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Missouri University of Science and Technology

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Articles 91 - 120 of 2222

Full-Text Articles in Mechanical Engineering

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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Optimizing Uav Swarm Deployment For Efficient Communication Signal Strength Alignment In Disaster Scenarios, Mina Khalilzadeh Fathi, Chaoying Pei Jan 2025

Optimizing Uav Swarm Deployment For Efficient Communication Signal Strength Alignment In Disaster Scenarios, Mina Khalilzadeh Fathi, Chaoying Pei

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In disaster scenarios, establishing reliable communication infrastructure is critical, and unmanned aerial vehicle (UAV) swarms offer a promising solution as temporary base stations. This study models communication demand in disaster-affected areas by applying Gaussian kernels to building data, forming a spatial demand distribution. Signal strength is estimated using the normalized inverse Free Space Path Loss (FSPL) to account for realistic attenuation. To guide UAV placement, we extract high-demand regions from the demand distribution using a gradient-based thresholding method. Based on this information, we develop a greedy algorithm to iteratively position UAVs for optimal coverage in areas with the greatest communication …

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Few-Shot Learning-Enhanced Tiered Path Planning For Mars Rover Navigation, Ziyi Wang, Di Yu, Mina Khalilzadeh Fathi, Chaoying Pei Jan 2025

Few-Shot Learning-Enhanced Tiered Path Planning For Mars Rover Navigation, Ziyi Wang, Di Yu, Mina Khalilzadeh Fathi, Chaoying Pei

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Path planning for Mars rovers presents significant challenges due to the diverse terrain, ranging from easily navigable areas to hazardous zones. Traditional methods typically classify terrain simply as passable or impassable, failing to account for the nuances of more moderately challenging areas. In this paper, we introduce a tiered terrain-aware path planning strategy, employing few-shot learning to classify and segment Martian terrain into levels of difficulty. The few-shot learning model, trained on Earth, is sent to the rover, enabling real-time processing of images from satellites or helicopters. The flexibility of few-shot learning, which requires minimal data and training time, enables …

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Influence Of Alloy Composition On The Process Robustness Of Steels Consolidated Via Laser-Directed Energy Deposition, Jonathan Kelley Jan 2025

Influence Of Alloy Composition On The Process Robustness Of Steels Consolidated Via Laser-Directed Energy Deposition, Jonathan Kelley

Masters Theses

"To ensure consistent quality of additively manufactured parts, it is advantageous to identify alloys which can meet performance criteria while being robust to process variations. Toward this end, this work investigated the effect of alloy composition on the robustness of steels consolidated via laser-directed energy deposition (L-DED). Ultra-high-strength low-alloy steel (UHSLA) and pure iron powders were mixed in-situ to produce 10 compositions containing 10-100% UHSLA by mass. JMatPro material simulations roughly predicted phases and mechanical properties. Two sets of experiments were used to evaluate the sensitivity of as-built hardness (all 10 compositions) and tensile properties (5 select compositions) to process …

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Anisotropic And Temperature-Tunable Second-Harmonic Vortex Generation In Ferroelectric Nbocl2 Holograms, Jayanta Deka, Xiaodong Yang, Jie Gao Jan 2025

Anisotropic And Temperature-Tunable Second-Harmonic Vortex Generation In Ferroelectric Nbocl2 Holograms, Jayanta Deka, Xiaodong Yang, Jie Gao

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Optical vortex beams with helical phase fronts have immense potential to enhance data capacity due to the unbounded values of orbital angular momentum. Chip-scale platforms for producing vortex beams are of paramount importance for a variety of applications. On the other hand, 2D materials with unique optical properties are essential for developing multifunctional ultrathin photonic devices. Here, anisotropic and temperature-tunable second-harmonic vortex beam generation is demonstrated with ultrathin ferroelectric niobium oxide dichloride (NbOCl2) fork holograms. The polarization-resolved Raman measurements are performed on the NbOCl2 crystal to understand the anisotropic behavior of the Raman modes. It is demonstrated …

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Machine Learning Approach For Defect Prediction In Metal 3d Printing For Aerospace Applications, Yerlik Gabdulla, Md Hazrat Ali, Frank Liou, Essam Shehab Jan 2025

Machine Learning Approach For Defect Prediction In Metal 3d Printing For Aerospace Applications, Yerlik Gabdulla, Md Hazrat Ali, Frank Liou, Essam Shehab

