 m inner diameter Plexiglas SBC with varying gas flowrates Ug (0.14–0.35) m/s at several radial sites along the column's diameter (±0.18, ±0.46, and ± 0.74) and three axial locations (H/D = 2, 3 and 4). To simulate the industrial Fischer–Tropsch bubble column reactor FT-BCR, a real heat exchanger consisting of 18 …

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A New Deep Decoder Type Cascaded Feedforward Neural Network For Critical Heat Flux Prediction In Power Reactors, Rehan Zubair Khalid, Atta Ullah, Asifullah Khan, Mansoor Hameed Inayat, Muthanna H. Al-Dahhan Jan 2025

A New Deep Decoder Type Cascaded Feedforward Neural Network For Critical Heat Flux Prediction In Power Reactors, Rehan Zubair Khalid, Atta Ullah, Asifullah Khan, Mansoor Hameed Inayat, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Critical Heat Flux (CHF) is a fundamental parameter for ensuring the performance, reliability, safety, and economic viability of water-cooled nuclear reactors. Despite its significance, the absence of a deterministic theory for CHF prediction poses a substantial challenge in thermal engineering. Consequently, various experimental and numerical models have been developed, yet no universally accepted model comprehensively addresses the wide range of flow conditions encountered in practical applications. The accurate prediction of CHF remains a complex and critical task. This work introduces a novel Deep Decoder Type Cascaded feedforward Neural Network (DD-CFNN) to predict CHF across a broad spectrum of operating conditions. …

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Experimental Investigation Of Heat Transfer Behavior In Spouted Bed Reactors Under Different Operating Conditions, Hasan A. Abdulwahab, Abbas J. Sultan, Amer A. Abdulrahman, Hasan Sh Majdi, Haydar A.S. Aljaafari, Zahraa W. Hasan, Laith S. Sabri, Bashar J. Kadhim, Jamal M. Ali, Muthanna H. Al-Dahhan Jan 2025

Experimental Investigation Of Heat Transfer Behavior In Spouted Bed Reactors Under Different Operating Conditions, Hasan A. Abdulwahab, Abbas J. Sultan, Amer A. Abdulrahman, Hasan Sh Majdi, Haydar A.S. Aljaafari, Zahraa W. Hasan, Laith S. Sabri, Bashar J. Kadhim, Jamal M. Ali, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Abstract: Spouted bed reactors (SBRs) are highly valued for their effectiveness in chemical and biochemical processes due to their mixing and heat transfer capabilities. Understanding the heat transfer mechanisms in these reactors is necessary. This research delves into the heat transfer behavior of SBRs, which plays a role in enhancing their performance under operational conditions. The study conducted experiments to measure the heat transfer coefficient (HTC) at varying gas velocities (ranging from 0.32 to 0.74 m/s) at radial positions (r/R = 0, ±0.28, ±0.56, and ±0.85) and axial levels (H/D = 0.8, 2.1, and 3.5) within the spouted bed (SB) …

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Tumor Microenvironment Immunomodulation By Nanoformulated Tlr 7/8 Agonist And Pi3k Delta Inhibitor Enhances Therapeutic Benefits Of Radiotherapy, Mostafa Yazdimamaghani, Oleg V. Kolupaev, Chaemin Lim, Duhyeong Hwang, Sonia J. Laurie, Charles M. Perou, Alexander V. Kabanov, Jonathan S. Serody Jan 2025

Tumor Microenvironment Immunomodulation By Nanoformulated Tlr 7/8 Agonist And Pi3k Delta Inhibitor Enhances Therapeutic Benefits Of Radiotherapy, Mostafa Yazdimamaghani, Oleg V. Kolupaev, Chaemin Lim, Duhyeong Hwang, Sonia J. Laurie, Charles M. Perou, Alexander V. Kabanov, Jonathan S. Serody

Chemical and Biochemical Engineering Faculty Research & Creative Works

Infiltration of immunosuppressive cells into the breast tumor microenvironment (TME) is associated with suppressed effector T cell (Teff) responses, accelerated tumor growth, and poor clinical outcomes. Previous studies from our group and others identified infiltration of immunosuppressive myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) as critical contributors to immune dysfunction in the orthotopic claudin-low tumor model, limiting the efficacy of adoptive cellular therapy. However, approaches to target these cells in the TME are currently lacking. To overcome this barrier, polymeric micellular nanoparticles (PMNPs) were used for the co-delivery of small molecule drugs activating Toll-like receptors 7 and 8 …

