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Explainability analysis of neural network-based turbulence modeling for transonic axial compressor rotor flows 期刊论文
AEROSPACE SCIENCE AND TECHNOLOGY, 2023, 卷号: 141, 页码: 108542
作者:  Wu CT(吴楚畋);  Wang SZ(王士召);  Zhang XL(张鑫磊);  He GW(何国威)
Adobe PDF(3908Kb)  |  收藏  |  浏览/下载：84/0  |  提交时间：2023/09/26
Explainability  Ensemble Kalman method  Turbulence model  Axial compressor rotor  Neural network  Machine learning  
Engineering perspective on bird flight: Scaling, geometry, kinematics and aerodynamics 期刊论文
PROGRESS IN AEROSPACE SCIENCES, 2023, 卷号: 142, 页码: 47
作者:  Liu, Tianshu;  Wang SZ(王士召);  Liu, Hao;  He GW(何国威)
Adobe PDF(39199Kb)  |  收藏  |  浏览/下载：46/1  |  提交时间：2024/01/22
Bird  Flight  Scaling  Flapping wing  Airfoil  Wing geometry  Wing kinematics  Aerodynamics  Vortex  Lift  Drag  Thrust  Thin-airfoil theory  Lifting-line theory  Wake models  Kutta-Joukowski theorem  Actuator disk model  Vortex ring model  CFD  Multiple joint arm system  
Space-time correlations of passive scalar in Kraichnan model 期刊论文
THEORETICAL AND APPLIED MECHANICS LETTERS, 2023, 卷号: 13, 期号: 5, 页码: 100470
作者:  Yang PF(杨平凡);  Pan, Liubin;  He GW(何国威)
Adobe PDF(345Kb)  |  收藏  |  浏览/下载：16/3  |  提交时间：2024/01/15
Space-time correlation  Passive scalar  Kraichnan model  
An interface-resolved phase-change model based on velocity decomposition 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2023, 卷号: 475, 页码: 28
作者:  Lu M(卢敏);  Yang ZX(杨子轩);  He GW(何国威)
Adobe PDF(3953Kb)  |  收藏  |  浏览/下载：148/0  |  提交时间：2023/02/20
Phase-change model  Velocity decomposition  Multi-phase flow  
Towards multi-fidelity simulation of flows around an underwater vehicle with appendages and propeller 期刊论文
THEORETICAL AND APPLIED MECHANICS LETTERS, 2022, 卷号: 12, 期号: 1, 页码: 100318
作者:  Zhou ZD(周志登);  Li ZB(李曌斌);  He GW(何国威);  Yang XL(杨晓雷)
Adobe PDF(2422Kb)  |  收藏  |  浏览/下载：21/3  |  提交时间：2024/01/15
Multi-fidelity model  Large-eddy simulation  Immersed boundary method  Actuator disk model  DARPA suboff  
Subgrid-scale model for large-eddy simulation of isotropic turbulent flows using an artificial neural network 期刊论文
COMPUTERS & FLUIDS, 2019, 卷号: 195, 页码: UNSP 104319
作者:  Zhou ZD(周志登);  He GW(何国威);  Wang SZ(王士召);  Jin GD(晋国栋)
浏览  |  Adobe PDF(4058Kb)  |  收藏  |  浏览/下载：581/187  |  提交时间：2019/12/17
Machine learning  Artificial neural network  Subgrid-scale model  Large-eddy simulation  Isotropic turbulent flows  
Wall-modeling for large-eddy simulation of flows around an axisymmetric body using the diffuse-interface immersed boundary method 期刊论文
APPLIED MATHEMATICS AND MECHANICS-ENGLISH EDITION, 2019, 卷号: 40, 期号: 3, 页码: 305-320
作者:  Shi BJ(时北极);  Yang XL(杨晓雷);  Jin GD(晋国栋);  He GW(何国威);  Wang SZ(王士召)
浏览  |  Adobe PDF(860Kb)  |  收藏  |  浏览/下载：360/90  |  提交时间：2019/04/11
wall model  large-eddy simulation (LES)  immersed boundary (IB) method  diffuse-interface  
Lattice-Boltzmann lattice-spring simulations of two flexible fibers settling in moderate Reynolds number flows 期刊论文
COMPUTERS & FLUIDS, 2018, 卷号: 167, 页码: 341-358
作者:  Alhasan Ahmed A;  Luo Y;  Wu TH;  He GW(何国威);  Qi DW
浏览  |  Adobe PDF(5318Kb)  |  收藏  |  浏览/下载：346/109  |  提交时间：2018/07/17
Lattice Boltzmann Method  Lattice Spring Model  Hemodynamics  Elastic Vessel  Blockage  
Multi-flexible fiber flows: A direct-forcing immersed boundary lattice-Boltzmann lattice-spring approach 期刊论文
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW, 2018, 卷号: 99, 页码: 408-422
作者:  Tang YH;  Wu TH;  He GW(何国威);  Qi DW
浏览  |  Adobe PDF(4262Kb)  |  收藏  |  浏览/下载：445/130  |  提交时间：2018/10/30
Lattice Boltzmann equation  Lattice spring model  Flexible fibers  Fiber network  Drainage rate  Immersed boundary method  Rigidity  Flexibility  
Space-Time Correlations and Dynamic Coupling in Turbulent Flows 期刊论文
ANNUAL REVIEW OF FLUID MECHANICS, 2017, 卷号: 49, 页码: 51-70
作者:  He GW(何国威);  Jin GD(晋国栋);  Yang Y;  He, GW (reprint author), Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing 100190, Peoples R China.
浏览  |  Adobe PDF(2133Kb)  |  收藏  |  浏览/下载：883/323  |  提交时间：2017/07/24
Eulerian And Lagrangian Time Correlations  Large-eddy Simulation  Taylor's Frozen-flow Hypothesis  Time-accurate Subgrid-scale Model  Turbulence-generated Noise  Particle-laden Turbulence