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单孔排气气泡特征识别与参数提取方法 期刊论文
化工进展, 2024, 卷号: 43, 期号: 02, 页码: 808-817
Authors:  杨志龙;  田文斌;  张珍;  王志英;  王一伟
Adobe PDF(2825Kb)  |  Favorite  |  View/Download：29/7  |  Submit date：2024/04/28
气液两相流  重叠气泡识别  气泡特征统计  高速摄像  
Data-driven turbulence model for unsteady cavitating flow 期刊论文
PHYSICS OF FLUIDS, 2023, 卷号: 35, 期号: 1, 页码: 18
Authors:  Zhang Z(张珍);  Wang JZ(王静竹);  Huang RF(黄仁芳);  Qiu RD(丘润荻);  Chu, Xuesen;  Ye SR(叶舒然);  Wang YW(王一伟);  Liu, Qingkuan
Adobe PDF(4681Kb)  |  Favorite  |  View/Download：162/8  |  Submit date：2023/02/27
Mesoscale analysis of the suction stress characteristic curve for unsaturated granular materials 期刊论文
PARTICUOLOGY, 2021, 卷号: 56, 页码: 183-192
Authors:  Wang XL(王晓亮);  Zhang Z(张珍);  Li JC(李家春);  Liu QQ(刘青泉)
Adobe PDF(2899Kb)  |  Favorite  |  View/Download：391/65  |  Submit date：2021/05/17
Suction stress  Liquid bridge  Unsaturated granular material  Discrete element method  
基于组合神经网络的雷诺平均湍流模型多次修正方法 期刊论文
力学学报, 2021, 卷号: 53, 期号: 06, 页码: 1532-1542
Authors:  张珍;  叶舒然;  岳杰顺;  王一伟;  黄晨光
Adobe PDF(7671Kb)  |  Favorite  |  View/Download：313/67  |  Submit date：2021/11/12
组合神经网络  雷诺平均  各向异性  隐式修正  精度闭环  
A semi-implicit discrepancy model of Reynolds stress in a higher-order tensor basis framework for Reynolds-averaged Navier-Stokes simulations 期刊论文
AIP ADVANCES, 2021, 卷号: 11, 期号: 4, 页码: 17
Authors:  Zhang Z(张珍);  Ye SR(叶舒然);  Yin B(银波);  Song, Xudong;  Wang YW(王一伟);  Huang CG(黄晨光);  Chen, Yaosong
Adobe PDF(9395Kb)  |  Favorite  |  View/Download：291/51  |  Submit date：2021/06/07
基于卷积神经网络的深度学习流场特征识别及应用进展 期刊论文
航空学报, 2021, 卷号: 42, 期号: 04, 页码: 185-199
Authors:  叶舒然;  张珍;  王一伟;  黄晨光
Adobe PDF(3737Kb)  |  Favorite  |  View/Download：755/220  |  Submit date：2021/08/25
卷积神经网络  流场识别  流动预测  外形优化  泊松方程  生成对抗网络  深度学习  
Energy performance prediction of the centrifugal pumps by using a hybrid neural network 期刊论文
Energy, 2020, 卷号: 213, 页码: 119005
Authors:  Huang RF(黄仁芳);  Zhang Z(张珍);  Zhang W;  Mou JG;  Zhou PJ;  Wang YW(王一伟)
Adobe PDF(4596Kb)  |  Favorite  |  View/Download：336/141  |  Submit date：2021/01/29
Centrifugal pump  Energy performance  Loss model  Physics-informed neural network  
Triaxial behavior of granular material under complex loading path by a new numerical true triaxial engine 期刊论文
ADVANCED POWDER TECHNOLOGY, 2019, 卷号: 30, 期号: 4, 页码: 700-706
Authors:  Wang XL(王晓亮);  Zhang Z(张珍);  Li JC(李家春)
View  |  Adobe PDF(2025Kb)  |  Favorite  |  View/Download：354/130  |  Submit date：2019/05/30
Granular material  Stress path  Strength criterion  Discrete element method  Numerical true triaxial engine  
Application of deep learning method to Reynolds stress models of channel flow based on reduced-order modeling of DNS data 期刊论文
JOURNAL OF HYDRODYNAMICS, 2019, 卷号: 31, 期号: 1, 页码: 58-65
Authors:  Zhang Z(张珍);  Song XD;  Ye SR;  Wang YW(王一伟);  Huang CG(黄晨光);  An YR;  Chen YS
View  |  Adobe PDF(1492Kb)  |  Favorite  |  View/Download：378/158  |  Submit date：2019/04/11
Deep neural network  channel flow  turbulence model  Reynolds stress  
Reconstruction of RANS model and cross-validation of flow field based on tensor basis neural network 会议论文
ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference, AJKFluids 2019, San Francisco, CA, United states, July 28, 2019 - August 1, 2019
Authors:  Song XD;  Zhang Z(张珍);  Wang YW(王一伟);  Ye SR(叶舒然);  Huang CG(黄晨光)
Favorite  |  View/Download：132/0  |  Submit date：2020/11/20
Cross-validation  Multi-layer neural network  Reynolds stress  Turbulence model