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Additive manufacturing (AM) has revolutionized the aerospace industry by enabling the production of lightweight and high-strength components, such as aerospace engine components and structural elements. The ability to create complex geometries and reduce material waste is particularly beneficial for aerospace applications, where performance and weight reduction are paramount. However, ensuring the quality and reliability of these components remains a challenge, particularly in mass production, which is related to material quality, expensive processes, and longer computational times than conventional manufacturing methods. This paper proposes an approach utilizing a Decision Tree Classification Machine Learning Algorithm to predict the possibility of defect occurrence …

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In-Situ Transmission Electron Microscopy Investigation Of Grain Size And Temperature Dependent Irradiation Behavior Of 304l Stainless Steel, Anish Ranjan, Matthew Luebbe, Nastaran Motaharinia, Wei Ying Chen, Frank Liou, Haiming Wen Jan 2025

In-Situ Transmission Electron Microscopy Investigation Of Grain Size And Temperature Dependent Irradiation Behavior Of 304l Stainless Steel, Anish Ranjan, Matthew Luebbe, Nastaran Motaharinia, Wei Ying Chen, Frank Liou, Haiming Wen

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The influence of grain size, irradiation temperature, and dose on the evolution of irradiation-induced defects in austenitic 304L stainless steel (SS) was systematically investigated. Coarse-grained (CG), ultrafine-grained (UFG), and nanocrystalline (NC) specimens were exposed to irradiation doses up to 10 displacements per atom (dpa) at room temperature (RT), 300°C, and 500°C. Dislocation loop size and density were quantitatively analyzed using transmission electron microscopy, and results showed that the dislocation loop size remained comparable across different grain sizes. However, loop density was strongly dependent on the grain size. The CG specimens exhibited the highest loop density due to a limited fraction …

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Anisotropic Third-Harmonic Vortex Beam Generation With Ultrathin Germanium Arsenide Fork Gratings, Jayanta Deka, Jie Gao, Xiaodong Yang Jan 2025

Anisotropic Third-Harmonic Vortex Beam Generation With Ultrathin Germanium Arsenide Fork Gratings, Jayanta Deka, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Optical vortices have the tremendous potential to increase data capacity by leveraging the extra degree of freedom of orbital angular momentum. On the other hand, anisotropic 2D materials are promising building blocks for future integrated polarization-sensitive photonic and optoelectronic devices. Here, highly anisotropic third-harmonic optical vortex beam generation is demonstrated with fork holograms patterned on ultrathin 2D germanium arsenide flakes. It is shown that the anisotropic nonlinear vortex beam generation can be achieved independent of the fork grating orientation with respect to the crystallographic orientation. Furthermore, 2D fork hologram is designed to generate multiple optical vortices having different topological charges …

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Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo Jan 2025

Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Vegetable oil-based lubricants have attracted increased research attention in recent decades as sustainable alternatives to conventional petroleum-based lubricants in metal machining. However, more studies are required to fully elucidate the thermo-rheological and tribological properties. This study presents an investigation of the thermo-rheological and tribological properties of different vegetable oils, including low- and high-oleic soybean oil, high-oleic sunflower, safflower, and canola oils. The lubricity, and evolution of viscosity and thermodynamic properties as a function of temperature were investigated to obtain important parameters including the viscosity index, flow behavior index, flow activation energy, specific heat capacity, thermal conductivity, coefficient of friction, contact …

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Generative Adversarial Networks For Dimensionality Reduction In Evtol Aircraft Takeoff Trajectory Optimization, Samuel Sisk, Farzaam Khorasani-Gerdehkouhi, Abdulaziz Abutunis, K. Chandrashekhara, Xiaosong Du Jan 2025

Generative Adversarial Networks For Dimensionality Reduction In Evtol Aircraft Takeoff Trajectory Optimization, Samuel Sisk, Farzaam Khorasani-Gerdehkouhi, Abdulaziz Abutunis, K. Chandrashekhara, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft play a key role in urban air mobility (UAM), which aims to alleviate traffic congestion in urban areas. Despite their value, eVTOL aircraft suffer from battery energy consumption, which affects their range and endurance in real world flight tasks. Especially, the takeoff process has been identified for excessive power demands. Multidisciplinary analysis and optimization manage to discover optimal takeoff trajectories with minimum energy consumption while balancing multidisciplinary trade-offs, such as short distance takeoff and passengers' comfort. However, conventional parametrization methods (such as B-spline curves) leverage an empirically high-dimensional design space to include real …

