IMECH-IR  > 流固耦合系统力学重点实验室
Reconstruction of RANS model and cross-validation of flow field based on tensor basis neural network
Song XD; Zhang Z(张珍); Wang YW(王一伟); Ye SR(叶舒然); Huang CG(黄晨光)
Source PublicationASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference, AJKFluids 2019
2019
Conference NameASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference, AJKFluids 2019
Conference DateJuly 28, 2019 - August 1, 2019
Conference PlaceSan Francisco, CA, United states
Abstract

The solution of the Reynolds-averaged Navier-Stokes (RANS) equation has been widely used in engineering problems. However, this model does not provide satisfactory prediction accuracy. Because the widely used eddy viscosity model assumes a linear relationship between the Reynolds stress and the average strain rate tensor and these linear models cannot capture the anisotropic characteristics of the actual flow. In this paper, two kinds of flow field structures of two-dimensional cylindrical flow and circular tube jet are calculated by using the RANS model. Secondly, in order to improve the prediction accuracy of the RANS model, the Reynolds stress of the RANS model is reconstructed by the tensor basis neural network algorithm based on nonlinear eddy viscosity model. Finally, the model trained by neural network is cross-validated, and compare the cross-test results with the traditional RANS k-eps model. The results show that the multi-layer neural network method has achieved good results in turbulence model reconstruction. Copyright © 2019 ASME.

KeywordCross-validation Multi-layer neural network Reynolds stress Turbulence model
ISBN9780791859032
URL查看原文
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://dspace.imech.ac.cn/handle/311007/85115
Collection流固耦合系统力学重点实验室
Affiliation1.College of Engineering, Peking University, Beijing, China
2.Key Laboratory for Mechanics in Fluid Solid Coupling Systems, Institute of Mechanics, Chinese Academy of Sciences, Beijing, China
3.School of Engineering Science, University of Chinese Academy of Science, Beijing, China
Recommended Citation
GB/T 7714
Song XD,Zhang Z,Wang YW,et al. Reconstruction of RANS model and cross-validation of flow field based on tensor basis neural network[C]ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference, AJKFluids 2019,2019.
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