Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Aerospace Engineering (700)
- Manufacturing (207)
- Materials Science and Engineering (80)
- Physical Sciences and Mathematics (35)
- Ceramic Materials (24)
-
- Electrical and Computer Engineering (24)
- Metallurgy (19)
- Computer Sciences (16)
- Chemistry (11)
- Physics (11)
- Engineering Mechanics (8)
- Engineering Science and Materials (8)
- Aerodynamics and Fluid Mechanics (7)
- Chemical Engineering (7)
- Numerical Analysis and Scientific Computing (6)
- Civil and Environmental Engineering (5)
- Operations Research, Systems Engineering and Industrial Engineering (4)
- Materials Chemistry (3)
- Biology (2)
- Business (2)
- Education (2)
- Electromagnetics and Photonics (2)
- Life Sciences (2)
- Mathematics (2)
- Mining Engineering (2)
- Applied Mechanics (1)
- Architectural Engineering (1)
- Architecture (1)
- Keyword
-
- Additive manufacturing (42)
- Optimal Control (41)
- Neurocontrollers (26)
- Nonlinear Control Systems (23)
- Control System Synthesis (20)
-
- Adaptive Control (13)
- Stability (13)
- Feedback (11)
- Solid Freeform Fabrication (10)
- Laser metal deposition (9)
- Neural Nets (9)
- 3D printers (8)
- Additive Manufacturing (8)
- Distributed Parameter Systems (8)
- Dynamic Programming (8)
- Mechanical properties (8)
- Neural Networks (8)
- Neural networks (8)
- Robots (8)
- Aerospace Control (7)
- Deposition (7)
- Directed energy deposition (7)
- Learning Systems (7)
- Machine learning (7)
- Microstructure (7)
- Optimal control (7)
- Plasmonics (7)
- Position Control (7)
- Rapid Prototyping (7)
- Riccati Equations (7)
- Publication Year
Articles 31 - 60 of 1141
Full-Text Articles in Mechanical Engineering
Tunable Phase-Change Metasurfaces Coupled With Mid-Infrared Molecular Vibrations, Haotian Tang, Liliana Stan, David A. Czaplewski, Xiaodong Yang, Jie Gao
Tunable Phase-Change Metasurfaces Coupled With Mid-Infrared Molecular Vibrations, Haotian Tang, Liliana Stan, David A. Czaplewski, Xiaodong Yang, Jie Gao
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Chiral optical meta surfaces have emerged as a promising platform in coupling with molecular vibrational fingerprints through the enhanced light-matter interaction under different circularly polarized light illumination. This work reports the mode coupling between the mid-infrared phonon vibrations of polymethyl methacrylate (PMMA) molecules, and the thermally tunable chiral meta surfaces based on the phase-change material Ge₂Sb₂Te₅ (GST-225). Phase-change chiral meta surfaces with high circular dichroism (CD) in absorption and tunable plasmonic resonance in the frequency range of 48-56 THz are demonstrated, which covers the phonon vibrational frequency of PMMA molecules at 52 THz. The mode splitting features are observed in …
Ded Printing Process Modeling Using Metal Matrix Composites: In-Situ Feedstock Mixing With Variable Compositions And Empirical Validation, Muhammad Arif Mahmood, Sabin Mihai, Diana Chioibasu, Andrei C. Popescu, Frank Liou
Ded Printing Process Modeling Using Metal Matrix Composites: In-Situ Feedstock Mixing With Variable Compositions And Empirical Validation, Muhammad Arif Mahmood, Sabin Mihai, Diana Chioibasu, Andrei C. Popescu, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Directed Energy Deposition (DED) is a promising technology for producing metal matrix composites (MMXCs), but precise control over deposited layer dimensions, particularly in multi-material systems, remains difficult to achieve due to the complex interdependence of operating parameters such as laser parameters, feedstock flow rate, and beam energy attenuation. To address these problems, this work proposes an analytical model that predicts the width, height, and depth of the deposited layers using mixed feedstock compositions in-situ, with a focus on Inconel-718 and TiC MMXCs. The model takes into account variables such as laser power, feedstock density, and mixing ratios to improve layer …
Bending Fatigue In Additively Manufactured Metals: A Review Of Current Research And Future Directions, Md Bahar Uddin, Sriram Praneeth Isanaka, Frank Liou
