Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Machine learning (2)
- Residual stresses (2)
- Additive manufacturing (1)
- Additive-derived species (1)
- Airplane design (1)
-
- Aluminum (1)
- Bacterial biofilm (1)
- Bead geometry (1)
- Blended wing body (1)
- Ceramics (1)
- Cold atmospheric plasma (1)
- Composite (1)
- Computational method (1)
- Decontamination (1)
- Defocusing (1)
- Design space (1)
- Dielectric barrier discharge (1)
- Dielectrics (1)
- Directed energy deposition (1)
- Discharges (electric) (1)
- EVTOL (1)
- Electrodes (1)
- Experimental measurement (1)
- Film growth mechanism (1)
- Gas–solid reactions (1)
- Generative adversarial networks (1)
- High pressure (1)
- Infusion (1)
- Inverse design (1)
- Inverse mapping (1)
Articles 1 - 13 of 13
Full-Text Articles in Mechanical Engineering
Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy
Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy
Computer Science Faculty Research & Creative Works
Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computational efficiency of SNNs has been introduced. This paper studies the feasibility of using a convolutional spiking neural network (CSNN) to detect anticipatory slow cortical potentials (SCPs) related to braking intention in human participants using an electroencephalogram (EEG). Data was collected during an experiment wherein participants operated a remote-controlled vehicle on a testbed …
Insight Into Uniform Filming Of Lif-Rich Interphase Via Synergistic Adsorption For High-Performance Lithium Metal Anode, Yufang He, Li Wang, Aiping Wang, Bo Zhang, Hiep Pham, Jonghyun Park, Xiangming He
Insight Into Uniform Filming Of Lif-Rich Interphase Via Synergistic Adsorption For High-Performance Lithium Metal Anode, Yufang He, Li Wang, Aiping Wang, Bo Zhang, Hiep Pham, Jonghyun Park, Xiangming He
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Multi-scale simulation is an important basis for constructing digital batteries to improve battery design and application. Lif-rich solid electrolyte interphase (sei) is experimentally proven to be crucial for the electrochemical performance of lithium metal batteries. However, the lif-rich sei is sensitive to various electrolyte formulas and the fundamental mechanism is still unclear. Herein, the structure and formation mechanism of lif-rich sei in different electrolyte formulas have been reviewed. On this basis, it further discussed the possible filming mechanism of lif-rich sei determined by the initial adsorption of the electrolyte-derived species on the lithium metal anode (lma). It proposed that individual …
Experimental, Computational, And Machine Learning Methods For Prediction Of Residual Stresses In Laser Additive Manufacturing: A Critical Review, Sung Heng Wu, Usman Tariq, Ranjit Joy, Todd Sparks, Aaron Flood, Frank W. Liou
Experimental, Computational, And Machine Learning Methods For Prediction Of Residual Stresses In Laser Additive Manufacturing: A Critical Review, Sung Heng Wu, Usman Tariq, Ranjit Joy, Todd Sparks, Aaron Flood, Frank W. Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In recent decades, laser additive manufacturing has seen rapid development and has been applied to various fields, including the aerospace, automotive, and biomedical industries. However, the residual stresses that form during the manufacturing process can lead to defects in the printed parts, such as distortion and cracking. Therefore, accurately predicting residual stresses is crucial for preventing part failure and ensuring product quality. This critical review covers the fundamental aspects and formation mechanisms of residual stresses. It also extensively discusses the prediction of residual stresses utilizing experimental, computational, and machine learning methods. Finally, the review addresses the challenges and future directions …
Jet-Driven Mixing Regimes Identified In The Unsteady Isothermal Filling Of Rectangular Municipal Water Storage Tanks, Pramod Narayan Bangalore, K. (Kelly) O. Homan
Jet-Driven Mixing Regimes Identified In The Unsteady Isothermal Filling Of Rectangular Municipal Water Storage Tanks, Pramod Narayan Bangalore, K. (Kelly) O. Homan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Poor mixing of old and new water in municipal water storage vessels is a well-documented basis for potentially harmful water quality degradation in drinking water distribution systems. This numerical study investigates the effects of inflow and operational variables on mixing in the jet-driven filling process, with a particular focus on the transition from inadequate to sufficient mixing levels. An isothermal unsteady reynolds-averaged-navier-stokes volume-of-fluid (RANS-VOF) simulation is used to model the variable-volume filling process, accounting for the moving free surface following a draw-down in the stored water volume. A low diffusivity tracer is used to mark the old-water volume, and a …
