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Articles 31 - 60 of 763
Full-Text Articles in Mechanical Engineering
User Interface And Watchstation Improvements Required For Multi-Vehicle Usv Operations, Val Schmidt, Joshua Bergeron
User Interface And Watchstation Improvements Required For Multi-Vehicle Usv Operations, Val Schmidt, Joshua Bergeron
Faculty Publications
In October 2024, the University of New Hampshire and NOAA’s Uncrewed Systems Office embarked on a mapping mission in the Gulf of Maine, simultaneously operating two DriX Un-crewed Surface Vehicles. Goals of the project were focused on testing hypotheses related to concepts of operation, including the safety of operations, cognitive loading of operators, management of vehicle endurance, vehicle logistics, maintenance and field support, refueling and a host of others.
A Gas-Tight Bonding/Sealing Of Different Bulk Ceramics For Robust Oxygen Separation At Ultra-High Temperatures, Guoan Wang, Xingjian Xue
A Gas-Tight Bonding/Sealing Of Different Bulk Ceramics For Robust Oxygen Separation At Ultra-High Temperatures, Guoan Wang, Xingjian Xue
Faculty Publications
Oxygen transport membrane (OTM) is an economic technology for oxygen separation and high-purity oxygen production. To mitigate various issues induced by high temperatures, intermediate temperature OTM technology has been pursued in recent years. However, in certain circumstances, high operating temperatures are unavoidable, such as in situ oxygen production using OTMs for direct oxy-combustion. Nevertheless, the lack of reliable high temperature gas-tight sealing imposes great challenges on OTM technology for such applications. Herein, a novel sealing strategy is developed to obtain a gas-tight bonding/sealing of two different bulk ceramics using ceramic slurry in combination with phase inversion process. The sealing strategy …
Online Cyber-Physical Neural Network Model For Real-Time Hybrid Simulation, Faisal Nissar Malik, Liang Cao, James Ricles, Austin Downey
Online Cyber-Physical Neural Network Model For Real-Time Hybrid Simulation, Faisal Nissar Malik, Liang Cao, James Ricles, Austin Downey
Faculty Publications
Real-time hybrid simulation (RTHS) is an experimental testing methodology that divides a structural system into an analyticaland an experimental substructure. The analytical substructure is modeled numerically, and the experimental substructure ismodeled physically in the laboratory. The two substructures are kinematically linked together at their interface degrees of freedom,and the coupled equations of motion are solved in real-time to obtain the response of the complete system. A key challenge inapplying RTHS to large or complex structures is the limited availability of physical devices, which makes it difficult to representall required experimental components simultaneously. The present study addresses this challenge by introducing …
A New Low-Rate Stable Hydrogel Cathode For Aqueous Zn-Ion Batteries, Roya Rajabi, Shichen Sun, Jamil A. Khan, Morgan Stefik, Kevin Huang
A New Low-Rate Stable Hydrogel Cathode For Aqueous Zn-Ion Batteries, Roya Rajabi, Shichen Sun, Jamil A. Khan, Morgan Stefik, Kevin Huang
Faculty Publications
Aqueous Zn-ion batteries (ZIBs) are attractive candidates for large-scale energy storage owing to the abundance, low cost, and intrinsic safety of Zn metal. However, their practical application is hindered by poor cycle stability, especially at low current densities, due to cathode dissolution and limited electrochemically active sites (EAS). Herein, a hydrogel-based cathode comprising ammonium vanadate, carbon black, and a Zn-ion-conducting carboxymethyl chitosan–acrylamide hydrogel matrix doped with Zn(ClO4)2 is reported. This design establishes a continuous Zn-ion-conducting network, thereby maximizing EAS density throughout the electrode volume. The ZIB with the hydrogel cathode exhibits outstanding cycling stability, with 77% capacity retention after 2000 …
