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Physics-Driven Learning of the Steady Navier-Stokes Equations using Deep Convolutional Neural Networks被引量：1: 《Communications in Computational Physics》2022年第8期715-736,共22页Hao Ma Yuxuan Zhang Nils Thuerey Xiangyu Hu Oskar J.Haidn; Hao Ma(No.201703170250)and Yuxuan Zhang(No.201804980021)are supported by China Scholarship Council when they conduct the work this paper represents.; Recently,physics-driven deep learning methods have shown particular promise for the prediction of physical fields,especially to reduce the dependency on large amounts of pre-computed training data.In this work,we targ...; 关键词：Deep learning physics-drivenmethod convolutional neural networks Navier-Stokes equations

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