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典型文献
Fourier neural operator approach to large eddy simulation of three-dimensional turbulence
文献摘要:
Fourier neural operator (FNO) model is developed for large eddy simulation (LES) of three-dimensional (3D) turbulence. Velocity fields of isotropic turbulence generated by direct numerical simulation (DNS) are used for training the FNO model to predict the filtered velocity field at a given time. The input of the FNO model is the filtered velocity fields at the previous several time-nodes with large time lag. In the a posteriori study of LES, the FNO model performs better than the dynamic Smagorinsky model (DSM) and the dynamic mixed model (DMM) in the prediction of the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and the instantaneous flow structures. Moreover, the proposed model can significantly reduce the computational cost, and can be well generalized to LES of turbulence at higher Taylor-Reynolds numbers.
文献关键词:
作者姓名:
Zhijie Li;Wenhui Peng;Zelong Yuan;Jianchun Wang
作者机构:
Department of Mechanics and Aerospace Engineering,Southern University of Science and Technology,Shenzhen 518055,China;Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou),511458,China;Guangdong-Hong Kong-Macao Joint Laboratory for Data-Driven Fluid Mechanics and Engineering Applications,Southern University of Science and Technology,Shenzhen 518055,China;Department of Computer Engineering,Polytechnique Montreal,Montreal H3T1J4,Canada
引用格式:
[1]Zhijie Li;Wenhui Peng;Zelong Yuan;Jianchun Wang-.Fourier neural operator approach to large eddy simulation of three-dimensional turbulence)[J].力学快报(英文),2022(06):438-444
A类:
FNO
B类:
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AB值:
0.53576
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