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Machine Learning Modeling For Hydrolysis Recycling Of Pet Waste, Jie Li, Lanjia Pan, Hossein Abedsoltan, Hailong Wang, Taiyang Liu, Xiangzhou Yuan, Yong Sik Ok, Yin Wang Jan 2025

Machine Learning Modeling For Hydrolysis Recycling Of Pet Waste, Jie Li, Lanjia Pan, Hossein Abedsoltan, Hailong Wang, Taiyang Liu, Xiangzhou Yuan, Yong Sik Ok, Yin Wang

Chemical and Biochemical Engineering Faculty Research & Creative Works

The hydrolysis of polyethylene terephthalate (PET) into terephthalic acid (TPA) can efficiently recycle waste PET, but achieving high conversion efficiency through smart reaction design remains challenging. To develop a robust and accurate machine learning (ML) model for the in-depth understanding and intelligent design of PET hydrolysis, we compiled a new dataset comprising 942 data points and comprehensive information of 44 variables involved in heating type, acid/base catalyst (ABC), organic solvent (OS), co-solvent (CS), phase transfer catalyst (PTC), and operational conditions. The developed Neural Network model demonstrated the best performance in predicting PET conversion, with a testing determination coefficient (R2 …

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Mechanistic Scale-Up Of Gas-Solid Fluidized Beds Via Local Hydrodynamic Similarity, Faraj M. Zaid, Thaar M. Aljuwaya, Muthanna H. Al-Dahhan Jan 2025

Mechanistic Scale-Up Of Gas-Solid Fluidized Beds Via Local Hydrodynamic Similarity, Faraj M. Zaid, Thaar M. Aljuwaya, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

This study presents a detailed experimental evaluation of a newly developed mechanistic scale-up methodology for gas-solid fluidized beds. Traditional scale-up approaches typically rely on matching global dimensionless groups, which often fail to ensure local hydrodynamic similarity. In contrast, the new mechanistic method aims to achieve scale-up by matching the radial profiles of gas holdup between geometrically similar beds at corresponding dimensionless axial positions (z/Dc). This approach is based on the premise that when gas holdup profiles align, other key hydrodynamic parameters—such as solids holdup and particle velocity—also become similar. To validate this methodology, experiments were conducted in two …

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Pla-Based Bone Tissue Engineering Scaffolds Incorporating Hydroxyapatite And Bioactive Glass Using Digital Light Processing, Engin Gepek, Fateme Fayyazbakhsh, Lev Suliandziga, Vadym Mochalin, Osman Iyibilgin, Yue-Wern Huang, Ming C. Leu Jan 2025

Pla-Based Bone Tissue Engineering Scaffolds Incorporating Hydroxyapatite And Bioactive Glass Using Digital Light Processing, Engin Gepek, Fateme Fayyazbakhsh, Lev Suliandziga, Vadym Mochalin, Osman Iyibilgin, Yue-Wern Huang, Ming C. Leu

Chemistry Faculty Research & Creative Works

Bone tissue engineering (BTE) aims to repair bone defects using biocompatible materials with tailored geometries and pore structures, providing appropriate mechanical support and control over biodegradation kinetics to promote bone growth. In this study, we utilized digital light processing (DLP) 3D printing to fabricate scaffolds with varying pore sizes using polymer–ceramic slurries composed of polylactic acid (PLA) as the main polymer matrix, incorporated with hydroxyapatite (HA) and bioactive borate glass (BBG) at various ratios. We studied the effect of composition on rheological behavior, printability, mechanical properties, bioactivity, degradation rate, and biocompatibility. While HA increased viscosity and reduced printing accuracy, it …

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Mechanical And Thermal Characterization Of Additively Manufactured Carbon/Nylon 12 And Carbon/Peek Composites, Matik Heskin, Bradley Deuser, Thomas P. Schuman, K. Chandrashekhara, John Bayldon, Jeff Degrange, Steven Patterson, Neiko Levenhagen Jan 2025

Mechanical And Thermal Characterization Of Additively Manufactured Carbon/Nylon 12 And Carbon/Peek Composites, Matik Heskin, Bradley Deuser, Thomas P. Schuman, K. Chandrashekhara, John Bayldon, Jeff Degrange, Steven Patterson, Neiko Levenhagen

Chemistry Faculty Research & Creative Works

This study explores additive manufacturing of carbon fiber-reinforced thermoplastic composites using the Composite-Based Additive Manufacturing (CBAM) process. Carbon/Nylon 12 and Carbon/PEEK composites were fabricated and evaluated through mechanical (compression, tensile, flexural, and impact) and thermal (DSC and TGA) tests. Carbon/PEEK exhibited superior mechanical performance, with 97.5% higher tensile strength, 79.8% higher elastic modulus, and 59.6% higher flexural strength compared to Carbon/Nylon 12. Thermal testing showed that Carbon/PEEK had higher thermal stability, beginning degradation at 350 °C versus 298 °C for Carbon/Nylon. These results indicate that CBAM-fabricated Carbon/PEEK composites are suitable for applications requiring high strength and temperature resistance.

