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中国科学院力学研究所机构知识库
Knowledge Management System of Institue of Mechanics, CAS
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Key Labora... [7]
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叶舒然 [7]
张珍 [7]
王一伟 [7]
黄晨光 [7]
Song XD [2]
Chen YS [1]
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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)
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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)
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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)
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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
A flow feature detection method for modeling pressure distribution around a cylinder in non-uniform flows by using a convolutional neural network
期刊论文
SCIENTIFIC REPORTS, 2020, 卷号: 10, 期号: 1, 页码: 10
Authors:
Ye SR(叶舒然)
;
Zhang Z(张珍)
;
Song XD
;
Wang YW(王一伟)
;
Chen YS
;
Huang CG(黄晨光)
Adobe PDF(4204Kb)
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Submit date:2020/10/29
自动编码器在流场降阶中的应用
期刊论文
空气动力学学报, 2019, 卷号: 37, 期号: 03, 页码: 498-504
Authors:
叶舒然
;
张珍
;
宋旭东
;
杜特专
;
王一伟
;
黄晨光
;
陈耀松
View
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Submit date:2019/09/12
机器学习
自动编码器
圆柱绕流
流场特征提取
压力预测
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)
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Submit date:2020/11/20
Cross-validation
Multi-layer neural network
Reynolds stress
Turbulence model
Transfer learning for modeling pressure coefficient around cylinder using CNN
会议论文
29th International Ocean and Polar Engineering Conference, ISOPE 2019, Honolulu, HI, United states, June 16, 2019 - June 21, 2019
Authors:
Ye SR(叶舒然)
;
Wang YW(王一伟)
;
Zhang Z(张珍)
;
Huang CG(黄晨光)
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Submit date:2020/11/20
Convolutional neural networks
Flow field analysis
Pressure prediction
Transfer learning