A Comprehensive Assessment And Benchmark Studyof Large Atomistic Foundation Models For Phonons, Md Zaibul Anam, Ogheneyoma Aghoghovbia, Mohammed Al-Fahdi, Lingyu Kong, Victor Fung, Ming Hu
A Comprehensive Assessment And Benchmark Studyof Large Atomistic Foundation Models For Phonons, Md Zaibul Anam, Ogheneyoma Aghoghovbia, Mohammed Al-Fahdi, Lingyu Kong, Victor Fung, Ming Hu
Faculty Publications
The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces. While their capability for modeling phonon properties is emerging, systematic benchmarking across chemically diverse systems remains limited. We evaluate six recent uMLPs—EquiformerV2, MatterSim, MACE, and CHGNet—on 2429 crystalline materials from the Open Quantum Materials Database. Models were used to compute atomic forces in displaced supercells, derive interatomic force constants (IFCs), and predict phonon properties including lattice thermal conductivity (LTC), compared with density functional theory and experimental data. The EquiformerV2 pretrained model trained on the OMat24 dataset exhibits strong …
Integration Of Sco2 Brayton Cycles With Carbon Capture Systems, Nathan C. Stearns, Rajarshi Roy, Brian Schooff, Andrew Chiodo, Andrew R. Fry, Brian D. Iverson
Integration Of Sco2 Brayton Cycles With Carbon Capture Systems, Nathan C. Stearns, Rajarshi Roy, Brian Schooff, Andrew Chiodo, Andrew R. Fry, Brian D. Iverson
Faculty Publications
Increasing global energy consumption and greater market penetration of intermittent energy sources require a baseline power source to enable renewable energies. Here, a case is made for pairing supercritical CO2 Brayton cycles with carbon capture to create low-emission, high-efficiency, combustion-based power generation systems. Pairing carbon capture and storage (CCS) systems with supercritical carbon dioxide (sCO2) Brayton cycles enables the reduction of greenhouse gas emissions in combustion systems, but with an associated energy cost. Three different representative models of CCS systems (oxyfuel combustion, amine scrubbing, and cryogenic carbon capture) are considered for pairing with an sCO2 Brayton cycle, …
Machine-Learning-Assisted Discovery Of Lattice Dynamics Signatures Of Sodium Superionic Conductors, Ogheneyoma Aghoghovbia, Riccardo Rurali, Mohammed Al-Fahdi, Joshua Ojih, De-En Jiang, Ming Hu
Machine-Learning-Assisted Discovery Of Lattice Dynamics Signatures Of Sodium Superionic Conductors, Ogheneyoma Aghoghovbia, Riccardo Rurali, Mohammed Al-Fahdi, Joshua Ojih, De-En Jiang, Ming Hu
Faculty Publications
Sodium superionic conductors are key to the development of all-solid-state sodium batteries. Discovery of new superionic conductors has traditionally relied on insights from material defect chemistry and the transition/hopping theory, while the role of lattice vibrations, i.e., phonons, remains underexplored. We identify key lattice dynamics signatures that govern ionic conductivity by analyzing the phonon mean squared displacement (MSD) of Na+ ions. By high-throughput screening of a dataset of 3903 Na-containing structures, we establish a strong positive correlation between phonon MSD and diffusion coefficients, providing a quantitative correlation between lattice dynamics and ion transport. To accelerate this discovery, we incorporate …
Wind Turbine Rotor Design Using High-Fidelity Aerostructural Optimization, Marco Mangano, Sicheng He, Yingqian Liao, Denis-Gabriel Caprace, Andrew Ning, Joaquim R. R. A. Martins
Wind Turbine Rotor Design Using High-Fidelity Aerostructural Optimization, Marco Mangano, Sicheng He, Yingqian Liao, Denis-Gabriel Caprace, Andrew Ning, Joaquim R. R. A. Martins
Faculty Publications
Large wind turbines yield more energy but demand careful aeroelastic blade design. Coupled multiphysics design strategies can reduce wind energy costs exploiting fluid-structure interactions. This work presents the first high-fidelity aerostructural optimization study of a large wind turbine rotor.We use blade-resolved fluid dynamics and structural solvers in a monolithic gradient-based optimization framework to explore steady-state torque and blade mass trade-offs. The coupled-adjoint approach computes gradients efficiently, enabling the optimization of over 100 structural and geometric parameters simultaneously. Our optimization study modifies a DTU 10 MW benchmark with a simplified structure and isotropic material properties. The tightly coupled optimizations increase torque …
