Search Results | IDETC-CIE | ASME Digital Collection

1-20 of 289

2 3 4 5

Sort by

Sort Order Select

Proceedings Papers

Strut Diameter Uncertainty Prediction by Deep Neural Network for Additively Manufactured Lattice Structures

Recep M. Gorguluarslan, Gorkem Can Ates, O. Utku Gungor, Yusuf Yamaner

Proc. ASME. IDETC-CIE2021, Volume 2: 41st Computers and Information in Engineering Conference (CIE), V002T02A040, August 17–19, 2021

Paper No: DETC2021-69985

DOI: https://doi.org/10.1115/DETC2021-69985

View Paper

Topics: Additive manufacturing, Artificial neural networks, Extruding, Struts (Engineering), Uncertainty

Proceedings Papers

Prediction of Melt Pool Geometry Using Deep Neural Networks

Fahad Ali Milaat, Zhuo Yang, Hyunwoong Ko, Albert T. Jones

Proc. ASME. IDETC-CIE2021, Volume 2: 41st Computers and Information in Engineering Conference (CIE), V002T02A037, August 17–19, 2021

Paper No: DETC2021-69259

DOI: https://doi.org/10.1115/DETC2021-69259

View Paper

Topics: Artificial neural networks, Geometry, Modeling

Proceedings Papers

SuperMeshing: A Deep Learning Method for Boosting Mesh Density in Numerical Computation Within 2D Domain

Handing Xu, Zhenguo Nie, Qingfeng Xu, Xinjun Liu

Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A037, August 17–19, 2021

Paper No: DETC2021-68112

DOI: https://doi.org/10.1115/DETC2021-68112

View Paper

Topics: Computation, Density, Stress, Finite element methods, Resolution (Optics), Artificial neural networks, Errors, Interpolation, Plane strain

Proceedings Papers

Deep Reinforcement Learning Enhanced Convolutional Neural Networks for Robotic Grasping

Jianhao Fang, Weifei Hu, Chuxuan Wang, Zhenyu Liu, Jianrong Tan

Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A036, August 17–19, 2021

Paper No: DETC2021-67225

DOI: https://doi.org/10.1115/DETC2021-67225

View Paper

Topics: Artificial neural networks, Grasping, Reinforcement learning

Proceedings Papers

Gradient-Enhanced Multifidelity Neural Networks for High-Dimensional Function Approximation

Jethro Nagawkar, Leifur Leifsson

Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A040, August 17–19, 2021

Paper No: DETC2021-70502

DOI: https://doi.org/10.1115/DETC2021-70502

View Paper

Topics: Artificial neural networks, Function approximation, Algorithms, Construction, Machine learning

Proceedings Papers

Comparison of Neural Network-Based Pose Estimation Approaches for Mobile Manipulation

Arindam B. Chowdhury, Juncheng Li, David J. Cappelleri

Proc. ASME. IDETC-CIE2021, Volume 8A: 45th Mechanisms and Robotics Conference (MR), V08AT08A048, August 17–19, 2021

Paper No: DETC2021-69800

DOI: https://doi.org/10.1115/DETC2021-69800

View Paper

Topics: Algorithms, Artificial neural networks, Computer-aided design, Dimensions, Pipelines, Robustness

Proceedings Papers

Informed Latent Space Exploration for Image-Based Path Synthesis of Linkages

Shrinath Deshpande, Zhijie Lyu, Anurag Purwar

Proc. ASME. IDETC-CIE2021, Volume 8A: 45th Mechanisms and Robotics Conference (MR), V08AT08A037, August 17–19, 2021

Paper No: DETC2021-71629

DOI: https://doi.org/10.1115/DETC2021-71629

View Paper

Topics: Linkages, Machine learning, Kinematics, Artificial neural networks, Design, Errors, Machine design, Optimization, Pipelines, Statistical distributions

Proceedings Papers

A New Triangle: Fractional Calculus, Renormalization Group, and Machine Learning

Haoyu Niu, YangQuan Chen, Lihong Guo, Bruce J. West

Proc. ASME. IDETC-CIE2021, Volume 7: 17th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), V007T07A022, August 17–19, 2021

Paper No: DETC2021-70505

DOI: https://doi.org/10.1115/DETC2021-70505

View Paper

Topics: Machine learning, Renormalization (Physics), Optimization, Artificial neural networks, Complex systems, Creativity, Degrees of freedom, Design, Dynamic systems, Feature extraction