Bending Fatigue In Additively Manufactured Metals: A Review Of Current Research And Future Directions, Md Bahar Uddin, Sriram Praneeth Isanaka, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Metal additive manufacturing (MAM), also referred to as 3D printing, has proven remarkable in the fabrication of complex metal components in multiple sectors. However, the assessment of this revolutionary process through bending fatigue is frequently impeded due to concerns about mechanical and physical conditions of the printed components. The unique layer-by-layer production process results in varied microstructures, anisotropy, and intrinsic defects that considerably differ from traditionally manufactured wrought metals. This review article aims to integrate and evaluate historical and contemporary research on the bending fatigue of additively manufactured materials. More specifically, the impact of process parameters, build orientation, surface conditions, …
Powder Bed Fusion Of Stainless Steel 304l-Nbc Nanocomposite Produced By Ball Milling Method Using A Laser Beam, Khalid Hussain Solangi, Junaid Iqbal Bhatti, Irfan Ali Tunio, Imdad Ali Memon, Temoor Abbas Larik, Lianyi Chen
Powder Bed Fusion Of Stainless Steel 304l-Nbc Nanocomposite Produced By Ball Milling Method Using A Laser Beam, Khalid Hussain Solangi, Junaid Iqbal Bhatti, Irfan Ali Tunio, Imdad Ali Memon, Temoor Abbas Larik, Lianyi Chen
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Metal powders with uniformly dispersed nanoparticles, suitable shape, and size for additive manufacturing (AM) processes are highly demanded. However, it is difficult to manufacture metal matrix nanocomposite powders (MMNCs) with uniform dispersion of nanoparticles, optimized shape, and size. This study used high-energy ball milling to disperse NbC nanoparticles with an average length of 400 nm (ex-situ reinforcement) in a Stainless Steel (SS) 304 L matrix. In detail, SS304L-5wt% NbC powders were ball-milled from 4 to 10 h. The results showed that the milled powder particles experienced significant cold-welding during the milling time of 4–6 h, with a wide size distribution. …
Tensile And Fatigue Properties Of Haynes ® 233 Manufactured By Wire-Arc Additive Manufacturing, Samuel Onimpa Alfred, Frank W. Liou, Mehdi Amiri
Tensile And Fatigue Properties Of Haynes ® 233 Manufactured By Wire-Arc Additive Manufacturing, Samuel Onimpa Alfred, Frank W. Liou, Mehdi Amiri
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Haynes® 233 is a newly developed nickel-based superalloy currently in the early stages of commercial adoption. With the growing interest in fabricating large and complex components using wire-arc additive manufacturing (WAAM), this alloy presents a promising option for industrial applications. This study investigates the microstructure, tensile, and fatigue properties of heat-treated (HT) WAAM Haynes ® 233 and compares them to its wrought counterpart. Yield strength (YS), ultimate tensile strength (UTS), and fatigue strength of WAAM Haynes ® 233 are 709.4 MPa, 890.1 MPa, and 253.8 MPa, respectively. These values indicate a 63.8 % increase in YS, a 1.11 % decrease …
Physics-Based Machine Learning Framework For Predicting Structure-Property Relationships In Ded-Fabricated Low-Alloy Steels †, Atiqur Rahman, Md Hazrat Ali, Asad Waqar Malik, Muhammad Arif Mahmood, Frank Liou
Physics-Based Machine Learning Framework For Predicting Structure-Property Relationships In Ded-Fabricated Low-Alloy Steels †, Atiqur Rahman, Md Hazrat Ali, Asad Waqar Malik, Muhammad Arif Mahmood, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The Directed Energy Deposition (DED) process has demonstrated high efficiency in manufacturing steel parts with complex geometries and superior capabilities. Understanding the complex interplays of alloy compositions, cooling rates, grain sizes, thermal histories, and mechanical properties remains a significant challenge during DED processing. Interpretable and data-driven modeling has proven effective in tackling this challenge, as machine learning (ML) algorithms continue to advance in capturing complex property structural relationships. However, accurately predicting the prime mechanical properties, including ultimate tensile strength (UTS), yield strength (YS), and hardness value (HV), remains a challenging task due to the complex and non-linear relationships among process …
Modification Of Tini Alloy By Fast Pulse Laser Heat Treatment, Yitao Chen, Mohammad Masud Parvez, Frank Liou