Heat Treatments For Minimization Of Residual Stresses And Maximization Of Tensile Strengths Of Scalmalloy® Processed Via Directed Energy Deposition, Rachel Boillat-Newport, Sriram Praneeth Isanaka, Jonathan Kelley, Frank Liou
Heat Treatments For Minimization Of Residual Stresses And Maximization Of Tensile Strengths Of Scalmalloy® Processed Via Directed Energy Deposition, Rachel Boillat-Newport, Sriram Praneeth Isanaka, Jonathan Kelley, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Scalmalloy® is an Al-Mg-Sc-Zr-Based Alloy Specifically Developed for Additive Manufacturing (AM). This Alloy is Designed for Use with a Direct Aging Treatment, as Recommended by the Manufacturer, Rather Than with a Multistep Treatment, as Often Seen in Conventional Manufacturing. Most Work with Scalmalloy® is Conducted using Powder Bed Rather Than Powder-Fed Processes. This Investigation Seeks to Fill This Knowledge Gap and Expand Beyond Single-Step Aging to Promote an overall Balanced AM-Fabricated Component. for This Study, Directed Energy Deposition (DED)-Fabricated Scalmalloy® Components Were Subjected to Low-Temperature Treatments to Minimize Residual Stresses Inherent in the Material Due to the Layer-By-Layer Build Process. …
Effects Of Laser Defocusing On Bead Geometry In Coaxial Titanium Wire-Based Laser Metal Deposition, Remy Mathenia, Aaron Flood, Braden Mclain, Todd Sparks, Frank W. Liou
Effects Of Laser Defocusing On Bead Geometry In Coaxial Titanium Wire-Based Laser Metal Deposition, Remy Mathenia, Aaron Flood, Braden Mclain, Todd Sparks, Frank W. Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Coaxial wire-based laser metal deposition is a versatile and efficient additive process that can achieve a high deposition rate in the manufacturing of complex structures. In this paper, a three-beam coaxial wire system is studied, with particular attention to the effects of deposition height and laser defocusing on the resulting bead geometry. As the deposition standoff distance changes, so does the workpiece illumination proportion, which describes the ratio of energy going directly into the feedstock wire and into the substrate. Single titanium beads are deposited at varying defocus levels and deposition rates and the bead aspect ratio is measured and …
Mission-Driven Inverse Design Of Blended Wing Body Aircraft With Machine Learning, Rohan S. Sharma, Serhat Hosder
Mission-Driven Inverse Design Of Blended Wing Body Aircraft With Machine Learning, Rohan S. Sharma, Serhat Hosder
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The intent of this work was to investigate the feasibility of developing machine learning models for calculating values of airplane configuration design variables when provided time-series, mission-informed performance data. Shallow artificial neural networks were developed, trained, and tested using data pertaining to the blended wing body (BWB) class of aerospace vehicles. Configuration design parameters were varied using a Latin-hypercube sampling scheme. These data were used by a parametric-based BWB configuration generator to create unique BWBs. Performance for each configuration was obtained via a performance estimation tool. Training and testing of neural networks were conducted using a K-fold cross-validation scheme. A …
Upconversion Photoluminescence Of Monolayer Wse2 With Biaxial Strain Tuning, Shrawan Roy, Jie Gao, Xiaodong Yang
Upconversion Photoluminescence Of Monolayer Wse2 With Biaxial Strain Tuning, Shrawan Roy, Jie Gao, Xiaodong Yang
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Mechanical strain can be used to tune the optical properties of monolayer transition metal dichalcogenides (1L-TMDs). Here, up conversion photoluminescence (UPL) from 1L-WSe2 flakes is tuned with biaxial strain induced by cruciform bending and indentation method. It is found that the peak position of UPL is redshifted by around 24 nm as the applied biaxial strain increases from 0% to 0.51%. At the same time, the UPL intensity increases exponentially for the up-conversion energy difference that lies within a broad range between −157 meV to −37 meV. The observed linear and sublinear power dependence of UPL emission in 1L-WSe …
Effects Of Organic Surface Contamination On The Mass Accommodation Coefficient Of Water: A Molecular Dynamics Study, Jordan Hartfield, Eric Bird, Zhi Liang
Effects Of Organic Surface Contamination On The Mass Accommodation Coefficient Of Water: A Molecular Dynamics Study, Jordan Hartfield, Eric Bird, Zhi Liang
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The mass accommodation coefficient (MAC), a parameter that quantifies the possibility of a phase change to occur at a liquid-vapor interface, can strongly affect the evaporation and condensation rates at a liquid surface. Due to the various challenges in experimental determination of the MAC, molecular dynamics (MD) simulations have been widely used to study the MAC on liquid surfaces with no impurities or contaminations. However, experimental studies show that airborne hydrocarbons from various sources can adsorb on liquid surfaces and alter the liquid surface properties. In this work, therefore, we study the effects of organic surface contamination, which is immiscible …
