Analysis of three-dimensional potential problems in non-homogeneous media with physics-informed deep collocation method using material transfer learning and sensitivity analysis

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Guo, H.; Zhuang, X.; Chen, P.; Alajlan, N.; Rabczuk, T.: Analysis of three-dimensional potential problems in non-homogeneous media with physics-informed deep collocation method using material transfer learning and sensitivity analysis. In: Engineering with computers : an international journal for simulation-based engineering 38 (2022), S. 5423-5444. DOI: https://doi.org/10.1007/s00366-022-01633-6

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Sum total of downloads: 52




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Abstract: 
In this work, we present a deep collocation method (DCM) for three-dimensional potential problems in non-homogeneous media. This approach utilizes a physics-informed neural network with material transfer learning reducing the solution of the non-homogeneous partial differential equations to an optimization problem. We tested different configurations of the physics-informed neural network including smooth activation functions, sampling methods for collocation points generation and combined optimizers. A material transfer learning technique is utilized for non-homogeneous media with different material gradations and parameters, which enhance the generality and robustness of the proposed method. In order to identify the most influential parameters of the network configuration, we carried out a global sensitivity analysis. Finally, we provide a convergence proof of our DCM. The approach is validated through several benchmark problems, also testing different material variations. © 2022, The Author(s).
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2022
Appears in Collections:Fakultät für Mathematik und Physik

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pos. country downloads
total perc.
1 image of flag of Germany Germany 21 40.38%
2 image of flag of United States United States 16 30.77%
3 image of flag of China China 5 9.62%
4 image of flag of No geo information available No geo information available 1 1.92%
5 image of flag of Taiwan Taiwan 1 1.92%
6 image of flag of Russian Federation Russian Federation 1 1.92%
7 image of flag of Norway Norway 1 1.92%
8 image of flag of Netherlands Netherlands 1 1.92%
9 image of flag of India India 1 1.92%
10 image of flag of Israel Israel 1 1.92%
    other countries 3 5.77%

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