Exploring Different Metal-Oxide Cathode Materials For Structural Lithium-Ion Batteries Using Dip-Coating, David Petrushenko, Thomas Burns, Paul Ziehl, Ralph E. White, Paul T. Coman
Exploring Different Metal-Oxide Cathode Materials For Structural Lithium-Ion Batteries Using Dip-Coating, David Petrushenko, Thomas Burns, Paul Ziehl, Ralph E. White, Paul T. Coman
Faculty Publications
In this study, a selection of active materials were coated onto commercially available intermediate modulus carbon fibers to form and analyze the performance of novel composite cathodes for structural power composites. Various slurries containing polyvinylidene fluoride (PVDF), active material powders, 1-methyl-2-pyrrolidone (NMP) and carbon black (CB) were used to coat carbon fiber tows by immersion. Four active materials—lithium cobalt oxide (LCO), lithium iron phosphate (LFP), lithium nickel manganese cobalt oxide (NMC), and lithium nickel cobalt aluminum oxide (NCA)—were individually tested to assess their electrochemical reversibility. The cells were prepared with a polymer separator and liquid electrolytes and assembled in 2025-coin …
Impact Of Non-Uniform Surface Temperature On The Apparent Radiative Properties Of Cavity Receivers, Ehsan Mofidipour, Matthew R. Jones, Brian D. Iverson
Impact Of Non-Uniform Surface Temperature On The Apparent Radiative Properties Of Cavity Receivers, Ehsan Mofidipour, Matthew R. Jones, Brian D. Iverson
Faculty Publications
Radiative surface properties play a critical role in the design, analysis and optimization of solar–thermal systems. Cavity receivers increase the efficiency of solar–thermal energy systems through the cavity effect. The cavity effect refers to increased absorption of radiation due to multiple reflections within a cavity. Apparent radiative surface properties of a cavity characterize the effective interactions of radiation passing through an imaginary surface covering the cavity aperture. In this study, we investigate the extent to which the apparent emissivity of a cavity with a non-uniform surface temperature profile may be estimated using an isothermal enclosure model. A cylindrical cavity was …
Quantifying Electrokinetics Of Naca0.6V6O163h2O Cathode In Aqueous Zinc-Ion Batteries With Znso4 Electrolyte, Shichen Sun, Boyu Wang, Kevin Huang
Quantifying Electrokinetics Of Naca0.6V6O163h2O Cathode In Aqueous Zinc-Ion Batteries With Znso4 Electrolyte, Shichen Sun, Boyu Wang, Kevin Huang
Faculty Publications
Aqueous zinc-ion batteries (AZIBs) have been actively studied in recent years as a promising solution for next-generation stationary energy storage due to their inherent safety, low cost, and high energy density. However, their practical deployment remains hindered by the limited cycling stability of cathode materials. Overcoming this challenge requires a detailed understanding of cathodic electrokinetics and degradation mechanisms. In this study, we investigate the electrokinetic behavior of a NaCa0.6V6O163H2O (NaCaVO) cathode in ZnSO4 electrolyte through a combined application of the galvanostatic intermittent titration technique (GITT) and electrochemical impedance spectroscopy (EIS). For the …
Quantifying Electrokinetics Of Naca0.6V6O16·3h2O Cathode In Aqueous Zinc-Ion Batteries With Znso4 Electrolyte, Shichen Sun, Boyu Wang, Kevin Huang
Quantifying Electrokinetics Of Naca0.6V6O16·3h2O Cathode In Aqueous Zinc-Ion Batteries With Znso4 Electrolyte, Shichen Sun, Boyu Wang, Kevin Huang
Faculty Publications
