Search Results | IDETC-CIE | ASME Digital Collection

1-20 of 312

2 3 4 5

Sort by

Sort Order Select

Proceedings Papers

Artificial Intelligence Based State of Health Estimation With Short-Term Current Profile in Lead-Acid Batteries for Heavy-Duty Vehicles

Sara Luciani, Stefano Feraco, Angelo Bonfitto, Nicola Amati, Andrea Tonoli, Maurizio Quaggiotto

Proc. ASME. IDETC-CIE2022, Volume 1: 24th International Conference on Advanced Vehicle Technologies (AVT), V001T01A015, August 14–17, 2022

Paper No: DETC2022-89512

DOI: https://doi.org/10.1115/DETC2022-89512

View Paper

Topics: Artificial intelligence, Artificial neural networks, Construction equipment, Lead-acid batteries

Proceedings Papers

Assessment of State of Charge Estimation Methods Based on Neural Networks and Support Vector Machine for Lithium-Ion Batteries Used in Vehicular Applications

Sara Luciani, Stefano Feraco, Mario Silvagni, Angelo Bonfitto, Nicola Amati, Andrea Tonoli

Proc. ASME. IDETC-CIE2022, Volume 1: 24th International Conference on Advanced Vehicle Technologies (AVT), V001T01A014, August 14–17, 2022

Paper No: DETC2022-89454

DOI: https://doi.org/10.1115/DETC2022-89454

View Paper

Topics: Artificial intelligence, Artificial neural networks, Lithium-ion batteries, Support vector machines

Proceedings Papers

Anomaly Detection of Laser Powder Bed Fusion Melt Pool Images Using Combined Unsupervised and Supervised Learning Methods

Matthew M. Sato, Vivian Wen Hui Wong, Kincho H. Law, Ho Yeung, Zhuo Yang, Brandon Lane, Paul Witherell

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A070, August 14–17, 2022

Paper No: DETC2022-88313

DOI: https://doi.org/10.1115/DETC2022-88313

View Paper

Topics: Additive manufacturing, Artificial neural networks, Lasers, Algorithms, Machine learning, Machinery, Manufacturing, Metals, Process control, Shapes

Proceedings Papers

Learning the Part Shape and Part Quality Generation Capabilities of Machining and Finishing Processes Using a Neural Network Model

Changxuan Zhao, Shreyes N. Melkote

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A010, August 14–17, 2022

Paper No: DETC2022-91115

DOI: https://doi.org/10.1115/DETC2022-91115

View Paper

Topics: Artificial neural networks, Finishing, Machining, Manufacturing, Neural network models, Shapes, Computer-aided engineering, Design, Geometry, Production planning

Proceedings Papers

Multi-Fidelity Physics-Constrained Neural Networks With Minimax Architecture for Materials Modeling

Dehao Liu, Pranav Pusarla, Yan Wang

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A011, August 14–17, 2022

Paper No: DETC2022-91219

DOI: https://doi.org/10.1115/DETC2022-91219

View Paper

Topics: Artificial neural networks, Machine learning, Modeling, Optimization, Physics

Proceedings Papers

A Material Removal State Prediction Method Based on Multi-Scale Attention Mechanism

Zhihang Li, Qian Tang, Ying Liu, Xiao Li

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A073, August 14–17, 2022

Paper No: DETC2022-90919

DOI: https://doi.org/10.1115/DETC2022-90919

View Paper

Topics: Artificial neural networks, Belts, Displacement, Errors, Excitation, Feature extraction, Grinding, Machining, Wear

Proceedings Papers

Travel Links Prediction in Shared Mobility Networks Using Graph Neural Network Models

Yinshuang Xiao, Faez Ahmed, Zhenghui Sha

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A079, August 14–17, 2022

Paper No: DETC2022-90694

DOI: https://doi.org/10.1115/DETC2022-90694

View Paper

Topics: Artificial neural networks, Mechanical admittance, Neural network models

Proceedings Papers

Concurrent Build Direction, Part Segmentation, and Topology Optimization for Additive Manufacturing Using Neural Networks

