Abstract
Adaptive mesh refinement (AMR) automatically makes finer computational grids at only the important part of flows and improves accuracy of flow simulations. AMR needs methods which detect the important part such as shock waves. One of the methods is neural network for detection of flow discontinuities. The neural network is based on spatiotemporal visual processing which can detect discontinuities of illumination. So, the neural network detects discontinuities in numerical simulations of a supersonic flow. However, the neural network has not been yet applied to AMR. In this study, we applied neural network for detection of flow discontinuities to adaptive mesh refinement and showed its performance.
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