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Proceedings Papers

Multi-Physics Simulation Study of 3-D Bi-Continuous Silicon Anode for Li-Ion Batteries

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Parth Bansal, Yumeng Li
Proc. ASME. IMECE2024, Volume 6: Energy, V006T08A053, November 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2024-145633
https://doi.org/10.1115/IMECE2024-145633
View Paper titled, Multi-Physics Simulation Study of 3-D Bi-Continuous Silicon Anode for Li-Ion Batteries
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Topics: Anodes, Lithium-ion batteries, Physics, Silicon, Simulation, Stress, Triply periodic minimal surfaces
Proceedings Papers

Multiscale Modeling and Simulation of Silicon Anode

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Parth Bansal, Yumeng Li
Proc. ASME. IMECE2024, Volume 6: Energy, V006T08A052, November 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2024-145553
https://doi.org/10.1115/IMECE2024-145553
View Paper titled, Multiscale Modeling and Simulation of Silicon Anode
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Topics: Anodes, Lithium-ion batteries, Multiscale modeling, Silicon, Simulation
Proceedings Papers

Multiphysics Modeling and Simulation of Gas Sensor for NO 2 Detection

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Parth Bansal, Yuan Jiang, Zhou Li, Sergio Cordero, Zahra Heussen, Debbie Senesky, Pingfeng Wang, Yumeng Li
Proc. ASME. IMECE2024, Volume 10: Mechanics of Solids, Structures, and Fluids; Micro- and Nano-Systems Engineering and Packaging, V010T13A009, November 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2024-145663
https://doi.org/10.1115/IMECE2024-145663
View Paper titled, Multiphysics Modeling and Simulation of Gas Sensor for NO 2 Detection
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Topics: Modeling, Sensors, Simulation
Journal Articles

Uncertainty Quantification of Additively Manufactured Architected Cellular Materials for Energy Absorption Applications

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Zheng Liu, Yanwen Xu, Yuan Jiang, Anabel Renteria, Parth Bansal, Chenlong Xu, Pingfeng Wang, Yumeng Li
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. September 2025, 11(3): 031204.
Paper No: RISK-24-1031
https://doi.org/10.1115/1.4066933
Published Online: November 22, 2024
View Articletitled, Uncertainty Quantification of Additively Manufactured Architected Cellular Materials for Energy Absorption Applications
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Topics: Absorption, Additive manufacturing, Compression, Design, Simulation, Uncertainty, Uncertainty quantification, Modeling, Manufacturing, Reliability
Proceedings Papers

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

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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
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Topics: Artificial neural networks, Design, Convolutional neural networks, Engineering simulation, Feedforward neural networks, Simulation, Space, Deep learning, Displacement, Encryption
Journal Articles

Reliability-Based Design Optimization of Additive Manufacturing for Lithium Battery Silicon Anode

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Zheng Liu, Hao Wu, Pingfeng Wang, Yumeng Li
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. September 2024, 10(3): 031104.
Paper No: RISK-23-1100
https://doi.org/10.1115/1.4065530
Published Online: June 6, 2024
View Articletitled, Reliability-Based Design Optimization of Additive Manufacturing for Lithium Battery Silicon Anode
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Topics: Anodes, Silicon, Reliability-based optimization, Additive manufacturing, Design, Batteries, Manufacturing
Journal Articles

Multi-Task Learning for Design Under Uncertainty With Multi-Fidelity Partially Observed Information

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Yanwen Xu, Hao Wu, Zheng Liu, Pingfeng Wang, Yumeng Li
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. August 2024, 146(8): 081704.
Paper No: MD-23-1618
https://doi.org/10.1115/1.4064492
Published Online: March 5, 2024
View Articletitled, Multi-Task Learning for Design Under Uncertainty With Multi-Fidelity Partially Observed Information
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Topics: Design, Design under uncertainty, Machine learning, Metamodeling, Optimization, Reliability, Reliability-based optimization, Uncertainty, Complex systems, Uncertainty quantification
Proceedings Papers

Control Co-Design of Battery Packs With Immersion Cooling

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Zheng Liu, Jiaxin Wu, Wuchen Fu, Pouya Kabirzadeh, In-Bum Chung, Mohammed Jubair Dipto, Nenad Miljkovic, Pingfeng Wang, Yumeng Li
Proc. ASME. IMECE2023, Volume 2: Advanced Design and Information Technologies, V002T02A016, October 29–November 2, 2023
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2023-112873
https://doi.org/10.1115/IMECE2023-112873
View Paper titled, Control Co-Design of Battery Packs With Immersion Cooling
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Topics: Batteries, Cooling, Design
Proceedings Papers

Understanding Governing Physical Mechanism of Bio-Inspired Nanostructured Antifouling Coating

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Akash Singh, Yumeng Li
Proc. ASME. IMECE2023, Volume 4: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology, V004T04A052, October 29–November 2, 2023
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2023-113115
https://doi.org/10.1115/IMECE2023-113115
View Paper titled, Understanding Governing Physical Mechanism of Bio-Inspired Nanostructured Antifouling Coating
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Topics: Bacteria, Biomimetics, Coating processes, Coatings, Membranes, Molecular dynamics
Proceedings Papers

Machine Learning Accelerated Atomistic Simulations for 2D Materials With Defects

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Shijie Sun, Akash Singh, Yumeng Li
Proc. ASME. IMECE2023, Volume 4: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology, V004T04A066, October 29–November 2, 2023
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2023-113427
https://doi.org/10.1115/IMECE2023-113427
View Paper titled, Machine Learning Accelerated Atomistic Simulations for 2D Materials With Defects
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Topics: Artificial neural networks, Graphene, Machine learning, Simulation
Proceedings Papers