Hongrui Chen, Kate S. Whitefoot, Levent Burak Kara

Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A029, August 14–17, 2022

Paper No: DETC2022-90050

DOI: https://doi.org/10.1115/DETC2022-90050

View Paper

Topics: Additive manufacturing, Artificial neural networks, Image segmentation, Optimization, Topology, Density, Boundary-value problems, Displacement, Stress

Proceedings Papers

A Data-Driven Design Approach for Carbon Emission Prediction of Machining

Yuxuan Chen, Wei Yan, Hua Zhang, Ying Liu, Zhigang Jiang, Xumei Zhang

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A062, August 14–17, 2022

Paper No: DETC2022-90465

DOI: https://doi.org/10.1115/DETC2022-90465

View Paper

Topics: Carbon, Data-driven design, Emissions, Machining, Design, Errors, Manufacturing industry, Artificial neural networks, Computer-aided design, Data collection

Proceedings Papers

Multi-Scale Topology Optimization With Neural Network-Assisted Optimizer

Sina Rastegarzadeh, Jun Wang, Jida Huang

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A041, August 14–17, 2022

Paper No: DETC2022-89538

DOI: https://doi.org/10.1115/DETC2022-89538

View Paper

Topics: Optimization, Topology, Design, Machine learning, Resolution (Optics), Structural design, Artificial neural networks, Density, Filters, Interpolation

Proceedings Papers

A Comparative Study of Surrogate Modeling of Nonlinear Dynamic Systems

Ying Zhao, Chen Jiang, Manuel A. Vega, Michael D. Todd, Zhen Hu

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A040, August 14–17, 2022

Paper No: DETC2022-90027

DOI: https://doi.org/10.1115/DETC2022-90027

View Paper

Topics: Metamodeling, Nonlinear dynamical systems, Artificial neural networks, Design, Dynamic models, Dynamic systems, Uncertainty

Proceedings Papers

Material Prediction for Design Automation Using Graph Representation Learning

Shijie Bian, Daniele Grandi, Kaveh Hassani, Elliot Sadler, Bodia Borijin, Axel Fernandes, Andrew Wang, Thomas Lu, Richard Otis, Nhut Ho, Bingbing Li

Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A001, August 14–17, 2022

Paper No: DETC2022-88049

DOI: https://doi.org/10.1115/DETC2022-88049

View Paper

Topics: Design automation, Design, Manufacturing, Artificial neural networks, Computer-aided design, Sustainability

Proceedings Papers

Deep Ensembles for Modeling Uncertain Phase Constraints In Compositionally Graded Alloy Design

Marshall Allen, Raymundo Arroyave, Richard Malak

Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A028, August 14–17, 2022

Paper No: DETC2022-89091

DOI: https://doi.org/10.1115/DETC2022-89091

View Paper

Topics: Alloys, Design, Modeling, Artificial neural networks, Manufacturing, Metals, Probability, Algorithms, Engineering simulation, Functionally graded materials

Proceedings Papers

Application of Transfer Learning in Metalworking Fluid Distinction

Xiao Wei, Fabian Jochmann, Anna Lena Demmerling, Dirk Söffker

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A003, August 14–17, 2022

Paper No: DETC2022-89452

DOI: https://doi.org/10.1115/DETC2022-89452

View Paper

Topics: Acoustic emissions, Algorithms, Artificial neural networks, Data mining, Fluids, Metalworking, Signals, Thread, Water, Condition monitoring

Proceedings Papers

Efficient Design of Acoustic Metamaterials With Design Domains of Variable Size Using Graph Neural Networks

Tyler Wiest, Carolyn Conner Seepersad, Michael Haberman

Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A047, August 14–17, 2022

Paper No: DETC2022-89722

DOI: https://doi.org/10.1115/DETC2022-89722

View Paper

Topics: Artificial neural networks, Design, Phononic crystals, Acoustics, Architecture, Encryption, Metamaterials, Space

Proceedings Papers

Metareasoning Approaches for Thermal Management During Image Processing

Michael K. Dawson, Jr., Jeffrey W. Herrmann

Proc. ASME. IDETC-CIE2022, Volume 7: 46th Mechanisms and Robotics Conference (MR), V007T07A036, August 14–17, 2022

