Coping with shock : numerical procedure for the detection and sorting of shocks in fluid flows

Abstract

Within computational fluid dynamics (CFD) simulations, many complex flow phenomena can emerge. Accurately modeling these phenomena is often a primary motivating factor behind these simulations, and shocks are some of the most challenging phenomena to either model or resolve. However, once a shock is identified and well defined within a flow, there are many proven tools available to both improve the resolution of a given shock, and to efficiently propagate it through space. These methods often rely upon key geometric and/or mesh information related to the shocks, but such knowledge is non-trivial to obtain apriori. This thesis presents a numerical procedure to efficiently detect shocks, filter them to eliminate noise, and sort them into separate shocks or individual shock segments for further analysis. The resulting information could be used for shock fitting, anisotropic layered meshing, or analysis of complex shocks. A combination of numerical simulation data and manufactured data is used to demonstrate the performance of the current procedure. Overall, the novelprocedure developed in this work is robust, and results obtained thus far demonstrate its efficacy.