We have studied the prediction of numerical fluid dynamics results using AI techniques. In the past, we have used Convolutional LSTM to predict future spatial information from space-time information. We found that only CNNs with flow fields as spatial information can predict analytical results with high accuracy when the training data are under the same time evolution conditions. Therefore, we will examine whether the solution can be solved stably even when the time evolution of the numerical fluid dynamics analysis is greatly increased based on the results predicted using CNNs.
Masuda et al. (Wed,) studied this question.