التفاصيل البيبلوغرافية
| العنوان: |
Physics-informed deep learning for three-dimensional transient heat transfer analysis of functionally graded materials. |
| المؤلفون: |
Guo, Hongwei, Zhuang, Xiaoying, Fu, Xiaolong, Zhu, Yunzheng, Rabczuk, Timon |
| المصدر: |
Computational Mechanics; Sep2023, Vol. 72 Issue 3, p513-524, 12p |
| مصطلحات موضوعية: |
FUNCTIONALLY gradient materials, HEAT transfer, DEEP learning, TRANSIENT analysis, COLLOCATION methods, RUNGE-Kutta formulas |
| مستخلص: |
We present a physics-informed deep learning model for the transient heat transfer analysis of three-dimensional functionally graded materials (FGMs) employing a Runge–Kutta discrete time scheme. Firstly, the governing equation, associated boundary conditions and the initial condition for transient heat transfer analysis of FGMs with exponential material variations are presented. Then, the deep collocation method with the Runge–Kutta integration scheme for transient analysis is introduced. The prior physics that helps to generalize the physics-informed deep learning model is introduced by constraining the temperature variable with discrete time schemes and initial/boundary conditions. Further the fitted activation functions suitable for dynamic analysis are presented. Finally, we validate our approach through several numerical examples on FGMs with irregular shapes and a variety of boundary conditions. From numerical experiments, the predicted results with PIDL demonstrate well agreement with analytical solutions and other numerical methods in predicting of both temperature and flux distributions and can be adaptive to transient analysis of FGMs with different shapes, which can be the promising surrogate model in transient dynamic analysis. [ABSTRACT FROM AUTHOR] |
|
Copyright of Computational Mechanics is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
Find this article in full text from Springer Verlag. 
Full Text Finder