Aqueous zinc-ion batteries (AZIBs) have been actively studied in recent years as a promising solution for next-generation stationary energy storage due to their inherent safety, low cost, and high energy density. However, their practical deployment remains hindered by the limited cycling stability of cathode materials. Overcoming this challenge requires a detailed understanding of cathodic electrokinetics and degradation mechanisms. In this study, we investigate the electrokinetic behavior of a NaCa0.6V6O16·3H2O (NaCaVO) cathode in ZnSO4 electrolyte through a combined application of the galvanostatic intermittent titration technique (GITT) and electrochemical impedance spectroscopy (EIS). For …
A Perovskite Nanocomposite And Self-Assembled Nanoparticle-Decorated Cathode For Low Temperature Sofcs, Chunyang Yang, Guoan Wang, Xingjian Xue
A Perovskite Nanocomposite And Self-Assembled Nanoparticle-Decorated Cathode For Low Temperature Sofcs, Chunyang Yang, Guoan Wang, Xingjian Xue
Faculty Publications
One-pot route synthesis of an A-site Sm-doped simple perovskite with nominal composition Sm0.10Ba0.90Co0.8Fe0.2O3−δ leads to a novel perovskite nanocomposite containing ∼90% A-site cation deficient cubic simple perovskite Ba0.925(Co/Fe)0.962Sm0.038O3−δ and ∼10% orthorhombic layered perovskite SmBa(Co/Fe)2O5+δ. The synergy of the two phases in the nanocomposite results in high electrochemical kinetic properties at low temperatures. With the novel perovskite nanocomposite, a surface nanoparticle-decorated nanocomposite cathode is self-assembled through a one-step sintering process. The corresponding anode-supported cell delivers a peak power density of 1271 mW cm−2 …
Machine Tool Interoperability In Smart Manufacturing And Industry 4.0, M. R. Mccormick, Mohammed Shafae, Thorsten Wuest
Machine Tool Interoperability In Smart Manufacturing And Industry 4.0, M. R. Mccormick, Mohammed Shafae, Thorsten Wuest
Faculty Publications
Real-time decision making is supported by data-hungry emerging technologies such as machine learning and digital twins. Innovations in manufacturing process control utilizing these technologies are constrained by interoperability. Marketing materials, sales pitches, and academic literature portray interoperability on the factory floor as seamless and robust. However, this study demonstrates that in spite of plentiful mature standards, interoperability on the factory floor is neither seamless nor robust. To exemplify interoperability in the context of an established and widely adopted standard, this study analyzes the interoperability of machine tools produced by a premier equipment builder which has exceeded US$1 billion in sales …
Feedback Parameters For A Closed-Loop Multiple-Input Multiple-Output Model Of The Upper Limb, Ian Syndergaard, Daniel B. Free, Dario Farina, Steven Knight Charles
Feedback Parameters For A Closed-Loop Multiple-Input Multiple-Output Model Of The Upper Limb, Ian Syndergaard, Daniel B. Free, Dario Farina, Steven Knight Charles
Faculty Publications
Both closed-loop models and multi-input multi-output (MIMO) models of the neuromusculoskeletal system of the upper limb are important for simulating and understanding motor control. Yet no large-scale linear neuromusculoskeletal models of the upper limb that are both closed-loop and MIMO have been developed. The primary difficulty in creating such models is choosing appropriate feedback parameters (such as feedback gains and delays), as such a collection of parameters is not available in the literature. The purpose of this work is to 1) present a method for developing MIMO models of short-loop afferent feedback and 2) offer estimates of average feedback parameter …
Human Gut Commensal Alistipes Timonensis Modulates The Host Lipidome And Delivers Anti-Inflammatory Outer Membrane Vesicles To Suppress Colitis In An Il10-Deficient Mouse Model, Ethan Older, Mary K. Mitchell, Andrew Campbell, Xiaoying Lian, Michael Madden, Yuzhen Wang, Lauren E. Van De Wal, Thelma Zaw, Brandon N. Vanderveen, Rodney Tatum, E. Angela Murphy, Yan-Hua Chen, Daping Fang, Melissa Ellermann, Jie Li
