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Kerosene-fueled supersonic combustion modeling based on skeletal mechanisms 期刊论文
ACTA MECHANICA SINICA, 2019, 卷号: 35, 期号: 6, 页码: 1155-1177
Authors:  Yao W(姚卫)
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Kerosene  Supersonic combustion  Large eddy simulation  Skeletal mechanism  Scramjet  
Numerical study of convective heat transfer of a supersonic combustor with varied inlet flow conditions 期刊论文
ACTA MECHANICA SINICA, 2019, 卷号: 35, 期号: 5, 页码: 943-953
Authors:  Fan WH(范文慧);  Zhong FQ(仲峰泉);  Ma SG(马素刚);  Zhang XY(张新宇)
View  |  Adobe PDF(4075Kb)  |  Favorite  |  View/Download:309/91  |  Submit date:2020/03/11
Wall heat flux  Numerical simulation  Ethylene  Supersonic combustor  
高速铁路腔室耗能型风屏障气动冲击力的动模型试验研究 期刊论文
机械工程学报, 2019, 卷号: 55, 期号: 18, 页码: 78-85
Authors:  毛军;  柳润东;  郗艳红;  郭迪龙;  赵萌
View  |  Adobe PDF(1169Kb)  |  Favorite  |  View/Download:317/44  |  Submit date:2019/12/16
高速列车  动模型试验  风屏障  脉动压力  
高速列车车体长度对气动噪声影响的数值研究 期刊论文
力学学报, 2019, 卷号: 51, 期号: 05, 页码: 1310-1320
Authors:  莫晃锐;  安翼;  刘青泉
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高速列车  气动噪声  非线性声学求解器  FW-H声比拟法  长编组  
Numerical investigations of fully nonlinear water waves generated by moving bottom topography 期刊论文
Theoretical & Applied Mechanics Letters, 2019, 卷号: 9, 页码: 35-44
Authors:  Wang M(王冕)
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Underwater landslide  Surface gravity waves  Euler equations  
Dynamic experimental studies of A6N01S-T5 aluminum alloy material and structure for high-speed trains 期刊论文
ACTA MECHANICA SINICA, 2019, 卷号: 35, 期号: 4, 页码: 763-772
Authors:  Liu ZS(刘子尚);  Yu YY;  Yang Z(杨哲);  Wei YP(魏延鹏);  Cai JS;  Li MH;  Huang CG(黄晨光)
View  |  Adobe PDF(2832Kb)  |  Favorite  |  View/Download:587/129  |  Submit date:2019/10/14
Dynamic failure strain  Constitutive model  Dynamic mechanical properties  
间隙引发的变载非线性及其闭环辨识 期刊论文
控制理论与应用, 2019, 卷号: 36, 期号: 05, 页码: 673-679
Authors:  张珩;  肖歆昕
View  |  Adobe PDF(8816Kb)  |  Favorite  |  View/Download:316/49  |  Submit date:2019/09/12
间隙变载非线性  间隙闭环辨识  非线性效应  描述函数  自激振荡  
基于滑移速度壁模型的复杂边界湍流大涡模拟 期刊论文
力学学报, 2019, 卷号: 51, 期号: 03, 页码: 754-766
Authors:  时北极;  何国威;  王士召
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滑移速度壁模型  浸入边界方法  大涡模拟  压力梯度  周期山状流  回转体绕流  
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:377/158  |  Submit date:2019/04/11
Deep neural network  channel flow  turbulence model  Reynolds stress