A TensorFIow-based new high-performance computational framework for CFD  

作　　者：Xi-zeng Zhao Tian-yu Xu Zhou-teng Ye Wei-jie Liu 

机构地区：[1]Ocean College,Zhejiang University,Zhoushan 316021,China [2]The Engineering Research Center of Oceanic Sensing Technology and Equipment,Ministry of Education,Zhejiang University,Zhoushan 316021,China

出　　处：《Journal of Hydrodynamics》2020年第4期735-746,共12页水动力学研究与进展B辑（英文版）

基　　金：Supported by the National Natural Science Foundation of China(Grant No.51679212,51979245).

摘　　要：In this study,a computational framework in the field of artificial intelligence was applied in computational fluid dynamics(CFD)field.This Framework,which was initially proposed by Google Al department,is called"TensorFlow".An improved CFD model based on this framework was developed with a high-order difference method,which is a constrained interpolation profile(CIP)scheme for the base flow solver of the advection term in the Navier-Stokes equations,and preconditioned conjugate gradient(PCG)method was implemented in the model to solve the Poisson equation.Some new features including the convolution,vectorization,and graphics processing unit(GPU)acceleration were implemented to raise the computational efficiency.The model was tested with several benchmark cases and shows good performance.Compared with our former CIP-based model,the present Tensor Flow-based model also shows significantly higher computational efficiency in large-scale computation.The results indicate TensorFlow could be a promising framework for CFD models due to its ability in the computational acceleration and convenience for programming.

关 键 词：TensorFlow VECTORIZATION Navier-Stokes equations graphics processing unit(GPU)acceleration constrained interpolation profile(CIP)method preconditioned conjugate gradient(PCG)method 

分 类 号：TV13[水利工程—水力学及河流动力学]