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Navigation In Underground Mine Environments: A Simulation Framework For Quadruped Robots, Yixiang Gao, Kwame Awuah-Offei Jan 2025

Navigation In Underground Mine Environments: A Simulation Framework For Quadruped Robots, Yixiang Gao, Kwame Awuah-Offei

Mining Engineering Faculty Research & Creative Works

Quadruped robots have shown significant potential for navigating complex and hazardous environments, such as underground mines, where traditional wheeled or tracked systems have limitations. However, their development and deployment are hindered by the disparity between controlled laboratory testing and real-world conditions and the lack of tools (e.g., simulation testbeds) that expedite the required development and testing. This work develops a simulation testbed for expediting and advancing navigation algorithms, perception systems, and control strategies for quadruped robots in subterranean and hazardous environments. By utilizing high-fidelity 3D maps, ranging from intricate cave systems to real-world sites like the Edgar Mine, simulation environment …

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Optimizing Acid Mist Suppression: Unraveling Surfactant Effects On Bubble Formation And Bursting Dynamics In Copper Electrowinning, Ashish Kakoria, Mirza Muhammad Zaid, Aamir Iqbal, Ellen Amoako Afful, Guang Xu Jan 2025

Optimizing Acid Mist Suppression: Unraveling Surfactant Effects On Bubble Formation And Bursting Dynamics In Copper Electrowinning, Ashish Kakoria, Mirza Muhammad Zaid, Aamir Iqbal, Ellen Amoako Afful, Guang Xu

Mining Engineering Faculty Research & Creative Works

The working mechanism of surfactant to reduce acid mist in copper electrowinning system is not well understood. Most of the studies are based on the surface tension reduction phenomenon but this is not the only function that causes acid mist reduction. In this paper, we investigated the effect of different surfactants on a bubble's residence time, terminal velocity, flow regime, and bursting dynamics using a high-speed camera. We have evaluated five different surfactants and found that the presence of surfactants reduces the terminal velocity, bubble diameter, and increases the residence time of the bubble in electrolyte. Especially for FC-1100, the …

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Great Lakes Water Level Trends Using The Moving Statistics Method, With Implications For Climate Change And Cities, Brian Barkdoll, Opeyemi Alamutu Jan 2025

Great Lakes Water Level Trends Using The Moving Statistics Method, With Implications For Climate Change And Cities, Brian Barkdoll, Opeyemi Alamutu

Michigan Tech Publications

Increasing magnitudes of precipitation and evaporation are predicted for future climate change. Knowing whether these trends are occurring can help water managers plan with respect to future erosion, flooding, and design changes for shoreline infrastructure. Data from all the Laurentian Great Lakes (Erie, Michigan-Huron, Ontario, St. Clair, and Superior) were analyzed here to determine whether these trends are being realized. The MovingStatistics Method is used here using the moving average and moving standard deviation. It was found that Lakes Erie and St. Clair had the highest moving average trend of 0.5 mm/month, while Lake Ontario had the highest moving standard …

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A Ground Thermal Vacuum Facility For Simulating Cryogenic Space Environment Conditions, Emmanuel Kofi Asuako Wie-Addo, Lucas Scott, Daoru Han Jan 2025

A Ground Thermal Vacuum Facility For Simulating Cryogenic Space Environment Conditions, Emmanuel Kofi Asuako Wie-Addo, Lucas Scott, Daoru Han

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work presents the ongoing progress of a vacuum facility upgrade at the Gas and Plasma Dynamics Laboratory (GPDL) at Missouri University of Science and Technology. A movable shroud has been fabricated and installed to enable the simulation of extreme cold conditions. The cooling rate of the shroud, a dummy test article, and a platform, using liquid nitrogen as the thermal fluid, is analyzed and reported under varying vacuum conditions for cryogenic runs. Preliminary testing revealed substantial thermal exchange between the shroud and the chamber walls, underscoring the necessity for implementing effective thermal isolation measures to mitigate heat transfer.

