Geom-DeepONet: A point-cloud-based deep operator network for field predictions on 3D parameterized geometries
-
Published:2024-09
Issue:
Volume:429
Page:117130
-
ISSN:0045-7825
-
Container-title:Computer Methods in Applied Mechanics and Engineering
-
language:en
-
Short-container-title:Computer Methods in Applied Mechanics and Engineering
Author:
He JunyanORCID,
Koric SeidORCID,
Abueidda DiabORCID,
Najafi Ali,
Jasiuk IwonaORCID
Reference43 articles.
1. Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data;Sun;Comput. Methods Appl. Mech. Engrg.,2020
2. A physics and data co-driven surrogate modeling approach for temperature field prediction on irregular geometric domain;Bao;Struct. Multidiscip. Optim.,2022
3. Charles R. Qi, Hao Su, Kaichun Mo, Leonidas J. Guibas, Pointnet: Deep learning on point sets for 3d classification and segmentation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 652–660.
4. Pointnet++: Deep hierarchical feature learning on point sets in a metric space;Qi,2017
5. A point-cloud deep learning framework for prediction of fluid flow fields on irregular geometries;Kashefi;Phys. Fluids,2021
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献