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Ai-Powered Image-Based Assessment Of Pressure Injuries Using You Only Look Once (Yolo) Version 8 Models, Mehedi Hasan Tusar, Fateme Fayyazbakhsh, Niloofar Zendehdel, Eduard Mochalin, Igor Melnychuk, Lisa Gould, Ming C. Leu Jan 2025

Ai-Powered Image-Based Assessment Of Pressure Injuries Using You Only Look Once (Yolo) Version 8 Models, Mehedi Hasan Tusar, Fateme Fayyazbakhsh, Niloofar Zendehdel, Eduard Mochalin, Igor Melnychuk, Lisa Gould, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Objective: The primary objective of this study is to enhance the detection and staging of pressure injuries using machine learning capabilities for precise image analysis. This study explores the application of the You Only Look Once version 8 (YOLOv8) deep learning model for pressure injury staging. Approach: We prepared a high-quality, publicly available dataset to evaluate different variants of YOLOv8 (YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x) and five optimizers (Adam, AdamW, NAdam, RAdam, and stochastic gradient descent) to determine the most effective configuration. We followed a simulation-based research approach, which is an extension of the Consolidated Standards of Reporting Trials …

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Improving Neural Network Efficiency With Multi-Fidelity And Dimensionality Reduction Techniques, Vignesh Sella, Thomas O'Leary-Roseberry, Xiaosong Du, Mengwu Guo, Joaquim R.R.A. Martins, Omar Ghattas, Karen Willcox, Anirban Chaudhuri Jan 2025

Improving Neural Network Efficiency With Multi-Fidelity And Dimensionality Reduction Techniques, Vignesh Sella, Thomas O'Leary-Roseberry, Xiaosong Du, Mengwu Guo, Joaquim R.R.A. Martins, Omar Ghattas, Karen Willcox, Anirban Chaudhuri

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Design problems in aerospace engineering often require numerous evaluations of expensive to-evaluate high-fidelity models, resulting in prohibitive computational costs. One way to address the computational cost is through building surrogates, such as deep neural networks (DNNs). However, DNNs may only be an effective surrogate when sufficient evaluations of the high-fidelity model are required such that the up-front training cost is amortized, or in situations that require real-time responses (such as interactive visualizations). Typically, the data requirements for adequately accurate training of DNNs are often impractical for engineering applications. To alleviate this issue, the proposed work utilizes output dimensionality reduction along …

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Tensile Behavior Of Directed Energy Deposited Bi-Metallic Ti-Ni-Based Alloy At Interfacial Area, Yitao Chen, Cesar Ortiz Rios, Frank Liou Jan 2025

Tensile Behavior Of Directed Energy Deposited Bi-Metallic Ti-Ni-Based Alloy At Interfacial Area, Yitao Chen, Cesar Ortiz Rios, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

A Ti-Ni-based bi-metallic shape memory alloy was fabricated using directed energy deposition, and the tensile testing behavior at two sections after post-heat treatments were focused. The Ti-rich Ti-Ni-Cu ternary shape memory alloy was first fabricated on a TiNi shape memory alloy with near-equiatomic composition to achieve multi-functional shape memory behaviors using powder-based additive manufacturing. The bi-metallic part then underwent 400°C and 600°C heat treatment at the interfacial area, and the interfacial area was subject to tensile loading and unloading. The digital image correlation technique was applied to extract the tensile stress–strain behavior and map out the local strain evolution of …

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Advancing Cislunar Space Domain Awareness Through Robust Optimization Framework For Optical Sensors-Based Autonomous Satellite Systems, Smriti Nandan Paul, Siwei Fan, Igor Panfil Jan 2025

Advancing Cislunar Space Domain Awareness Through Robust Optimization Framework For Optical Sensors-Based Autonomous Satellite Systems, Smriti Nandan Paul, Siwei Fan, Igor Panfil

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The number of cislunar resident space objects is expected to proliferate rapidly because of strategic interests targeting long-term presence on the Moon and exploration of other planets (e.g., Artemis Accords) and liberalization of space through the entry of private space players (e.g., Intuitive Machines). It necessitates expanding current near-Earth space domain awareness (SDA) operation systems and knowledge to the relatively unexplored cislunar region. Besides the traditional complexities, xGEO orbits (orbits beyond the geosynchronous Earth orbit (GEO) region) face additional challenges because of highly non-linear and non-Keplerian dynamics, which results in inaccuracies in uncertainty propagation and state estimation. Further challenges include …

