Adjoint-based error estimation and grid adaptation for functional outputs: Application to two-dimensional, inviscid, incompressible flows

Abstract

Adjoint-based error estimation and grid adaptive procedures are investigated for their robustness and effectiveness in improving the accuracy of functional outputs such as lift and drag. The adjoint error estimates relate the global error in the output function to the local residual errors in the flow solution via adjoint variables as weight functions. These error estimates are used as a correction to produce improved functional estimates. Based on this error correction procedure, two output-based grid adaptive approaches are implemented and compared. While both approaches strive to improve the accuracy of the computed output, the means by which the adaptation parameters are formed differ. The first approach strives to improve the computable error estimates by forming adaptation parameters based on the level of error in the computable error estimates. The second approach uses the computable error estimates as adaptation parameters. Grid adaptation is performed with h-refinement and results are presented for two-dimensional, inviscid, incompressible flows.