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Arc-Jet And Free-Flight Evaluation Of Laminar And Turbulent Diffusion Models On Ablation, Kyle Worden, Andrew Heider, Serhat Hosder Jan 2025

Arc-Jet And Free-Flight Evaluation Of Laminar And Turbulent Diffusion Models On Ablation, Kyle Worden, Andrew Heider, Serhat Hosder

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper investigates the effect of diffusion models on carbon ablation with a parametric study on a slug-calorimeter geometry in arc-jet flow at two enthalpy conditions using two arc-jet flow modeling approaches, and at corresponding enthalpy-matched free-flight conditions using RANS CFD simulations. Additionally, a sphere-cone geometry is modeled at the arc-jet enthalpy matched free-flight conditions and at a high Reynolds number free-flight condition. The approximate-corrected form of Fick's law and the Stefan-Maxwell diffusion models are investigated for equilibrium and finite-rate carbon ablation in laminar and turbulent flows, which is simulated with the Menter-SST turbulence model. The turbulent cases include the …

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An Adaptive Sampling Strategy On Optimal Takeoff Trajectory Prediction Of Electric Drones, Dheeraj Paramkusham, Samuel Sisk, Jiachen Wang, Shuan Tai Yeh, Xiaosong Du, Nathan Roberts Jan 2025

An Adaptive Sampling Strategy On Optimal Takeoff Trajectory Prediction Of Electric Drones, Dheeraj Paramkusham, Samuel Sisk, Jiachen Wang, Shuan Tai Yeh, Xiaosong Du, Nathan Roberts

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft transforms future transportation systems by alleviating transportation congestion on the ground. This eVTOL technique possesses unique features, including reduced noise, low pollutant emissions, efficient operating costs, and flexible maneuverability. Meanwhile, battery consumption poses critical challenges to flight task duration. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimization, however, iteratively evaluates high fidelity simulation models, making the design process computationally intensive. In this work, we implement a machine learning-enabled inverse mapping optimization concept, i .e., directly predicting optimal design based on design requirements (including …

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Study On Field Emission Characteristics Of Carbon Nanotube Arrays Patterned Via Laser Welding Of Dissimilar Materials, Hung Yin Tsai, Yi Hung Chen, Kuan Ching Wang, Paul W. Leu, Ming C. Leu Jan 2025

Study On Field Emission Characteristics Of Carbon Nanotube Arrays Patterned Via Laser Welding Of Dissimilar Materials, Hung Yin Tsai, Yi Hung Chen, Kuan Ching Wang, Paul W. Leu, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper describes a new method of growing carbon nanotube (CNT) arrays using laser welding of a catalyst metal onto the surface of a quartz substrate, followed by CNT growth through the chemical vapor deposition (CVD) process. A major advantage of this method is its ability to pattern the catalyst before growing the CNTs, thus allowing for the formation of CNTs at specific locations. The laser pre-treatment method minimized structural damage to CNTs in comparison to the laser post-processing method, achieving a lower ID/IG value of 0.72 in Raman spectroscopy analysis. Using hexagonally patterned CNT arrays on quartz, we achieve …

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Correction: Advancing Cislunar Space Domain Awareness Through Robust Optimization Framework For Optical Sensors-Based Autonomous Satellite Systems (American Institute Of Aeronautics And Astronautics Inc, Aiaa), Smriti Nandan Paul, Siwei Fan, Igor Panfil Jan 2025

Correction: Advancing Cislunar Space Domain Awareness Through Robust Optimization Framework For Optical Sensors-Based Autonomous Satellite Systems (American Institute Of Aeronautics And Astronautics Inc, Aiaa), Smriti Nandan Paul, Siwei Fan, Igor Panfil

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Correction Notice • Page 8: "$\lambda_2$: It represents the cardinality-weighted" corrected to "$\lambda_2$: It represents the inverse of cardinality-weighted." Equation $\lambda_2=\sum_{i=1}^{10}(n_i\Xi_i)$ corrected to $\lambda_2=1/(\sum_{i=1}^{10}(n_i \Xi_i))$ • Page 11: Table 1 is updated with new orbital families and number of satellites & 1 & $L_2$ Halo south|$L_1$ Halo north|Butterfly south & 1|2|3\\ & 2 & $L_1$ Halo north|$L_2$ Halo south|Dragonfly south & 5|10|3\\ & 3 & Butterfly south|$L_2$ Halo south|$L_2$ Lyapunov & 3|10|4\\ & 4 & $L_1$ Halo south|$L_2$ Halo north|$L_1$ Halo north & 5|3|1\\ A|B|C & 5 & $L_2$ Halo south|$L_1$ Lyapunov|$L_2$ Halo north & 2|8|9\\ & 6 & $L_3$ …

