Zobrazeno 1 - 10
of 203
pro vyhledávání: '"Zhang, Laiping"'
Publikováno v:
Physics of Fluids 36 (10) 2024
Advances in deep learning have enabled physics-informed neural networks to solve partial differential equations. Numerical differentiation using the finite-difference (FD) method is efficient in physics-constrained designs, even in parameterized sett
Externí odkaz:
http://arxiv.org/abs/2406.10534
In this study, we present a novel computational framework that integrates the finite volume method with graph neural networks to address the challenges in Physics-Informed Neural Networks(PINNs). Our approach leverages the flexibility of graph neural
Externí odkaz:
http://arxiv.org/abs/2405.04466
Publikováno v:
Physics of Fluids 1 April 2024; 36 (4): 043601
The rapid development of deep learning has significant implications for the advancement of Computational Fluid Dynamics (CFD). Currently, most pixel-grid-based deep learning methods for flow field prediction exhibit significantly reduced accuracy in
Externí odkaz:
http://arxiv.org/abs/2309.10050
Publikováno v:
In Journal of Molecular Structure 15 December 2024 1318 Part 1
Publikováno v:
In Applied Soft Computing March 2024 154
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
In Journal of Computational Science September 2023 72
Publikováno v:
In Engineering Applications of Artificial Intelligence August 2023 123 Part B
Autor:
Wang, Nianhua1,2 (AUTHOR) nhwang@skla.cardc.cn, Zhang, Laiping3 (AUTHOR), Deng, Xiaogang4 (AUTHOR)
Publikováno v:
Computational Mechanics. Feb2024, Vol. 73 Issue 2, p341-364. 24p.
Autor:
Ji, Yuchun, Li, Zhengde, Zhang, Laiping, Wang, Jilin, Li, Wenbiao, Chen, Wenzhuo, Zheng, Guoyuan, Long, Fei, Zou, Zhengguang
Publikováno v:
In Materials Today Communications June 2023 35