Latest revision as of 16:06, 25 November 2022

Summary

A relaxed, high-order, Multidimensional Optimal Order Detection (MOOD) framework is extended to the simulation of compressible multicomponent flows on unstructured meshes in the open-source unstructured compressible flow solver UCNS3D. The class of diffuse interface methods (DIM) is employed with a five-equation model. The high-order CWENO spatial discretisation is selected due to its low computational cost and improved non-oscillatory behaviour compared to the original WENO variants. The relaxed MOOD enhancement of the CWENO method has been necessary to further improve the robustness of the CWENO method. A series of challenging compressible multicomponent flow problems have been implemented in UCNS3D, including shock wave interaction with a water droplet and shock-induced collapse of bubbles arrays. Such problems are generally very stiff due to the strong gradients present, and it has been possible to tackle them using the extended MOOD-CWENO numerical framework.

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