When analyzing the thermal stress and deformation of satellites in orbit, traditional numerical methods, such as finite difference element, are expensive time-consuming. To improve computational efficiency, we propose a deep-learning based surrogate to immediately predict satellite with given temperature field, where U-Net is employed learn end-to-end mapping from field deformation. A data set ...
