1-20 of 258
Trains
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Aggressive Driving Behavior Detection Using Integrated I-DBSCAN and LSTM Neural Network

Hao Chen, Shailesh Hegde, Angelo Bonfitto
Proc. ASME. IDETC-CIE2024, Volume 1: 26th International Conference on Advanced Vehicle Technologies (AVT), V001T01A020, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143462
https://doi.org/10.1115/DETC2024-143462
View Paper titled, Aggressive Driving Behavior Detection Using Integrated I-DBSCAN and LSTM Neural Network
Open the PDF for Aggressive Driving Behavior Detection Using Integrated I-DBSCAN and LSTM Neural Network in another window
Topics: Artificial neural networks, Accidents, Algorithms, Cities, Computer software, Density, Engineering simulation, Machine learning, Noise (Sound), Optimization
Proceedings Papers

Automated Functional Basis Modeling Using Multi-Label Machine Learning on 3D Models

Zachariah A. Connor, Shital Sable, Matthew I. Campbell, Robert B. Stone
Proc. ASME. IDETC-CIE2024, Volume 3A: 50th Design Automation Conference (DAC), V03AT03A011, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-138095
https://doi.org/10.1115/DETC2024-138095
View Paper titled, Automated Functional Basis Modeling Using Multi-Label Machine Learning on 3D Models
Open the PDF for Automated Functional Basis Modeling Using Multi-Label Machine Learning on 3D Models in another window
Topics: Machine learning, Modeling, Three-dimensional models, Algorithms, Trains, Computer-aided design, Convolutional neural networks, Engineering systems and industry applications, Engineers, Generators
Proceedings Papers

Towards Domain-Adaptive, Resolution-Free 3D Topology Optimization With Neural Implicit Fields

Amin Heyrani Nobari, Lyle Regenwetter, Faez Ahmed
Proc. ASME. IDETC-CIE2024, Volume 3A: 50th Design Automation Conference (DAC), V03AT03A012, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-142135
https://doi.org/10.1115/DETC2024-142135
View Paper titled, Towards Domain-Adaptive, Resolution-Free 3D Topology Optimization With Neural Implicit Fields
Open the PDF for Towards Domain-Adaptive, Resolution-Free 3D Topology Optimization With Neural Implicit Fields in another window
Topics: Resolution (Optics), Topology optimization, Topology, Shapes, Engineering design, Generative artificial intelligence, Graphics processing units, Innovation, Optimization, Trains
Proceedings Papers

Inverse Design With Conditional Cascaded Diffusion Models

Milad Habibi, Mark Fuge
Proc. ASME. IDETC-CIE2024, Volume 3A: 50th Design Automation Conference (DAC), V03AT03A020, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143607
https://doi.org/10.1115/DETC2024-143607
View Paper titled, Inverse Design With Conditional Cascaded Diffusion Models
Open the PDF for Inverse Design With Conditional Cascaded Diffusion Models in another window
Topics: Design, Diffusion (Physics), Resolution (Optics), Errors, Generative adversarial networks, Machine learning, Pipelines, Trains
Proceedings Papers

To Quantize or Not to Quantize: Effects on Generative Models for 2D Heat Sink Design

Arthur Drake, Jun Wang, Qiuyi Chen, Ardalan Nejat, James Guest, Mark Fuge
Proc. ASME. IDETC-CIE2024, Volume 3A: 50th Design Automation Conference (DAC), V03AT03A017, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-142052
https://doi.org/10.1115/DETC2024-142052
View Paper titled, To Quantize or Not to Quantize: Effects on Generative Models for 2D Heat Sink Design
Open the PDF for To Quantize or Not to Quantize: Effects on Generative Models for 2D Heat Sink Design in another window
Topics: Design, Heat sinks, Compression, Topology, Topology optimization, Boundary-value problems, Collapse, Engineering design, Engineering simulation, Engineering systems and industry applications
Proceedings Papers

Microstructure-Aware Surrogate Models Based on Unbalanced Data for Material Design

Yulun Wu, Yumeng Li
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A012, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143366
https://doi.org/10.1115/DETC2024-143366
View Paper titled, Microstructure-Aware Surrogate Models Based on Unbalanced Data for Material Design
Open the PDF for Microstructure-Aware Surrogate Models Based on Unbalanced Data for Material Design in another window
Topics: Artificial neural networks, Design, Convolutional neural networks, Engineering simulation, Feedforward neural networks, Simulation, Space, Deep learning, Displacement, Encryption
Proceedings Papers

Impact of Social Learning on Teamwork Efficiency in Learning-Based Self-Organized Systems