Proceedings Papers

A Contactless Classification Method for Early Detection of Nematodes Using Deep Neural Networks (DNNs) and TensorFlow

Haoyu Niu, Andreas Westphal, YangQuan Chen

Proc. ASME. IDETC-CIE2021, Volume 7: 17th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), V007T07A001, August 17–19, 2021

Paper No: DETC2021-68557

DOI: https://doi.org/10.1115/DETC2021-68557

View Paper

Topics: Artificial neural networks, Soil, Damage, Flow (Dynamics), Microscopes, Reflectance, Sensors, Tensors, Trains

Proceedings Papers

Towards Generalization of Intelligent Fault Detection for Roller Element Bearings via Distinct Dataset Transfer Learning

Justin Larocque-Villiers, Patrick Dumond

Proc. ASME. IDETC-CIE2021, Volume 10: 33rd Conference on Mechanical Vibration and Sound (VIB), V010T10A012, August 17–19, 2021

Paper No: DETC2021-67773

DOI: https://doi.org/10.1115/DETC2021-67773

View Paper

Topics: Artificial neural networks, Bearings, Flaw detection, Rollers

Proceedings Papers

Model-Order-Reduction Approach for Structural Health Monitoring of Large Deployed Structures With Localized Operational Excitations

Mohamed Aziz Bhouri

Proc. ASME. IDETC-CIE2021, Volume 10: 33rd Conference on Mechanical Vibration and Sound (VIB), V010T10A022, August 17–19, 2021

Paper No: DETC2021-70375

DOI: https://doi.org/10.1115/DETC2021-70375

View Paper

Topics: Artificial neural networks, Excitation, Partial differential equations, Simulation, Structural health monitoring, Errors, Bridges (Structures), Damage, Elastodynamics, Fracture (Materials)

Proceedings Papers

CreativeGAN: Editing Generative Adversarial Networks for Creative Design Synthesis

Amin Heyrani Nobari, Muhammad Fathy Rashad, Faez Ahmed

Proc. ASME. IDETC-CIE2021, Volume 3A: 47th Design Automation Conference (DAC), V03AT03A002, August 17–19, 2021

Paper No: DETC2021-68103

DOI: https://doi.org/10.1115/DETC2021-68103

View Paper

Topics: Creativity, Design, Bicycles, Innovation, Artificial neural networks, Design automation, Design methodology, Engineering disciplines, Image segmentation, Machine learning

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

Paper No: DETC2021-70557

DOI: https://doi.org/10.1115/DETC2021-70557

View Paper

Topics: Artificial neural networks, Lasers, Metals, Physics, Thermal analysis, Engineering simulation, Machine learning, Manufacturing, Simulation, Transients (Dynamics)

Proceedings Papers

A Graph Neural Network Approach for Product Relationship Prediction

Faez Ahmed, Yaxin Cui, Yan Fu, Wei Chen

Proc. ASME. IDETC-CIE2021, Volume 3A: 47th Design Automation Conference (DAC), V03AT03A036, August 17–19, 2021

Paper No: DETC2021-69462

DOI: https://doi.org/10.1115/DETC2021-69462

View Paper

Topics: Artificial neural networks, Artificial intelligence, Automobiles, Design, Drugs, Engineering systems and industry applications, Machine learning, Modeling, Network analysis, Optimization

Proceedings Papers

Multi-Objective Structural Optimization of Vehicle Wheels

P. Stabile, F. Ballo, M. Gobbi, G. Previati

Proc. ASME. IDETC-CIE2021, Volume 1: 23rd International Conference on Advanced Vehicle Technologies (AVT), V001T01A015, August 17–19, 2021

Paper No: DETC2021-71062

DOI: https://doi.org/10.1115/DETC2021-71062

View Paper

Topics: Artificial neural networks, Design, Genetic algorithms, Pareto optimization, Structural optimization, Vehicles, Wheels

Proceedings Papers

A New Robot Path Planning Method Based on LSTM Neural Network and Rapidly-Exploring Random Tree Algorithm

Weifei Hu, Feng Tang, Zhenyu Liu, Jianrong Tan

Proc. ASME. IDETC-CIE2021, Volume 8B: 45th Mechanisms and Robotics Conference (MR), V08BT08A006, August 17–19, 2021

