PRELIMINARY INVESTIGATION ON UNSTRUCTURED MESH GENERATION TECHNIQUE BASED ON ADVANCING FRONT METHOD AND MACHINE LEARNING METHODS

Wang Nianhua; Lu Peng; Chang Xinghua; Zhang Laiping

doi:10.6052/0459-1879-20-402

Volume 53 Issue 3

Mar. 2021

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Chinese Journal of Theoretical and Applied Mechanics > 2021 > 53(3): 740-751. > DOI: 10.6052/0459-1879-20-402 CSTR: 32045.14.0459-1879-20-402

Wang Nianhua, Lu Peng, Chang Xinghua, Zhang Laiping. PRELIMINARY INVESTIGATION ON UNSTRUCTURED MESH GENERATION TECHNIQUE BASED ON ADVANCING FRONT METHOD AND MACHINE LEARNING METHODS[J]. Chinese Journal of Theoretical and Applied Mechanics, 2021, 53(3): 740-751. DOI: 10.6052/0459-1879-20-402

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PRELIMINARY INVESTIGATION ON UNSTRUCTURED MESH GENERATION TECHNIQUE BASED ON ADVANCING FRONT METHOD AND MACHINE LEARNING METHODS

Wang Nianhua^*,2), ,,
Lu Peng^†,**,
Chang Xinghua^††,
Zhang Laiping^††

^*State Key Laboratory of Aerodynamics,China Aerodynamics Research and Development Center,Mianyang 621000,Sichuan,China
^††School of Information Engineering,Southwest University of Science and Technology,Mianyang 621010,Sichuan,China
^**School of Intelligent Manufacturing Engineering,Chongqing University of Arts and Science,Chongqing 402160,China
^†††Unmanned Systems Research Center,National Innovation Institute of Defense Technology,Beijing 100071,China

Received Date: November 26, 2020

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Abstract

Mesh generation and adaptation are bottleneck problems restricting future development of computational fluid dynamics (CFD). Automatic and intelligent mesh generation is still worth continuous investigation. With the rapid progress in high-performance computing power and big data technology, artificial intelligence, represented by machine learning, has been successfully applied to multiple fields including fluid dynamics, which has revolutionarily boosted the development of these fields. This paper reviews briefly the application of machine learning in the unstructured mesh generation in CFD and analyzes the key issues in the mesh generation based on machine learning. Meanwhile, the sample data format is designed and the automatic extraction of unstructured mesh sample data sets is realized. By integrating the advancing front (AFT) method with the artificial neural network, a novel two-dimensional triangular grid generation method is developed based on machine learning. Finally, several isotropic unstructured grids and hybrid grids (2D cylinder, 2D NACA0012 airfoil, and 30p30n three-element airfoil) are generated and mesh quality and elapsed time are counted, it indicates that mesh quality is generally equivalent to commercial software and the efficiency is 30% higher than the traditional AFT method.
- machine learning,
- artificial neural network,
- computational fluid dynamics,
- mesh generation,
- advancing front method

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PRELIMINARY INVESTIGATION ON UNSTRUCTURED MESH GENERATION TECHNIQUE BASED ON ADVANCING FRONT METHOD AND MACHINE LEARNING METHODS

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