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2203.08150
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A physics and data co-driven surrogate modeling approach for temperature field prediction on irregular geometric domain
15 March 2022
K. Bao
Wenjuan Yao
Xiaoya Zhang
Wei Peng
Yu Li
AI4CE
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Papers citing
"A physics and data co-driven surrogate modeling approach for temperature field prediction on irregular geometric domain"
6 / 6 papers shown
Title
Point-DeepONet: A Deep Operator Network Integrating PointNet for Nonlinear Analysis of Non-Parametric 3D Geometries and Load Conditions
Jangseop Park
Namwoo Kang
AI4CE
3DPC
50
1
0
24 Dec 2024
Physics-informed MTA-UNet: Prediction of Thermal Stress and Thermal Deformation of Satellites
Zeyu Cao
Wenjuan Yao
Wei Peng
Xiaoya Zhang
K. Bao
AI4CE
29
10
0
01 Sep 2022
Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data
Xiaoyu Zhao
Zhiqiang Gong
Yunyang Zhang
Wen Yao
Xiaoqian Chen
OOD
AI4CE
69
90
0
26 Sep 2021
Mosaic Flows: A Transferable Deep Learning Framework for Solving PDEs on Unseen Domains
Hengjie Wang
R. Planas
Aparna Chandramowlishwaran
Ramin Bostanabad
AI4CE
42
61
0
22 Apr 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
203
2,272
0
18 Oct 2020
FEA-Net: A Physics-guided Data-driven Model for Efficient Mechanical Response Prediction
Houpu Yao
Yi Gao
Yongming Liu
AI4CE
49
66
0
31 Jan 2020
1