Modification Of Tini Alloy By Fast Pulse Laser Heat Treatment, Yitao Chen, Mohammad Masud Parvez, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this study, the effects of local heat treatment with fast pulse laser on thin TiNi shape memory alloy strip materials were investigated. Various materials characterization methods including optical microscope, scanning electron microscope, atomic force microscope, X-ray diffraction, differential scanning calorimetry, and Vickers hardness were used to identify the differences of microstructure, mechanical properties, and functional properties between regions inside and outside the laser-scanned region. The tensile test was also conducted for both the non-laser-scanned specimen and the laser-scanned specimen. The area covered by laser scanning shows great differences by possessing a more homogeneous austenite phase without shear bands and …
Digital Twins, Ai, And Cybersecurity In Additive Manufacturing: A Comprehensive Review Of Current Trends And Challenges, Md Sazol Ahmmed, Laraib Khan, Muhammad Arif Mahmood, Frank Liou
Digital Twins, Ai, And Cybersecurity In Additive Manufacturing: A Comprehensive Review Of Current Trends And Challenges, Md Sazol Ahmmed, Laraib Khan, Muhammad Arif Mahmood, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The development of Industry 4.0 has accelerated the adoption of sophisticated technologies, including Digital Twins (DTs), Artificial Intelligence (AI), and cybersecurity, within Additive Manufacturing (AM). Enabling real-time monitoring, process optimization, predictive maintenance, and secure data management can redefine conventional manufacturing paradigms. Although their individual importance is increasing, a consistent understanding of how these technologies interact and collectively improve AM procedures is lacking. Focusing on the integration of digital twins (DTs), modular AI, and cybersecurity in AM, this review presents a comprehensive analysis of over 137 research publications from Scopus, Web of Science, Google Scholar, and ResearchGate. The publications are categorized …
Experimental Study Of Process Parameter Effects On Internal Defects In Titanium Coaxial Wire-Based Laser Metal Deposition, Remy Mathenia, Braden Mclain, Todd Sparks, Frank Liou
Experimental Study Of Process Parameter Effects On Internal Defects In Titanium Coaxial Wire-Based Laser Metal Deposition, Remy Mathenia, Braden Mclain, Todd Sparks, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Wire-based laser metal deposition is an additive manufacturing process that can be used in the efficient manufacturing of complex structures. This paper utilizes a three-beam coaxial laser wire system to explore the effect of process parameters on the resultant deposition density. The reduction in or elimination of defects is important to the mechanical properties of the additively manufactured material and the widespread adoption of additive manufacturing processes. In this work, two-bead-wide walls were deposited under varying experimental conditions, including the traverse feed rate and workpiece illumination proportion. A method for calculating the bead pitch and layer height increment based on …
Impact Of Delayed Artificial Aging On Tensile Properties And Microstructural Evolution Of Directed Energy Deposited Scalmalloy®, Rachel Boillat-Newport, Sriram Praneeth Isanaka, Frank Liou
Impact Of Delayed Artificial Aging On Tensile Properties And Microstructural Evolution Of Directed Energy Deposited Scalmalloy®, Rachel Boillat-Newport, Sriram Praneeth Isanaka, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Scalmalloy® is a novel alloy designed to work with the unique processing inherent in additive manufacturing (AM). This alloy is post-processed using a single artificial aging treatment rather than a multistep heat treatment, as often noted in traditional manufacturing processes. Much of the literature details the impact of direct aging treatments around the temperature and time recommended by the manufacturer, 325 °C for 4 h; however, few studies have explored the impact of delayed artificial aging on the resulting mechanical and microstructural behavior. This study explored this missing link and determined the impact that the time between the fabrication of …
Multiphase Iterative Algorithm For Mixed-Integer Optimal Control, Chaoying Pei, Sixiong You, Yu Di, Ran Dai
Multiphase Iterative Algorithm For Mixed-Integer Optimal Control, Chaoying Pei, Sixiong You, Yu Di, Ran Dai