Human Gut Commensal Alistipes Timonensis Modulates The Host Lipidome And Delivers Anti-Inflammatory Outer Membrane Vesicles To Suppress Colitis In An Il10-Deficient Mouse Model, Ethan Older, Mary K. Mitchell, Andrew Campbell, Xiaoying Lian, Michael Madden, Yuzhen Wang, Lauren E. Van De Wal, Thelma Zaw, Brandon N. Vanderveen, Rodney Tatum, E. Angela Murphy, Yan-Hua Chen, Daping Fang, Melissa Ellermann, Jie Li
Faculty Publications
Correlative studies have linked human gut microbes to specific health conditions. Alistipes is one such microbial genus negatively linked to inflammatory bowel disease (IBD). However, the protective role of Alistipes in IBD is understudied, and the underlying molecular mechanisms remain unknown. In this study, colonization of Il10-deficient mice with Alistipes timonensis DSM 27924 delays colitis development. Colonization does not significantly alter the gut microbiome composition, but instead shifts the host plasma lipidome, increasing phosphatidic acids while decreasing triglycerides. Outer membrane vesicles (OMVs) derived from Alistipes are detected in the plasma of colonized mice, carrying potentially immunomodulatory metabolites into the …
Surface Resistivity Correlation To Nano-Defects In Laser Powder Bed Fused Molybdenum (Mo)-Silicon Carbide (Sic) Alloys, Andrew Mason, Larry W. Burggraf, Ryan A. Kemnitz, Nate Ellsworth
Surface Resistivity Correlation To Nano-Defects In Laser Powder Bed Fused Molybdenum (Mo)-Silicon Carbide (Sic) Alloys, Andrew Mason, Larry W. Burggraf, Ryan A. Kemnitz, Nate Ellsworth
Faculty Publications
The integration of Silicon Carbide (SiC) nanoparticles into Laser Powder Bed Fusion (LB-PBF) Molybdenum (Mo) printing represents a significant advancement in refractory metal additive manufacturing. Our investigation examined how varying SiC nanoparticle sizes affect the microstructural and electrical properties of LB-PBF-printed molybdenum components while maintaining a 0.01 mass fraction of Mo. At an Linear Energy Densities (LED) of 1.8 J/mm, the addition of 80 nm SiC particles achieved a 46% reduction in porosity, while sheet resistance decreased by 6% at LED of 2.0 J/mm with 80 nm SiC particles. These performance improvements stem from several mechanisms: SiC particles serve as …
Untethered Isoperimetric Robotic Truss For Lunar Applications, Mihai Stanciu, Spencer Stowell, Isaac Weaver, Adam Rose, Chris Paul, James Wade, Ashleigh Cerven, Annie O'Bryan, Brian Bodily, Logan Yang, Nathan Usevitch
Untethered Isoperimetric Robotic Truss For Lunar Applications, Mihai Stanciu, Spencer Stowell, Isaac Weaver, Adam Rose, Chris Paul, James Wade, Ashleigh Cerven, Annie O'Bryan, Brian Bodily, Logan Yang, Nathan Usevitch
Faculty Publications
We introduce a robotic system designed to function as a lightweight, modular, and reconfigurable structure on the Moon. This robust system consists of truss-like robotic triangles, each formed by a continuous inflated fabric tube routed through two robotic roller units and a connecting unit. When deflated, these triangles can be compacted to roughly the volume of the roller units, offering an advantageous stowed-to-deployed volume ratio of 1 to 6.24. Upon inflation, the roller units pinch the tubes, creating corners by reducing the bending stiffness of the tube. Once fully deployed, electric motors move the robotic roller units along the tube, …
Review Of Tethered Unmanned Aerial Vehicles: Building Versatile And Robust Tethered Multirotor Uav System, Dario Handrick, Mattie Eckenrode, Junsoo Lee
Review Of Tethered Unmanned Aerial Vehicles: Building Versatile And Robust Tethered Multirotor Uav System, Dario Handrick, Mattie Eckenrode, Junsoo Lee
Faculty Publications
This paper presents a comprehensive review of tethered unmanned aerial vehicles (UAVs), focusing on their challenges and potential applications across various domains. We analyze the dynamic characteristics of tethered UAV systems and address the unique challenges they present, including complex tether dynamics, impulsive forces, and entanglement risks. Additionally, we explore application-specific challenges in areas such as payload transportation and ground-connected systems. The review also examines existing tethered UAV testbed designs, highlighting their strengths and limitations in both simulation and experimental settings. We discuss advancements in multi-UAV cooperation, ground–air collaboration through tethers, and the integration of retractable tether systems. Moreover, we …