Multi-Physics Simulation for Morphology Design of Si Anode

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Parth Bansal, Yumeng Li
Proc. ASME. IMECE2023, Volume 7: Energy, V007T08A050, October 29–November 2, 2023
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2023-113107
https://doi.org/10.1115/IMECE2023-113107
View Paper titled, Multi-Physics Simulation for Morphology Design of Si Anode
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Topics: Anodes, Design, Lithium-ion batteries, Physics, Simulation, Stress
Proceedings Papers

Multiphysics-Informed Machine Learning for Mechanical-Induced Degradation of Silicon Anode

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Parth Bansal, Yumeng Li
Proc. ASME. IMECE2023, Volume 11: Mechanics of Solids, Structures and Fluids, V011T12A008, October 29–November 2, 2023
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2023-113404
https://doi.org/10.1115/IMECE2023-113404
View Paper titled, Multiphysics-Informed Machine Learning for Mechanical-Induced Degradation of Silicon Anode
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Topics: Anodes, Cracking (Materials), Delamination, Fracture (Process), Lithium-ion batteries, Machine learning, Silicon
Proceedings Papers

Feature Importance and Uncertainty Quantification of Machine Learning Model in Materials Science

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Zhichen Liu, Akash Singh, Yumeng Li
Proc. ASME. IMECE2023, Volume 11: Mechanics of Solids, Structures and Fluids, V011T12A007, October 29–November 2, 2023
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2023-112990
https://doi.org/10.1115/IMECE2023-112990
View Paper titled, Feature Importance and Uncertainty Quantification of Machine Learning Model in Materials Science
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Topics: Machine learning, Materials science, Simulation, Uncertainty quantification
Proceedings Papers

Multiphysics-Informed Machine Learning for Battery Design and Health Monitoring

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Parth Bansal, Yumeng Li
Proc. ASME. IDETC-CIE2023, Volume 3A: 49th Design Automation Conference (DAC), V03AT03A037, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-117113
https://doi.org/10.1115/DETC2023-117113
View Paper titled, Multiphysics-Informed Machine Learning for Battery Design and Health Monitoring
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Topics: Anodes, Batteries, Design, Lithium-ion batteries, Machine learning
Proceedings Papers

Data-Driven Control Co-Design for Indirect Liquid Cooling Plate With Microchannels for Battery Thermal Management

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Zheng Liu, Yanwen Xu, Hao Wu, Pingfeng Wang, Yumeng Li
Proc. ASME. IDETC-CIE2023, Volume 3A: 49th Design Automation Conference (DAC), V03AT03A048, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-116921
https://doi.org/10.1115/DETC2023-116921
View Paper titled, Data-Driven Control Co-Design for Indirect Liquid Cooling Plate With Microchannels for Battery Thermal Management
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Topics: Batteries, Cooling, Design, Microchannels, Thermal management
Proceedings Papers

Uncertainty Quantification on Mechanical Behavior of Corroded Plate With Statistical Shape Modeling

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Hao Wu, Parth Bansal, Zheng Liu, Yumeng Li, Pingfeng Wang
Proc. ASME. IDETC-CIE2023, Volume 3B: 49th Design Automation Conference (DAC), V03BT03A051, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-117050
https://doi.org/10.1115/DETC2023-117050
View Paper titled, Uncertainty Quantification on Mechanical Behavior of Corroded Plate With Statistical Shape Modeling
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Topics: Corrosion, Finite element analysis, Mechanical behavior, Modeling, Shapes, Uncertainty quantification
Proceedings Papers

How to Encode Microstructure in Machine Learning: A Comparison Study

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Yulun Wu, Yumeng Li
Proc. ASME. IDETC-CIE2023, Volume 3B: 49th Design Automation Conference (DAC), V03BT03A032, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-116704
https://doi.org/10.1115/DETC2023-116704
View Paper titled, How to Encode Microstructure in Machine Learning: A Comparison Study
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Topics: Artificial neural networks, Encryption, Machine learning
Proceedings Papers

Physics-Informed Multitask Learning for Material Development

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Yulun Wu, Yumeng Li
Proc. ASME. SSDM2023, ASME 2023 Aerospace Structures, Structural Dynamics, and Materials Conference, V001T03A012, June 19–21, 2023
Publisher: American Society of Mechanical Engineers
Paper No: SSDM2023-108449
https://doi.org/10.1115/SSDM2023-108449
View Paper titled, Physics-Informed Multitask Learning for Material Development
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Topics: Artificial neural networks, Physics, Design, Computer simulation, Displacement, Robustness, Simulation results
Proceedings Papers

Bactericidal Effects of Micropillars: A Molecular Dynamics Study

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Akash Singh, Yumeng Li
Proc. ASME. IMECE2022, Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology, V003T03A001, October 30–November 3, 2022
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2022-95325
https://doi.org/10.1115/IMECE2022-95325
View Paper titled, Bactericidal Effects of Micropillars: A Molecular Dynamics Study
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Topics: Bacteria, Biomimetics, Molecular dynamics, Design, Molecular dynamics simulation, Wings, Dimensions, Engineering simulation, Modeling, Simulation
Proceedings Papers

Machine Learning Potentials for Graphene

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Akash Singh, Yumeng Li
Proc. ASME. IMECE2022, Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology, V003T03A036, October 30–November 3, 2022
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2022-95341
https://doi.org/10.1115/IMECE2022-95341
View Paper titled, Machine Learning Potentials for Graphene
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Topics: Artificial neural networks, Density functional theory, Graphene, Machine learning, Molecular dynamics simulation