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Mixed-integer optimal control problems (MIOCPs) frequently arise in the domain of optimal control problems (OCPs) when decisions including integer variables are involved. However, existing state-of-the-art approaches for solving MIOCPs are often plagued by drawbacks such as high computational costs, low precision, and compromised optimality. In this study, we propose a novel multiphase scheme coupled with an iterative second-order cone programming (SOCP) algorithm to efficiently and effectively address these challenges in MIOCPs. In the first phase, we relax the discrete decision constraints and account for the terminal state constraints and certain path constraints by introducing them as penalty terms in the …
A Gaze-Driven Manufacturing Assembly Assistant System With Integrated Step Recognition, Repetition Analysis, And Real-Time Feedback, Haodong Chen, Niloofar Zendehdel, Ming C. Leu, Zhaozheng Yin
A Gaze-Driven Manufacturing Assembly Assistant System With Integrated Step Recognition, Repetition Analysis, And Real-Time Feedback, Haodong Chen, Niloofar Zendehdel, Ming C. Leu, Zhaozheng Yin
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Modern manufacturing faces significant challenges, including efficiency bottlenecks and high error rates in manual assembly operations. To address these challenges, we implement artificial intelligence (AI) and propose a gaze-driven assembly assistant system that leverages artificial intelligence for human-centered smart manufacturing. Our system processes video inputs of assembly activities using a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network for assembly step recognition, a Transformer network for repetitive action counting, and a gaze tracker for eye gaze estimation. The application of AI integrates the outputs of these tasks to deliver real-time visual assistance through a software interface that displays …
Experiment-Based Superposition Thermal Modeling Of Laser Powder Bed Fusion, Cody S. Lough, Tao Liu, Robert G. Landers, Douglas A. Bristow, James A. Drallmeier, Ben Brown, Edward C. Kinzel
Experiment-Based Superposition Thermal Modeling Of Laser Powder Bed Fusion, Cody S. Lough, Tao Liu, Robert G. Landers, Douglas A. Bristow, James A. Drallmeier, Ben Brown, Edward C. Kinzel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Parts experience significant local thermal variations during the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process, providing a potential source of defects. Near real-time thermal predictions can enable better process planning and facilitate corrections on subsequent layers to enable the engineering of laser parameter and scan path combinations that avoid defect inducing scenarios. This paper considers an experiment-based Discrete Green's Function (DGF) thermal model for temperature field prediction in LPBF. An analytical framework is developed and used to calculate an experimental DGF (i.e., powder bed's single pulse temperature response) from spatiotemporal Short-Wave Infrared (SWIR) camera data. The extracted …
Few-Shot Transfer Learning For Individualized Braking Intent Detection On Neuromorphic Hardware, Nathan A. Lutes, V. Sriram Siddhardth Nedendla, K. Krishnamurthy
Few-Shot Transfer Learning For Individualized Braking Intent Detection On Neuromorphic Hardware, Nathan A. Lutes, V. Sriram Siddhardth Nedendla, K. Krishnamurthy
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a Brain Chip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used group-level, models using electroencephalographic data. The efficacy of the method is studied on an advanced driver assist system related task of predicting braking intention. Approach. Data are collected from participants operating an NVIDIA JetBot on a testbed simulating urban streets for three different scenarios. Participants receive a braking indicator in the form of: (1) an audio countdown in a nominal baseline, stress-free environment; (2) an …
Oxidation–Reduction Of Ti-6al-4v In Direct Energy Deposition Subject To Minimum Argon Consumption, Bharadwaja Ragampeta, Prashansa Ragampeta, Todd Sparks, Frank Liou
Oxidation–Reduction Of Ti-6al-4v In Direct Energy Deposition Subject To Minimum Argon Consumption, Bharadwaja Ragampeta, Prashansa Ragampeta, Todd Sparks, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Ti-6Al-4V is a well-known alloy for its low density and excellent corrosion resistance, making it popular in aerospace, marine, medical, and automotive applications. However, at elevated temperatures, the alloy forms oxides, leading to embrittlement. In additive manufacturing, particularly in the direct energy deposition (DED) process, which involves high temperatures, the alloy experiences oxidation. An inert gas chamber provides shielding during the process but limits the size of the manufactured components, and deposition in a vacuum chamber can alter the chemical composition of the alloy. Local shielding is a technique generally used for such applications, but it uses a high volume …