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Hands-Free Uav Control: Real-Time Eye Movement Detection Using Eog And Lstm Networks, Niloofar Zendehdel, Khosro Ghorbani Zadeh, Haodong Chen, Yun Seong Song, Ming C. Leu Jan 2025

Hands-Free Uav Control: Real-Time Eye Movement Detection Using Eog And Lstm Networks, Niloofar Zendehdel, Khosro Ghorbani Zadeh, Haodong Chen, Yun Seong Song, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Industry 4.0 has created a growing need for effective human-robot collaboration (HRC). As robots and humans work more closely together, efficient communication becomes essential for coordinating their actions seamlessly. While speech may seem like the obvious choice for communication, noisy factory environments can render it impractical. Additionally, workers often have their hands occupied with assembly tasks, making hand-controlled interfaces less practical for controlling robots. To address these challenges, this paper presents a novel, hands-free method for robot control using electrooculography (EOG) signals–specifically, eye movements and blinks–with unmanned aerial vehicles (UAVs) used as the demonstration platform. We developed a real-time system …

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Physics-Constrained Generative Artificial Intelligence For Rapid Takeoff Trajectory Design, Samuel Sisk, Xiaosong Du Jan 2025

Physics-Constrained Generative Artificial Intelligence For Rapid Takeoff Trajectory Design, Samuel Sisk, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The urban air mobility (UAM) industry is rapidly growing to alleviate regional transportation congestion. Electric vertical takeoff and landing (eVTOL) aircraft plays a critical role in this growth due to their efficiency and reduced operating cost. However, excessive energy demands by the takeoff phase impact the practicality of the aircraft. Conventional multidisciplinary analysis and optimization (MDAO) identifies a minimum energy trajectory but can be computationally intensive due to iteratively evaluating high-fidelity simulation models. In addition, complex constraints in practical MDAO pose crucial challenges to the already demanding process. Surrogate models enable efficient design optimization, but complex constraints could prohibit surrogate-based …

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Versatile Injector Platform: A Modular Design For Supersonic Flow Research, Connor Bell, Davide Viganò Jan 2025

Versatile Injector Platform: A Modular Design For Supersonic Flow Research, Connor Bell, Davide Viganò

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Fuel–air mixing remains a critical challenge in the development of high-speed air-breathing propulsion due to the extremely short residence times in supersonic combustors. Experimental studies are essential to investigate the underlying mixing mechanisms, but they require injection systems that can deliver repeatable and controlled flow conditions. In this work, we present the design of a modular strut-type injection platform developed for the Missouri S&T Supersonic Wind Tunnel. In its initial configuration, the platform features a planar trailing-edge slit to generate a two-dimensional jet and includes interchangeable trailing-edge modules to support a wide range of geometries and flow-control strategies. Designed with …

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Comparison Of Cnn And Lstm Networks On Human Intention Prediction In Physical Human-Robot Interactions, Khosro Ghorbani Zadeh, Niloofar Zendehdel, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Ming-Chuan Leu, Yun Seong Song Jan 2025

Comparison Of Cnn And Lstm Networks On Human Intention Prediction In Physical Human-Robot Interactions, Khosro Ghorbani Zadeh, Niloofar Zendehdel, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Ming-Chuan Leu, Yun Seong Song

Psychological Science Faculty Research & Creative Works

Advancements in robotics and AI have increased the demand for interactive robots in healthcare and assistive applications. However, ensuring safe and effective physical human-robot interactions (pHRIs) remains challenging due to the sophistication of human motor communication and intent recognition. Traditional physics-based models struggle to capture the dynamic nature of human force interactions, limiting robot adaptability. To address these limitations, neural networks (NNs) have been explored for force-movement intention prediction. While multi-layer perceptron (MLP) networks show potential, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks effectively model sequential dependencies, while Convolutional Neural Networks (CNNs) enhance spatial feature …

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Designing Robust Quasi-2d Perovskites Thin Films For Stable Light-Emitting Applications, Sharmistha Khan, Reshna Shrestha, Mengru Jin, Doyun Kim, Guan Lin Chen, Ruipeng Li, Yijia Gu, Qing Tu, Namyoung Ahn, Wanyi Nie Jan 2025