Bingling Huang, Hao Ji, Yan Jin
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A002, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143326
https://doi.org/10.1115/DETC2024-143326
View Paper titled, Impact of Social Learning on Teamwork Efficiency in Learning-Based Self-Organized Systems
Open the PDF for Impact of Social Learning on Teamwork Efficiency in Learning-Based Self-Organized Systems in another window
Topics: Collisions (Physics), Design, Energy efficiency, Engineering systems and industry applications, Failure, Manufacturing, Reinforcement learning, Teams, Trains
Proceedings Papers

DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Graph-Based Drag Prediction

Mohamed Elrefaie, Angela Dai, Faez Ahmed
Proc. ASME. IDETC-CIE2024, Volume 3A: 50th Design Automation Conference (DAC), V03AT03A019, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143593
https://doi.org/10.1115/DETC2024-143593
View Paper titled, DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Graph-Based Drag Prediction
Open the PDF for DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Graph-Based Drag Prediction in another window
Topics: Computational fluid dynamics, Design, Drag (Fluid dynamics), Aerodynamics, Automobiles, Automotive design, Convolutional neural networks, Deep learning, Engineering standards, Engineering systems and industry applications
Proceedings Papers

Torque Characteristics of a Planetary Gear Train During Gear Shifting Under Two Inputs and One Output Tandem Driving Conditions

Daiki Shimura, Toshiki Hirogaki, Eiichi Aoyama, Masao Nakagawa, Shinnosuke Yuba
Proc. ASME. IDETC-CIE2023, Volume 11: 2023 International Power Transmission and Gearing Conference (PTG), V011T11A012, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-115087
https://doi.org/10.1115/DETC2023-115087
View Paper titled, Torque Characteristics of a Planetary Gear Train During Gear Shifting Under Two Inputs and One Output Tandem Driving Conditions
Open the PDF for Torque Characteristics of a Planetary Gear Train During Gear Shifting Under Two Inputs and One Output Tandem Driving Conditions in another window
Topics: Gears, Planetary gears, Torque, Trains
Proceedings Papers

Determination of a Predictive Model for Print Quality of Desktop 3D Printers While at Sea

Eliott J. Radcliffe, Drew P. Seker, Eric Y. Chen, Nina N. Horne, John L. Hill
Proc. ASME. IDETC-CIE2023, Volume 12: 35th Conference on Mechanical Vibration and Sound (VIB), V012T12A012, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-112599
https://doi.org/10.1115/DETC2023-112599
View Paper titled, Determination of a Predictive Model for Print Quality of Desktop 3D Printers While at Sea
Open the PDF for Determination of a Predictive Model for Print Quality of Desktop 3D Printers While at Sea in another window
Topics: Additive manufacturing, Failure, Regression models, Seas, Ships, Testing, Trains, Vessels, Vibration, Vibration monitors
Proceedings Papers

Characterizing Designs via Isometric Embeddings: Applications to Airfoil Inverse Design

Qiuyi Chen, Mark D. Fuge
Proc. ASME. IDETC-CIE2023, Volume 3A: 49th Design Automation Conference (DAC), V03AT03A007, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-116743
https://doi.org/10.1115/DETC2023-116743
View Paper titled, Characterizing Designs via Isometric Embeddings: Applications to Airfoil Inverse Design
Open the PDF for Characterizing Designs via Isometric Embeddings: Applications to Airfoil Inverse Design in another window
Topics: Airfoils, Design, Ablation (Vaporization technology), Manifolds, Shape optimization, Trains
Proceedings Papers

Inverse Design of 2D Shape-Morphing Structures

Mohammad Abu-Mualla, Victor Jirón, Jida Huang
Proc. ASME. IDETC-CIE2023, Volume 2: 43rd Computers and Information in Engineering Conference (CIE), V002T02A040, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-111426
https://doi.org/10.1115/DETC2023-111426
View Paper titled, Inverse Design of 2D Shape-Morphing Structures
Open the PDF for Inverse Design of 2D Shape-Morphing Structures in another window
Topics: Design, Shapes, Poisson ratio, Tensile testing, Algorithms, Artificial neural networks, Computer simulation, Design automation, Finite element analysis, Physics
Proceedings Papers

Route Based Fuel Savings of Freight Train Hybridization

Nitisha Ahuja, Jay D. Martin, Michael A. Yukish, Gary M. Stump, Lorri A. Bennett, Bryan W. Schlake, Joel R. Anstrom, Christopher D. Rahn
Proc. ASME. IDETC-CIE2023, Volume 1: 25th International Conference on Advanced Vehicle Technologies (AVT), V001T01A005, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-114683
https://doi.org/10.1115/DETC2023-114683
View Paper titled, Route Based Fuel Savings of Freight Train Hybridization
Open the PDF for Route Based Fuel Savings of Freight Train Hybridization in another window
Topics: Batteries, Fuels, Locomotives, Trains, Diesel, Fuel consumption, Diesel engines, Fuel efficiency, Rails, Computation
Proceedings Papers

