典型文献
A new dynamic subgrid-scale model using artificial neural network for compressible flow
文献摘要：
The subgrid-scale (SGS) kinetic energy has been used to predict the SGS stress in compressible flow and it was resolved through the SGS kinetic energy transport equation in past studies. In this paper, a new SGS eddy-viscosity model is proposed using artificial neural network to obtain the SGS kinetic energy precisely, instead of using the SGS kinetic energy equation. Using the infinite series expansion and reserving the first term of the expanded term, we obtain an approximated SGS kinetic energy, which has a high correlation with the real SGS kinetic energy. Then, the coe?cient of the modelled SGS kinetic energy is resolved by the artificial neural network and the modelled SGS kinetic energy is more accurate through this method compared to the SGS kinetic energy obtained from the SGS kinetic energy equation. The coe?cients of the SGS stress and SGS heat flux terms are determined by the dynamic procedure. The new model is tested in the compressible turbulent channel flow. From the a posterior tests, we know that the new model can precisely predict the mean velocity, the Reynolds stress, the mean temperature and turbulence intensities, etc.
文献关键词：
中图分类号：
作者姓名：
Han Qi;Xinliang Li;Ning Luo;Changping Yu
作者机构：
LHD,Institute of Mechanics,Chinese Academy of Sciences,Beijing 100190,China;School of Engineering Science,University of Chinese Academy of Sciences,Beijing 100049,China;State Key Laboratory for Geomechanics and Deep Underground Engineering,China University of Mining and Technology,Xuzhou 221116,China
文献出处：
引用格式：
[1]Han Qi;Xinliang Li;Ning Luo;Changping Yu-.A new dynamic subgrid-scale model using artificial neural network for compressible flow)[J].力学快报（英文）,2022(04):267-274
A类：
subgrid,reserving
B类：
new,dynamic,scale,using,artificial,neural,network,compressible,flow,SGS,kinetic,energy,has,been,used,predict,stress,was,resolved,through,transport,equation,past,studies,In,this,paper,eddy,viscosity,proposed,precisely,instead,Using,infinite,series,expansion,first,expanded,we,approximated,which,high,correlation,real,Then,coe,modelled,by,more,accurate,method,compared,obtained,from,cients,heat,flux,terms,determined,procedure,tested,turbulent,channel,From,posterior,tests,know,that,can,mean,velocity,Reynolds,temperature,turbulence,intensities,etc
AB值：
0.413768
相似文献
机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