A Comprehensive Study Of Cooling Rate Effects On Diffusion, Microstructural Evolution, And Characterization Of Aluminum Alloys, Atiqur Rahman, Sriram Praneeth Isanaka, Frank Liou
A Comprehensive Study Of Cooling Rate Effects On Diffusion, Microstructural Evolution, And Characterization Of Aluminum Alloys, Atiqur Rahman, Sriram Praneeth Isanaka, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Cooling Rate (CR) definitively influences the microstructure of metallic parts manufactured through various processes. Factors including cooling medium, surface area, thermal conductivity, and temperature control can influence both predicted and unforeseen impacts that then influence the results of mechanical properties. This comprehensive study explores the impact of CRs in diffusion, microstructural development, and the characterization of aluminum alloys and the influence of various manufacturing processes and post-process treatments, and it studies analytical models that can predict their effects. It examines a broad range of CRs encountered in diverse manufacturing methods, such as laser powder bed fusion (LPBF), directed energy deposition …
Circular Dichroism In Achiral Metasurfaces Induced By Spatially Selective Coupling With Molecules, Baojuan Han, Xiaodong Yang, Jie Gao
Circular Dichroism In Achiral Metasurfaces Induced By Spatially Selective Coupling With Molecules, Baojuan Han, Xiaodong Yang, Jie Gao
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Achiral metasurfaces with near-field optical chirality have attracted great attention in molecular sensing and chiral emission control. Here, the circular dichroism (CD) response of an achiral metasurface induced by spatially selective coupling with polymethyl methacrylate (PMMA) molecules is demonstrated. A designed achiral metasurface with a V-shaped resonator exhibits large optical chirality with a strongly dissymmetric distribution under circular polarization. By introducing a PMMA molecule layer on top of the metasurface, which covers the area with large optical chirality, CD in absorption of 0.38 and a dissymmetric factor of optical chirality gc of 0.16 are obtained. Furthermore, an analysis of the …
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
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 …
Anisotropic And Temperature-Tunable Second-Harmonic Vortex Generation In Ferroelectric Nbocl2 Holograms, Jayanta Deka, Xiaodong Yang, Jie Gao
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 …
Machine Learning Approach For Defect Prediction In Metal 3d Printing For Aerospace Applications, Yerlik Gabdulla, Md Hazrat Ali, Frank Liou, Essam Shehab
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 …
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
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 …
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
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 …
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
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 …
Anisotropic Third-Harmonic Vortex Beam Generation With Ultrathin Germanium Arsenide Fork Gratings, Jayanta Deka, Jie Gao, Xiaodong Yang
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 …
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
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 …
Generative Adversarial Networks For Dimensionality Reduction In Evtol Aircraft Takeoff Trajectory Optimization, Samuel Sisk, Farzaam Khorasani-Gerdehkouhi, Abdulaziz Abutunis, K. Chandrashekhara, Xiaosong Du
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 …
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
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 …
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
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 …
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
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 …
Tensile Behavior Of Directed Energy Deposited Bi-Metallic Ti-Ni-Based Alloy At Interfacial Area, Yitao Chen, Cesar Ortiz Rios, Frank Liou
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 …