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A Flow Field Super-resolution Strategy for Direct Numerical Simulation Based on Physics-informed Convolutional Neural Networks
Hanqing Ouyang, Zhicheng Zhu, Weixiong Zheng,
Jia Hao
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此作品的通讯作者
机械与车辆学院
Beijing Institute of Technology
China University of Mining & Technology, Beijing
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探究 'A Flow Field Super-resolution Strategy for Direct Numerical Simulation Based on Physics-informed Convolutional Neural Networks' 的科研主题。它们共同构成独一无二的指纹。
分类
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Engineering
Computational Fluid Dynamics
25%
Computer Simulation
25%
Convolutional Neural Network
100%
Direct Numerical Simulation
100%
Discretization
25%
Dynamic Method
25%
Engineering
50%
Flow Field
100%
High Resolution
75%
Improve Efficiency
25%
Newtonian Fluid
25%
Simulation Result
25%
Simulation Time
25%
Solution Domain
25%
Physics
Computational Fluid Dynamics
25%
Convolutional Neural Network
100%
Direct Numerical Simulation
100%
Flow Distribution
100%
High Resolution
75%
nonNewtonian Fluids
25%
Physics
100%
Material Science
Computational Fluid Dynamics
100%
Chemical Engineering
Neural Network
100%
Earth and Planetary Sciences
nonNewtonian Fluids
50%