Abstract
AbstractIn this work, we extend the characteristic-featured shock wave indicator based on artificial neuron training to 3D high-speed flow simulation on unstructured meshes. The extension is achieved through dimension splitting. This leads to that the proposed indicator is capable of identifying regions of flow compression in any direction. With this capability, the indicator is further developed to combine with h-adaptivity of mesh refinement to improve resolution with less computational costs. The present indicator provides an attractive alternative for constructing high-resolution, high-efficiency shock-processing methods to simulate high-speed inviscid flows.
Funder
National Numerical Wind Tunnel Project
National Natural Science Foundation of China
Academic Excellence Foundation of BUAA for PHD Students
China Postdoctoral Science Foundation
Publisher
Springer Science and Business Media LLC