Paper No: DETC2021-71234

DOI: https://doi.org/10.1115/DETC2021-71234

View Paper

Topics: Algorithms, Artificial neural networks, Path planning, Robots

Proceedings Papers

A Machine Learning Method for State of Charge Estimation in Lead-Acid Batteries for Heavy-Duty Vehicles

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

Proc. ASME. IDETC-CIE2021, Volume 1: 23rd International Conference on Advanced Vehicle Technologies (AVT), V001T01A017, August 17–19, 2021

Paper No: DETC2021-68469

DOI: https://doi.org/10.1115/DETC2021-68469

View Paper

Topics: Artificial neural networks, Construction equipment, Genetic algorithms, Lead-acid batteries, Machine learning

Proceedings Papers

Neural Network Based Transfer Learning for Robot Path Generation

Houcheng Tang, Leila Notash

Proc. ASME. IDETC-CIE2021, Volume 8B: 45th Mechanisms and Robotics Conference (MR), V08BT08A049, August 17–19, 2021

Paper No: DETC2021-69006

DOI: https://doi.org/10.1115/DETC2021-69006

View Paper

Topics: Artificial neural networks, Displacement, Manipulators, Robots

Proceedings Papers

Forward Kinematics for Suspended Under-Actuated Cable-Driven Parallel Robots: A Neural Network Approach

Utkarsh A. Mishra, Stéphane Caro

Proc. ASME. IDETC-CIE2021, Volume 8B: 45th Mechanisms and Robotics Conference (MR), V08BT08A053, August 17–19, 2021

Paper No: DETC2021-71064

DOI: https://doi.org/10.1115/DETC2021-71064

View Paper

Topics: Artificial neural networks, Cables, Kinematics, Robots, Algorithms, Equilibrium (Physics), Function approximation, Gravity (Force), Kinematic analysis, Optimization

Proceedings Papers

A Zero-Trust Methodology for Security of Complex Systems With Machine Learning Components

Britta Hale, Douglas L. Van Bossuyt, Nikolaos Papakonstantinou, Bryan O’Halloran

Proc. ASME. IDETC-CIE2021, Volume 2: 41st Computers and Information in Engineering Conference (CIE), V002T02A067, August 17–19, 2021

Paper No: DETC2021-70442

DOI: https://doi.org/10.1115/DETC2021-70442

View Paper

Topics: Complex systems, Machine learning, Security, Defense industry, Unmanned aerial vehicles, Algorithms, Artificial neural networks, Decision making, Machinery, Safety

2 3 4 5

NARROW

Strut Diameter Uncertainty Prediction by Deep Neural Network for Additively Manufactured Lattice Structures

Prediction of Melt Pool Geometry Using Deep Neural Networks

SuperMeshing: A Deep Learning Method for Boosting Mesh Density in Numerical Computation Within 2D Domain

Deep Reinforcement Learning Enhanced Convolutional Neural Networks for Robotic Grasping

Gradient-Enhanced Multifidelity Neural Networks for High-Dimensional Function Approximation

Comparison of Neural Network-Based Pose Estimation Approaches for Mobile Manipulation

Informed Latent Space Exploration for Image-Based Path Synthesis of Linkages

A New Triangle: Fractional Calculus, Renormalization Group, and Machine Learning

A Contactless Classification Method for Early Detection of Nematodes Using Deep Neural Networks (DNNs) and TensorFlow

Towards Generalization of Intelligent Fault Detection for Roller Element Bearings via Distinct Dataset Transfer Learning

Model-Order-Reduction Approach for Structural Health Monitoring of Large Deployed Structures With Localized Operational Excitations

CreativeGAN: Editing Generative Adversarial Networks for Creative Design Synthesis

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

A Graph Neural Network Approach for Product Relationship Prediction

Multi-Objective Structural Optimization of Vehicle Wheels

A New Robot Path Planning Method Based on LSTM Neural Network and Rapidly-Exploring Random Tree Algorithm

A Machine Learning Method for State of Charge Estimation in Lead-Acid Batteries for Heavy-Duty Vehicles

Neural Network Based Transfer Learning for Robot Path Generation

Forward Kinematics for Suspended Under-Actuated Cable-Driven Parallel Robots: A Neural Network Approach

A Zero-Trust Methodology for Security of Complex Systems With Machine Learning Components

Journals

Conference Proceedings

eBooks

Resources

Opportunities

Journals

Conference Proceedings

eBooks

Resources

Opportunities

This Feature Is Available To Subscribers Only