Paper No: DETC2022-88459

DOI: https://doi.org/10.1115/DETC2022-88459

View Paper

Topics: Artificial neural networks, Image processing, Thermal management, Temperature, Cooling, Electronic systems, Failure, Fatigue, Sensors, Thermodynamics

Proceedings Papers

Design and Development of a Sit-To-Stand Device Using A Variational Autoencoder-Based Deep Neural Network

Zhijie Lyu, Anurag Purwar

Proc. ASME. IDETC-CIE2022, Volume 7: 46th Mechanisms and Robotics Conference (MR), V007T07A027, August 14–17, 2022

Paper No: DETC2022-90494

DOI: https://doi.org/10.1115/DETC2022-90494

View Paper

Topics: Artificial neural networks, Design, Machine learning

Proceedings Papers

A Small MEMS Neural Network to Classify Human Sitting and Standing Activities

Mohammad Okour, Mohammad Megdadi, Hamed Nikfarjam, Siavash Pourkamali, Fadi Alsaleem

Proc. ASME. IDETC-CIE2022, Volume 8: 16th International Conference on Micro- and Nanosystems (MNS), V008T08A012, August 14–17, 2022

Paper No: DETC2022-91236

DOI: https://doi.org/10.1115/DETC2022-91236

View Paper

Topics: Artificial neural networks, Microelectromechanical systems

Proceedings Papers

Manufacturing Process Classification Based on Distance Rotationally Invariant Convolutions

Zhichao Wang, David Rosen

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A002, August 14–17, 2022

Paper No: DETC2022-89307

DOI: https://doi.org/10.1115/DETC2022-89307

View Paper

Topics: Artificial neural networks, Manufacturing, Rotation

Proceedings Papers

Surrogate Models and Time Series for Flow Prediction on the Red River Dam Network

Reza Alizadeh, Janet K. Allen, Farrokh Mistree

Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A023, August 14–17, 2022

Paper No: DETC2022-88163

DOI: https://doi.org/10.1115/DETC2022-88163

View Paper

Topics: Artificial neural networks, Dams, Flow (Dynamics), Machine learning, Metamodeling, Rivers, Time series

2 3 4 5

NARROW

Artificial Intelligence Based State of Health Estimation With Short-Term Current Profile in Lead-Acid Batteries for Heavy-Duty Vehicles

Assessment of State of Charge Estimation Methods Based on Neural Networks and Support Vector Machine for Lithium-Ion Batteries Used in Vehicular Applications

Anomaly Detection of Laser Powder Bed Fusion Melt Pool Images Using Combined Unsupervised and Supervised Learning Methods

Learning the Part Shape and Part Quality Generation Capabilities of Machining and Finishing Processes Using a Neural Network Model

Multi-Fidelity Physics-Constrained Neural Networks With Minimax Architecture for Materials Modeling

A Material Removal State Prediction Method Based on Multi-Scale Attention Mechanism

Travel Links Prediction in Shared Mobility Networks Using Graph Neural Network Models

Concurrent Build Direction, Part Segmentation, and Topology Optimization for Additive Manufacturing Using Neural Networks

A Data-Driven Design Approach for Carbon Emission Prediction of Machining

Multi-Scale Topology Optimization With Neural Network-Assisted Optimizer

A Comparative Study of Surrogate Modeling of Nonlinear Dynamic Systems

Material Prediction for Design Automation Using Graph Representation Learning

Deep Ensembles for Modeling Uncertain Phase Constraints In Compositionally Graded Alloy Design

Application of Transfer Learning in Metalworking Fluid Distinction

Efficient Design of Acoustic Metamaterials With Design Domains of Variable Size Using Graph Neural Networks

Metareasoning Approaches for Thermal Management During Image Processing

Design and Development of a Sit-To-Stand Device Using A Variational Autoencoder-Based Deep Neural Network

A Small MEMS Neural Network to Classify Human Sitting and Standing Activities

Manufacturing Process Classification Based on Distance Rotationally Invariant Convolutions

Surrogate Models and Time Series for Flow Prediction on the Red River Dam Network

Journals

Conference Proceedings

eBooks

Resources

Opportunities

Journals

Conference Proceedings

eBooks

Resources

Opportunities

This Feature Is Available To Subscribers Only