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High-Order Dynamic Mode Decomposition For Multidimensional Harmonic Retrieval, Yanming Zhang, Steven Gao, Lijun Jiang Jan 2025

High-Order Dynamic Mode Decomposition For Multidimensional Harmonic Retrieval, Yanming Zhang, Steven Gao, Lijun Jiang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Estimating channel parameters such as azimuth, elevation, Doppler shift, and delay is a key challenge in wireless communication, often formulated as a multidimensional harmonic retrieval (MHR) problem. To address this, we propose a high-order dynamic mode decomposition (HODMD) framework for robust frequency estimation from high-dimensional signals in noisy environments. The HODMD approach combines high-order singular value decomposition (HOSVD) to decompose tensor data into a core tensor and mode matrices, with dynamic mode decomposition (DMD) to extract frequencies from the imaginary parts of the DMD eigenvalues. Simulation examples validate the effectiveness of the proposed method, demonstrating its efficiency in solving MHR …

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Performance Evaluation And Multiphysics Process Modeling Of Carbon Fiber Reinforced Thermoset Composites Using Microwave And Autoclave, Nayan Pundhir, Patrick Schwartzkopf, K. Chandrashekhara, Logan Wilcox, Kristen M. Donnell, Jim Lua, Rui Li Jan 2025

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

Mechanical and Aerospace Engineering Faculty Research & Creative Works

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

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Design And Testing Of An Intrusive Arm For Supersonic Flow Sampling, Caleb Roberts, Davide Viganò Jan 2025

Design And Testing Of An Intrusive Arm For Supersonic Flow Sampling, Caleb Roberts, Davide Viganò

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Intrusive probes are critical tools in supersonic wind tunnel testing, enabling direct measurement of flow properties such as pressure and heat flux. To support these measurements, a single-axis intrusive arm was designed and implemented in the Missouri S&T Supersonic Wind Tunnel. The system is designed to maintains precise probe positioning, while withstanding the aerodynamic loads, and preserving a dynamic seal between the test section and ambient environment. Its modular design accommodates a range of probe types for various research applications. This paper presents the design methodology, including structural, mechanical, and aerodynamic considerations, and details the integration process. System performance was …

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Deep Reinforcement Learning-Based Optimal Takeoff Trajectory Design Of An Evtol Drone, Nathan M. Roberts, Bingling Huang, Xiaosong Du Jan 2025

Deep Reinforcement Learning-Based Optimal Takeoff Trajectory Design Of An Evtol Drone, Nathan M. Roberts, Bingling Huang, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The continuing development of electric vertical take-off and landing (eVTOL) aircraft presents promising opportunities to alleviate transportation congestion. However, designing and executing takeoff trajectories that optimally balance energy usage, passenger comfort, and aircraft constraints remains challenging. Conventional design optimization provides a solution for pre-defined flight conditions and environments but is not ideal in real-world applications. In contrast, deep reinforcement learning (DRL) implements optimal policy making real-time decisions with no assumption of mathematical models. Seeing the lack of literature on DRL-based takeoff trajectory design of eVTOL aircraft, we implement and conduct DRL-based optimal takeoff trajectory designs for the Airbus3 Vahana …

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Industry 5.0, Human–Machine Interface, And Smart Manufacturing In Additive Manufacturing—A Recent Trend, Atiqur Rahman, Md Hazrat Ali, Muhammad Arif Mahmood, Frank Liou Jan 2025

Industry 5.0, Human–Machine Interface, And Smart Manufacturing In Additive Manufacturing—A Recent Trend, Atiqur Rahman, Md Hazrat Ali, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The emergence and importance of Industry 5.0 are transforming production by integrating smart technology with human creativity and intelligence, especially in advanced additive manufacturing. This critical review precisely analyzes the function of human–machine interfaces (HMIs) in enhancing additive processes, emphasizing their incorporation into smart manufacturing systems and hybrid manufacturing methods, including material extrusion (MEX), laser powder bed fusion (LPBF), and directed energy deposition (DED). It also evaluates artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, which enhance HMIs in process monitoring, operation, and system adaptability. This study aims to provide a critical analysis and future research direction on …

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