Designing Robust Quasi-2d Perovskites Thin Films For Stable Light-Emitting Applications, Sharmistha Khan, Reshna Shrestha, Mengru Jin, Doyun Kim, Guan Lin Chen, Ruipeng Li, Yijia Gu, Qing Tu, Namyoung Ahn, Wanyi Nie

Materials Science and Engineering Faculty Research & Creative Works

Quasi-2D perovskite made with organic spacers co-crystallized with inorganic cesium lead bromide inorganics is demonstrated for near unity photoluminescence quantum yield at room temperature. However, light emitting diodes made with quasi-2D perovskites rapidly degrade which remains a major bottleneck in this field. In this work, It is shown that the bright emission originates from finely tuned multi-component 2D nano-crystalline phases that are thermodynamically unstable. The bright emission is extremely sensitive to external stimuli and the emission quickly dims away upon heating. After a detailed analysis of their optical and morphological properties, the degradation is attributed to 2D phase redistribution associated …

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Ground Testing Of A Magnetic-Electrostatic Separation System For Lunar Regolith Beneficiation, Peter Bachle, Charles Wood, Jeffrey Smith, Fateme Rezaei, David Bayless, William Schonberg, Daoru Han Jan 2025

Ground Testing Of A Magnetic-Electrostatic Separation System For Lunar Regolith Beneficiation, Peter Bachle, Charles Wood, Jeffrey Smith, Fateme Rezaei, David Bayless, William Schonberg, Daoru Han

Materials Science and Engineering Faculty Research & Creative Works

The separation of lunar regolith by mineral composition and size category is useful forin-situ resource utilization (ISRU). The research presented herein discusses the designing and development of equipment that has the potential to separate lunar regolith into aluminum, iron-titanium, and magnesium-iron ores. Along with the metal ore separation, this equipment shows the potential to separate regolith by size categories. The combined effect of these separation methods generates output that is valuable to subsequent use in metal and oxygen extraction, additive manufacturing, and regolith sintering processes. The designed equipment uses a dual-strength magnet system with N42 and N52 neodymium magnets for …

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Controlling Nitrogen Pickup During Induction Melting Of Ultrahigh-Strength Cr-Ni-Mo-V Steels, Kingsley T. Amatanweze, Viraj A. Athavale, Mario F. Buchely, Laura N. Bartlett, Ronald J. O'Malley, Daniel M. Field Jan 2025

Controlling Nitrogen Pickup During Induction Melting Of Ultrahigh-Strength Cr-Ni-Mo-V Steels, Kingsley T. Amatanweze, Viraj A. Athavale, Mario F. Buchely, Laura N. Bartlett, Ronald J. O'Malley, Daniel M. Field

Materials Science and Engineering Faculty Research & Creative Works

Nitrogen pickup during air induction melting can result in porosity and a loss of fracture toughness in ultrahigh-strength quenched and tempered steel castings. Nitrogen atoms are easily adsorbed into liquid steel upon exposure to the air, and argon shrouding alone has limited effectiveness. Previous studies have shown that proper charge sequencing and maintaining a high amount of dissolved oxygen in the melt prior to tapping and deoxidation can limit nitrogen pickup in the melt. In the current study, the effect of melt practice and charging procedure on nitrogen pickup was studied as a function of hold time in a series …

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Parametric Analysis Of Water Jet Descaling Efficiency Of Reheated Continuously Cast Thin Slab, Tochukwu P. Ojiako, Mario F. Buchely, Simon Lekakh, Ronald J. O'Malley, Richard Osei, Taha Tayebali Jan 2025

Parametric Analysis Of Water Jet Descaling Efficiency Of Reheated Continuously Cast Thin Slab, Tochukwu P. Ojiako, Mario F. Buchely, Simon Lekakh, Ronald J. O'Malley, Richard Osei, Taha Tayebali

Materials Science and Engineering Faculty Research & Creative Works

Efficient oxide scale removal is critical for maintaining surface quality and process efficiency in steel manufacturing. This study optimizes water jet descaling by evaluating the performance of flat and rotary jet nozzles under varying process parameters. Using a combined approach of experimental analysis and computational fluid dynamics, it investigates the influence of pressure (138–275 bar), lead angle (0°, 15°, 25°), working distance (50–100 mm), and spray angle (15°–25°) on descaling efficiency. Findings indicate that flat jet nozzles achieve superior performance at short working distances due to concentrated impact forces, while rotary jet nozzles sustain efficiency over extended distances through dynamic …