Graphics Processing Unit-Enabled Path Planning Based On Global Evolutionary Dynamic Programming And Local Genetic Algorithm Optimization, Junlin Ou, Ge Song, Yi Wang
Graphics Processing Unit-Enabled Path Planning Based On Global Evolutionary Dynamic Programming And Local Genetic Algorithm Optimization, Junlin Ou, Ge Song, Yi Wang
Faculty Publications
This paper presents a novel path planning method for real-time robotic path planning in a dynamic environment involving moving obstacles. It combines on a holistic platform a global approach to rapidly generate initial paths of prominent diversity and a heuristic approach to enable local path refinement for enhanced computational efficiency, exploration, and robustness. The global approach innovates a formulation that treats a path planning problem with a visibility graph as a Markov decision process and decomposes the process into many subproblems. A new evolutionary dynamic programming approach (EDP) is proposed to solve these subproblems in an iterative manner using …
Towards Human Modeling For Human-Robot Collaboration And Digital Twins In Industrial Environments: Research Status, Prospects, And Challenges, Guoyi Xia, Zied Gharairi, Thorsten Wuest, Karl Hribernik, Aaron Heuermann, Furui Liu, Hui Liu, Klaus-Dieter Thoben
Towards Human Modeling For Human-Robot Collaboration And Digital Twins In Industrial Environments: Research Status, Prospects, And Challenges, Guoyi Xia, Zied Gharairi, Thorsten Wuest, Karl Hribernik, Aaron Heuermann, Furui Liu, Hui Liu, Klaus-Dieter Thoben
Faculty Publications
Human-Robot Collaboration (HRC) and Digital Twins (DT) have significantly advanced industrial development and digital transformation. Human representations and models are essential in Industry 5.0, where human-centric is one of the key features. Despite the growing interest in human models for HRC and DT, a comprehensive overview of these models and enabling technologies currently needs to be provided. This paper aims to present the research status, prospects, applications, and challenges of human modeling for HRC and DT in industrial environments. This paper adopts a Systematic Literature Review (SLR) approach. Moreover, a framework is proposed to systematize human modeling aspects, the technologies …
Mechanism Of Property Enhancement Of Cu−Ti Alloys Via Microalloying With Cr And Mg Elements, Huan Wei, Hong Wei, Hua-Yun Du, Qian Wang, Cai-Zhi Zhou, Ying-Hui Weu, Li-Feng Hou
Mechanism Of Property Enhancement Of Cu−Ti Alloys Via Microalloying With Cr And Mg Elements, Huan Wei, Hong Wei, Hua-Yun Du, Qian Wang, Cai-Zhi Zhou, Ying-Hui Weu, Li-Feng Hou
Faculty Publications
The effect of adding Cr and Mg on the microstructure and properties of Cu−Ti alloys was examined. Cu−Ti−Cr−Mg alloys were fabricated using vacuum induction melting. The microstructure and phase composition of Cu−Ti−Cr−Mg alloys in different aging states were characterized. Additionally, the hardness and electrical conductivity of the materials were investigated. Results show that the precipitation pattern in Cu−Ti−Cr−Mg alloys resembled that of binary Cu−Ti alloys, with Cr and Ti forming the intermetallic compound of Cr2Ti during casting. The introduction of Cr and Mg increased the hardness of the alloy. Increasing the Mg content in the Cu−Ti−Cr−Mg alloy led to grain …
Open Accessarticle Crystal Plasticity Modeling Of Dislocation Density Evolution In Cellular Dislocation Structures, Md Mahabubur Rohoman, Caizhi Zhou
Open Accessarticle Crystal Plasticity Modeling Of Dislocation Density Evolution In Cellular Dislocation Structures, Md Mahabubur Rohoman, Caizhi Zhou
Faculty Publications
