A new modified deep learning technique based on physics-informed neural networks (PINNs) for the shock-induced coupled thermoelasticity analysis in a porous material-Reference-Cited by-同舟云学术

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A new modified deep learning technique based on physics-informed neural networks (PINNs) for the shock-induced coupled thermoelasticity analysis in a porous material

Published:2024-04-10 Issue:6 Volume:47 Page:798-825
ISSN:0149-5739
Container-title:Journal of Thermal Stresses
language:en
Short-container-title:Journal of Thermal Stresses

Author:

Eshkofti Katayoun¹,Hosseini Seyed Mahmoud¹

Affiliation:

1. Industrial Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01495739.2024.2321205

Reference79 articles.

1. A review on the applications of porous materials in solar energy systems

2. Porous materials in building energy technologies—A review of the applications, modelling and experiments

3. A nonlinear theory of elastic materials with voids

4. Linear elastic materials with voids

5. A theory of thermoelastic materials with voids

Cited by 1 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

1. The modified physics-informed neural network (PINN) method for the thermoelastic wave propagation analysis based on the Moore-Gibson-Thompson theory in porous materials;Composite Structures;2024-11

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