Synthetic Image Assisted Deep Learning Framework for Detecting Defects During Composite Sheet Layup

Omey M. Manyar, Junyan Cheng, Reuben Levine, Vihan Krishnan, Jernej Barbič, Satyandra K. Gupta
Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A005, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-90084
https://doi.org/10.1115/DETC2022-90084
View Paper titled, Synthetic Image Assisted Deep Learning Framework for Detecting Defects During Composite Sheet Layup
Open the PDF for Synthetic Image Assisted Deep Learning Framework for Detecting Defects During Composite Sheet Layup in another window
Topics: Composite materials, Flaw detection, Manufacturing, Machinery, Simulation, Trains
Proceedings Papers

Integrated Computational Materials Engineering With Monotonic Gaussian Processes

Anh Tran, Kathryn Maupin, Theron Rodgers
Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A038, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-89213
https://doi.org/10.1115/DETC2022-89213
View Paper titled, Integrated Computational Materials Engineering With Monotonic Gaussian Processes
Open the PDF for Integrated Computational Materials Engineering With Monotonic Gaussian Processes in another window
Topics: Interpolation, Machine learning, Materials science, Physics, Trains
Proceedings Papers

Human Hand Motion Prediction in Disassembly Operations

Hao-yu Liao, Minghui Zheng, Boyi Hu, Sara Behdad
Proc. ASME. IDETC-CIE2022, Volume 5: 27th Design for Manufacturing and the Life Cycle Conference (DFMLC), V005T05A021, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-89967
https://doi.org/10.1115/DETC2022-89967
View Paper titled, Human Hand Motion Prediction in Disassembly Operations
Open the PDF for Human Hand Motion Prediction in Disassembly Operations in another window
Topics: Computers, Hazardous substances, Human-robot collaboration, Performance, Robotics, Robots, Safety, Trains
Proceedings Papers

Triggered: Using Human-AI Dialogue for Problem Understanding in Collaborative Design

Anne Arzberger, Vera van der Burg, Senthil Chandrasegaran, Peter Lloyd
Proc. ASME. IDETC-CIE2022, Volume 6: 34th International Conference on Design Theory and Methodology (DTM), V006T06A038, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-89273
https://doi.org/10.1115/DETC2022-89273
View Paper titled, Triggered: Using Human-AI Dialogue for Problem Understanding in Collaborative Design
Open the PDF for Triggered: Using Human-AI Dialogue for Problem Understanding in Collaborative Design in another window
Topics: Design, Artificial intelligence, Engineers, Generators, Machine learning, Space, Trains
Proceedings Papers

Task Modification Scheme for a Collaborative Robot

Hardeep Singh, Rajesh Kumar, Subir Kumar Saha
Proc. ASME. IDETC-CIE2022, Volume 7: 46th Mechanisms and Robotics Conference (MR), V007T07A075, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-89720
https://doi.org/10.1115/DETC2022-89720
View Paper titled, Task Modification Scheme for a Collaborative Robot
Open the PDF for Task Modification Scheme for a Collaborative Robot in another window
Topics: Robots, Sliding mode control, Algorithms, Control equipment, End effectors, Human dynamics, Ignorance, Trajectories (Physics), Dynamics (Mechanics), Inertia (Mechanics)
Proceedings Papers

Automated and Customized CAD Drawings by Utilizing Machine Learning Algorithms: A Case Study

Javier Villena Toro, Mehdi Tarkian
Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A040, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-88971
https://doi.org/10.1115/DETC2022-88971
View Paper titled, Automated and Customized CAD Drawings by Utilizing Machine Learning Algorithms: A Case Study
Open the PDF for Automated and Customized CAD Drawings by Utilizing Machine Learning Algorithms: A Case Study in another window
Topics: Algorithms, Computer-aided design, Engineering drawings, Machine learning, Artificial neural networks, Computer software, Dimensions, Geometry, Personnel management, Trains
Proceedings Papers

Stochastically-Trained Physics-Informed Neural Networks: Application to Thermal Analysis in Metal Laser Powder Bed Fusion

Justin Pierce, Glen Williams, Timothy W. Simpson, Nicholas A. Meisel, Christopher McComb
Proc. ASME. IDETC-CIE2021, Volume 3A: 47th Design Automation Conference (DAC), V03AT03A004, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-70557
https://doi.org/10.1115/DETC2021-70557
View Paper titled, Stochastically-Trained Physics-Informed Neural Networks: Application to Thermal Analysis in Metal Laser Powder Bed Fusion
Open the PDF for Stochastically-Trained Physics-Informed Neural Networks: Application to Thermal Analysis in Metal Laser Powder Bed Fusion in another window
Topics: Artificial neural networks, Lasers, Metals, Physics, Thermal analysis, Engineering simulation, Machine learning, Manufacturing, Simulation, Transients (Dynamics)