The complex thermal cycles during the solidification process in metal additive manufacturing (AM) lead to the formation of high-density dislocation networks, organizing into submicron-scale cellular structures. These ultrafine structures are recognized as crucial for enhancing the mechanical properties of AM metals. In this study, we investigate the evolution of dislocation density within these cellular structures under plastic deformation and its impact on mechanical response using dislocation density-based crystal plasticity finite element (CPFE) modeling. The model incorporates the evolution of both statistically stored dislocation (SSD) and geometrically necessary dislocation (GND). Our simulations reveal that the yield and flow stresses of dislocation …
Wind-Resilient Solar: Harnessing Cfd For Enhanced Load Estimation, Aly Mousaad Aly
Wind-Resilient Solar: Harnessing Cfd For Enhanced Load Estimation, Aly Mousaad Aly
Faculty Publications
Solar panels are a cornerstone of renewable energy infrastructure, playing a pivotal role in global sustainability efforts. To ensure their resilience and long-term viability, accurate wind load estimations are essential for designing supporting structures, which account for nearly 50% of their total cost. However, traditional building codes lack comprehensive guidance for solar panels, resulting in inconsistent estimations due to discrepancies in scaled wall-bounded wind tunnel testing methodologies. These inaccuracies pose safety risks, increase costs, and hinder adoption. Emerging technologies like computational fluid dynamics (CFD) simulations offer a promising alternative by enabling full-scale analysis under realistic conditions of complete turbulence. This …
Advancing Solar Farm Resilience: Cfd-Driven Wind Load Optimization, Aly Mousaad Aly
Advancing Solar Farm Resilience: Cfd-Driven Wind Load Optimization, Aly Mousaad Aly
Faculty Publications
This study investigates wind load design methods for ground-mounted solar panels and arrays by comparing Computational Fluid Dynamics (CFD) simulations with design standards. A case study of a solar farm impacted by Hurricane Maria examines the effects of elevation height, tilt angle, and variations in the American Society of Civil Engineers (ASCE) standards on wind loads and structural failure. Turbulence models, including Reynolds Stress Model, k–ε Model, and Large Eddy Simulation (LES), are used to analyze wind pressures, lift, drag, and peak pressures. Results show Phase 1 experienced higher wind loads than Phase 2 due to design differences. A cost-benefit …
New Method Of Impact Localization On Plate-Like Structures Using Deep Learning And Wavelet Transform, Asaad Migot, Ahmed Saaudi, Victor Giurgiutiu
New Method Of Impact Localization On Plate-Like Structures Using Deep Learning And Wavelet Transform, Asaad Migot, Ahmed Saaudi, Victor Giurgiutiu
Faculty Publications
This paper presents a new methodology for localizing impact events on plate-like structures using a proposed two-dimensional convolutional neural network (CNN) and received impact signals. A network of four piezoelectric wafer active sensors (PWAS) was installed on the tested plate to acquire impact signals. These signals consisted of reflection waves that provided valuable information about impact events. In this methodology, each of the received signals was divided into several equal segments. Then, a wavelet transform (WT)-based time-frequency analysis was used for processing each segment signal. The generated WT diagrams of these segments’ signals were cropped and resized using MATLAB code …
Real-Time Defect Detection And Classification In Robotic Assembly Lines: A Machine Learning Framework, Fadi El Kalach, Mojtaba Farahani, Thorsten Wuest, Ramy Harik
Real-Time Defect Detection And Classification In Robotic Assembly Lines: A Machine Learning Framework, Fadi El Kalach, Mojtaba Farahani, Thorsten Wuest, Ramy Harik
Faculty Publications
