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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
https://doi.org/10.1115/DETC2022-88459
View Paper titled, Metareasoning Approaches for Thermal Management During Image Processing
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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
https://doi.org/10.1115/DETC2022-90494
View Paper titled, Design and Development of a Sit-To-Stand Device Using A Variational Autoencoder-Based Deep Neural Network
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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
https://doi.org/10.1115/DETC2022-91236
View Paper titled, A Small MEMS Neural Network to Classify Human Sitting and Standing Activities
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Topics: Artificial neural networks, Microelectromechanical systems
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
https://doi.org/10.1115/DETC2022-90465
View Paper titled, A Data-Driven Design Approach for Carbon Emission Prediction of Machining
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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
https://doi.org/10.1115/DETC2022-89538
View Paper titled, Multi-Scale Topology Optimization With Neural Network-Assisted Optimizer
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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
https://doi.org/10.1115/DETC2022-90027
View Paper titled, A Comparative Study of Surrogate Modeling of Nonlinear Dynamic Systems
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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
https://doi.org/10.1115/DETC2022-88049
View Paper titled, Material Prediction for Design Automation Using Graph Representation Learning
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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
https://doi.org/10.1115/DETC2022-89091
View Paper titled, Deep Ensembles for Modeling Uncertain Phase Constraints In Compositionally Graded Alloy Design
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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
https://doi.org/10.1115/DETC2022-89452
View Paper titled, Application of Transfer Learning in Metalworking Fluid Distinction
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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
https://doi.org/10.1115/DETC2022-89722
View Paper titled, Efficient Design of Acoustic Metamaterials With Design Domains of Variable Size Using Graph Neural Networks
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Topics: Artificial neural networks, Design, Phononic crystals, Acoustics, Architecture, Encryption, Metamaterials, Space
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
https://doi.org/10.1115/DETC2022-89307
View Paper titled, Manufacturing Process Classification Based on Distance Rotationally Invariant Convolutions
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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
https://doi.org/10.1115/DETC2022-88163
View Paper titled, Surrogate Models and Time Series for Flow Prediction on the Red River Dam Network
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Topics: Artificial neural networks, Dams, Flow (Dynamics), Machine learning, Metamodeling, Rivers, Time series
Proceedings Papers

Uncertainty Quantification of Physics-Based Label-Free Deep Learning and Probabilistic Prediction of Extreme Events

Huiru Li, Jianhua Yin, Xiaoping Du
Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A001, August 14–17, 2022
Paper No: DETC2022-88277
https://doi.org/10.1115/DETC2022-88277
View Paper titled, Uncertainty Quantification of Physics-Based Label-Free Deep Learning and Probabilistic Prediction of Extreme Events
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Topics: Physics, Reliability, Uncertainty, Uncertainty quantification, Artificial neural networks, Errors, Machine learning, Design, Linkages, Regression models
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
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
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Topics: Algorithms, Computer-aided design, Engineering drawings, Machine learning, Artificial neural networks, Computer software, Dimensions, Geometry, Personnel management, Trains
Proceedings Papers

A Scalable Graph Learning Approach to Capacitated Vehicle Routing Problem Using Capsule Networks and Attention Mechanism

Steve Paul, Souma Chowdhury
Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A045, August 14–17, 2022
Paper No: DETC2022-90123
https://doi.org/10.1115/DETC2022-90123
View Paper titled, A Scalable Graph Learning Approach to Capacitated Vehicle Routing Problem Using Capsule Networks and Attention Mechanism
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Topics: Vehicles, Uncertainty, Artificial neural networks, Manufacturing, Reinforcement learning, Robotics
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
https://doi.org/10.1115/DETC2022-89512
View Paper titled, Artificial Intelligence Based State of Health Estimation With Short-Term Current Profile in Lead-Acid Batteries for Heavy-Duty Vehicles
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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
https://doi.org/10.1115/DETC2022-89454
View Paper titled, Assessment of State of Charge Estimation Methods Based on Neural Networks and Support Vector Machine for Lithium-Ion Batteries Used in Vehicular Applications
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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
https://doi.org/10.1115/DETC2022-88313
View Paper titled, Anomaly Detection of Laser Powder Bed Fusion Melt Pool Images Using Combined Unsupervised and Supervised Learning Methods
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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
https://doi.org/10.1115/DETC2022-91115
View Paper titled, Learning the Part Shape and Part Quality Generation Capabilities of Machining and Finishing Processes Using a Neural Network Model
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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
https://doi.org/10.1115/DETC2022-91219
View Paper titled, Multi-Fidelity Physics-Constrained Neural Networks With Minimax Architecture for Materials Modeling
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Topics: Artificial neural networks, Machine learning, Modeling, Optimization, Physics