A Mixed Operator Overloading and Source Transformation Approach for Adjoint CFD Computation

Adjoint based calculation of sensitivities pertaining to a Computational Fluid Dynamics (CFD) Solver has proven to be a vital tool in tackling large scale problems often found in industrial applications. There are two basic approaches for applying Algorithmic Differentiation (AD) to a CFD solver, namely, Operator Overloading and Source Transformation. Unfortunately, in both cases, it is still necessary to invest a significant amount of manual coding in order to get to an application that performs acceptably in terms of memory consumption and runtime. In this paper reverse mode of AD has been applied to an unstructured pressure based steady Navier-Stokes solver. We explore the feasibility of combining both kinds of AD approaches to show where and how the advantages of each method can be exploited in order to reach a suitable compromise between performance, simplicity and efficiency. Additionally,we propose a methodology to automate the implementation of an adjoint software in order to minimize work the developer must carry out to produce the desired derivative. We investigate the effectiveness of this approach for relevant flow test cases