This paper introduces a novel surrogate model for two-dimensional adaptive steady-state
thermal convection fields based on deep learning technology. The proposed model aims to
overcome limitations in traditional frameworks caused by network types, such as the
requirement for extensive training data, accuracy loss due to pixelated preprocessing of
original data, and inability to predict information near the boundaries with precision. We
propose a new framework that consists primarily of a physical-informed neural network …