Details

Autor(en) / Beteiligte

• Li, Zhijie
• Peng, Wenhui
• Yuan, Zelong
• Wang, Jianchun

Titel

Fourier neural operator approach to large eddy simulation of three-dimensional turbulence

Ist Teil von

• Theoretical and applied mechanics letters, 2022-11, Vol.12 (6), p.100389, Article 100389

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2022

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• •The FNO model is developed for large eddy simulation of 3D turbulence.•The FNO model can perform with higher accuracy and more efficiency than the traditional models in the LES of turbulence.•The Model trained on data with low Reynolds numbers can be well generalized to LES at higher Reynolds numbers. 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.