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Proceedings Papers

SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Metal Forming Stress Field With Attention Mechanism And Perceptual Features

Qingfeng Xu, Zhenguo Nie, Handing Xu, Haosu Zhou, Xinjun Liu
Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A041, August 17–19, 2021
Paper No: DETC2021-71158
DOI: https://doi.org/10.1115/DETC2021-71158
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Topics: Density, Metalworking, Stress, Finite element analysis, Errors, Finite element methods, Interpolation, Sheet metal work, Simulation results
Journal Articles

SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Physical Fields in Metal Forming Numerical Simulation

Qingfeng Xu, Zhenguo Nie, Handing Xu, Haosu Zhou, Hamid Reza Attar, Nan Li, Fugui Xie, Xin-Jun Liu
Journal: Journal of Applied Mechanics
Article Type: Research Papers
J. Appl. Mech. January 2022, 89(1): 011002.
Paper No: JAM-21-1240
DOI: https://doi.org/10.1115/1.4052195
Published Online: September 13, 2021
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Topics: Density, Finite element methods, Metalworking, Interpolation, Resolution (Optics)
Journal Articles

A Study on Using Image-Based Machine Learning Methods to Develop Surrogate Models of Stamp Forming Simulations

Haosu Zhou, Qingfeng Xu, Zhenguo Nie, Nan Li
Journal: Journal of Manufacturing Science and Engineering
Article Type: Research Papers
J. Manuf. Sci. Eng. February 2022, 144(2): 021012.
Paper No: MANU-21-1029
DOI: https://doi.org/10.1115/1.4051604
Published Online: August 6, 2021
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Topics: Design, Engineering simulation, Finite element analysis, Machine learning, Multilayer perceptron, Scalars, Simulation, Interpolation, Metalworking, Simulation results