Manufacturing systems have witnessed a significant transformation with the introduction of Industry 4.0, introducing new capabilities with the emergence of new technologies. One such instance is the proliferation of sensors enabling the generation and acquisition of vast amounts of data, leading to advancements in Artificial Intelligence (AI) for manufacturing. One field profiting from this is that of Time Series Analytics (TSC) which includes forecasting and classification. TSC can be crucial for fault detection and diagnosis in manufacturing systems. However, there are still challenges in utilizing manufacturing datasets to train and deploy classification algorithms for real time classification. As such this …
Time-Series Forecasting In Smart Manufacturing Systems: An Experimental Evaluation Of The State-Of-The-Art Algorithms, Mojaba A. Farahani, Fadi El Kalach, Austin Harper, M.R. Mccormick, Ramy Harik, Thorsten Wuest
Time-Series Forecasting In Smart Manufacturing Systems: An Experimental Evaluation Of The State-Of-The-Art Algorithms, Mojaba A. Farahani, Fadi El Kalach, Austin Harper, M.R. Mccormick, Ramy Harik, Thorsten Wuest
Faculty Publications
Time-Series Forecasting (TSF) is a growing research area across various domains including manufacturing. Manufacturing can benefit from Artificial Intelligence (AI) and Machine Learning (ML) innovations for TSF tasks. Although numerous TSF algorithms have been developed and proposed over the past decades, the critical validation and experimental evaluation of the algorithms hold substantial value for researchers and practitioners and are missing to date. This study aims to fill this research gap by providing a rigorous experimental evaluation of the state-of-the-art TSF algorithms on thirteen manufacturing-related datasets with a focus on their applicability in smart manufacturing environments. Each algorithm was selected based …
Friction-Based Recycling: An Evaluation Of Friction Extrusion For Fabricating Ti-6al-4 V Wire Fabricated From Machining Chip Feedstock, Devesh Kumar Chouhan, Mageshwari Komarasamy, Scott B. Taysom, Nicole R. Overman, Nathan L. Canfield, Timothy J. Roosendaal, Anthony P. Reynolds, Scott A. Whalen
Friction-Based Recycling: An Evaluation Of Friction Extrusion For Fabricating Ti-6al-4 V Wire Fabricated From Machining Chip Feedstock, Devesh Kumar Chouhan, Mageshwari Komarasamy, Scott B. Taysom, Nicole R. Overman, Nathan L. Canfield, Timothy J. Roosendaal, Anthony P. Reynolds, Scott A. Whalen
Faculty Publications
Titanium and its alloys are used in aviation and automobile industries due to their remarkable strength to weight ratio, but machining loss commonly is high with ~ 80 wt% of the material being converted to scrap. Recycling post-consumer Ti scrap directly into solid bulk products is a potential solution for repurposing valuable material. Further, eliminating fresh Ti sponge during recycling might lead to lower energy and greenhouse gas emissions. In this study, a solid-phase process known as friction extrusion was utilized to recycle Ti-6Al-4 V machining chips into solid wires which could be used as feedstock in additive manufacturing. The …
Potential Of Individual Upper-Limb Muscles To Contribute To Postural Tremor: Simulations From Neural Drive To Joint Rotation, Spencer A. Baker, Landon J. Beutler, Daniel B. Free, Dario Farina, Steven Knight Charles
Potential Of Individual Upper-Limb Muscles To Contribute To Postural Tremor: Simulations From Neural Drive To Joint Rotation, Spencer A. Baker, Landon J. Beutler, Daniel B. Free, Dario Farina, Steven Knight Charles
Faculty Publications
Background: It is unclear which muscles contribute most to tremor and should therefore be targeted by tremor suppression methods. Previous studies used mathematical models to investigate how upper-limb biomechanics affect muscles’ potential to generate tremor. These investigations yielded principles, but the models included at most only 15 muscles. Here we expand previous models to include 50 upper-limb muscles, simulate tremor propagation, and test the validity of the previously postulated principles. Methods: Tremor propagation was characterized using the gains between tremorogenic neural drive to the 50 muscles (inputs) and tremulous joint rotations in the 7 joint degreesof- freedom (DOF) from shoulder …