A Review Of Dielectric Barrier Discharge Cold Atmospheric Plasma For Surface Sterilization And Decontamination, Kolawole Adesina, Ta Chun Lin, Yue-Wern Huang, Marek Locmelis, Daoru Frank Han
A Review Of Dielectric Barrier Discharge Cold Atmospheric Plasma For Surface Sterilization And Decontamination, Kolawole Adesina, Ta Chun Lin, Yue-Wern Huang, Marek Locmelis, Daoru Frank Han
Biological Sciences Faculty Research & Creative Works
Numerous investigations have shown that non-equilibrium discharges at atmospheric pressure, also known as "cold atmospheric plasma" (CAP) are efficient to remove biological contaminants from surfaces of a variety of materials. Recently, CAP has quickly advanced as a technique for microbial cleaning, wound healing, and cancer therapy due to the chemical and biologically active radicals it produces, known collectively as reactive oxygen and nitrogen species (RONS). This article reviews studies pertaining to one of the atmospheric plasma sources known as Dielectric Barrier Discharge (DBD) which has been widely used to treat materials with microbes for sterilization, disinfection, and decontamination purposes. To …
Development Of A High-Pressure Infiltration Process For Phenol–Formaldehyde Matrix Composites, Samuel Weiler, Patrick Schwartzkopf, Henry Haffner, K. Chandrashekhara
Development Of A High-Pressure Infiltration Process For Phenol–Formaldehyde Matrix Composites, Samuel Weiler, Patrick Schwartzkopf, Henry Haffner, K. Chandrashekhara
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Phenol–formaldehyde (phenolic) thermosets are known for excellent heat and chemical resistance, high flame retardance, and good mechanical performance. However, phenolics are also known for their high brittleness, and tendency to form voids, due to a condensation reaction forming water during curing. These voids can decrease the mechanical performance of the resultant phenolic composite and introduce undesirable performance characteristics. This work aims to develop a technique that uses high-pressure infiltration to obtain dense phenolic matrix composites, with commercially available resin and fiber reinforcement. The high-pressure system developed in this work is compared to a conventional low-pressure resin infusion technique, and the …
Optimal Tilt-Wing Evtol Takeoff Trajectory Prediction Using Regression Generative Adversarial Networks, Shuan Tai Yeh, Xiaosong Du
Optimal Tilt-Wing Evtol Takeoff Trajectory Prediction Using Regression Generative Adversarial Networks, Shuan Tai Yeh, Xiaosong Du
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Electric vertical takeoff and landing (eVTOL) aircraft have attracted tremendous attention nowadays due to their flexible maneuverability, precise control, cost efficiency, and low noise. The optimal takeoff trajectory design is a key component of cost-effective and passenger-friendly eVTOL systems. However, conventional design optimization is typically computationally prohibitive due to the adoption of high-fidelity simulation models in an iterative manner. Machine learning (ML) allows rapid decision making; however, new ML surrogate modeling architectures and strategies are still desired to address large-scale problems. Therefore, we showcase a novel regression generative adversarial network (regGAN) surrogate for fast interactive optimal takeoff trajectory predictions of …
Oxidation Of Additively Manufactured Zrb2–Sic In Air And In Co2 At 700–1000 °C, Marharyta Lakusta, Nicholas M. Timme, Abid H. Rafi, Jeremy Lee Watts, M. (Ming) C. (Chuan) Leu, Gregory E. Hilmas, William G. Fahrenholtz, David W. Lipke
Oxidation Of Additively Manufactured Zrb2–Sic In Air And In Co2 At 700–1000 °C, Marharyta Lakusta, Nicholas M. Timme, Abid H. Rafi, Jeremy Lee Watts, M. (Ming) C. (Chuan) Leu, Gregory E. Hilmas, William G. Fahrenholtz, David W. Lipke
Materials Science and Engineering Faculty Research & Creative Works
Oxidation behavior of additively manufactured zrb2–sic in air and in co2 is reported in the temperature range of 700–1000 °c. Observed scale morphologies in air and in co2 were similar, featuring an outer borosilicate layer and an inner porous zirconia layer containing partially oxidized silicon carbide particles and remnant borosilicate products. Oxide scale thicknesses and parabolic scaling constants in air were approximately twice those observed in co2 across all studied temperatures. Activation energies for oxidation of 140 ± 20 kj/mol in air and 110 ± 20 kj/mol in co2 were determined, indicating similar diffusion processes that appear to be rate-limiting. …