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Effect Of Gating Design On Filling And Inclusion Control In An Al-Killed Cr-Mo-Ni Steel, Kingsley T. Amatanweze, Koushik Balasubramanian, Soumava Chakraborty, Viraj A. Athavale, Mario F. Buchely, Laura N. Bartlett, Ronald J. O'Malley, Daniel M. Field, Krista R. Limmer, Katherine M. Sebeck Jan 2025

Effect Of Gating Design On Filling And Inclusion Control In An Al-Killed Cr-Mo-Ni Steel, Kingsley T. Amatanweze, Koushik Balasubramanian, Soumava Chakraborty, Viraj A. Athavale, Mario F. Buchely, Laura N. Bartlett, Ronald J. O'Malley, Daniel M. Field, Krista R. Limmer, Katherine M. Sebeck

Materials Science and Engineering Faculty Research & Creative Works

The effect of gating system design on the inclusion population and size distribution in an aluminum-killed low-alloy advanced high strength steel casting was studied. A mold with four different gating systems: pressurized and non-pressurized with side risers, naturally pressurized with a side riser, and naturally pressurized with a top riser, was designed using computational fluid dynamics and solidification software. The design allowed inclusion populations in castings produced with each gating system to be compared during the same pouring event. Samples taken from different positions just below the top surface of each casting were analyzed using an SEM/EDS system with automated …

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In-Situ Thermographic Monitoring And Numerical Simulations Of Laser-Foil-Printing Additive Manufacturing, Tunay Turk, Tao Liu, Chia Hung Hung, Richard Billo, Jonghyun Park, Ming C. Leu Jan 2025

In-Situ Thermographic Monitoring And Numerical Simulations Of Laser-Foil-Printing Additive Manufacturing, Tunay Turk, Tao Liu, Chia Hung Hung, Richard Billo, Jonghyun Park, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Laser-foil-printing (LFP) is an additive manufacturing (AM) technique offering advantages over traditional powder-based methods. A deeper understanding of the melt pool dynamics is crucial for optimizing process parameters and achieving high-quality builds. This paper presents a combined approach utilizing numerical simulations and in-situ thermographic monitoring to investigate the relationship between scanning strategies, melt pool dimensions, and cooling rate in LFP. The numerical simulations are employed to predict melt pool behavior using a time-dependent thermal finite element analysis (FEA). Results demonstrate that the simulations accurately predict melt pool dimensions, showing strong agreement with experimental data. Simultaneously, real-time melt pool dynamics were …

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Implementation Of Miniature Tensile Specimens In Mechanical Properties Assessment Of Directed Energy Deposited Ti-6al-4v: As-Built And Heat Treated, Saeid Alipour, Sung Heng Wu, Frank Liou, Arezoo Emdadi Jan 2025

Implementation Of Miniature Tensile Specimens In Mechanical Properties Assessment Of Directed Energy Deposited Ti-6al-4v: As-Built And Heat Treated, Saeid Alipour, Sung Heng Wu, Frank Liou, Arezoo Emdadi

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Within the last two decades, additive manufacturing (AM), a. k.a. 3D printing, has provided promising solutions for producing near-net-shape components with intricate geometries. From the material perspective, titanium alloys, one of humankind's most essential structural materials, are being considered the first candidate for AMed parts due to their unique characteristics in strength-weight-corrosion combinations. However, measuring the mechanical properties of designed geometry remains a challenge due to the ineffectiveness of conventional standard tensile specimens in assessing the site-specific and intricate geometries. In AM, the current approach often consists of evaluating standard-sized samples with the assumption that components with complex geometries possess …

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Experimental Study Of Defects In Coaxial Wire-Based Laser Metal Deposition, Remy Mathenia Jan 2025

Experimental Study Of Defects In Coaxial Wire-Based Laser Metal Deposition, Remy Mathenia

Doctoral Dissertations

This work seeks to improve the usability and capability of coaxial wire-based laser metal deposition (LMD) through the experimental study of process parameters on output geometry, directional effects, and defect formation. Wire-based LMD is a directed energy deposition (DED) strategy that uses a focused laser heat source to melt and fuse metal wire as it is deposited. This process is used to build parts layer-by-layer until a desired geometry is accomplished. LMD enables the creation of complex components at a high build rate with low material and energy waste. This work focuses on the deposition of titanium wire in the …

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