AD tools and prospects for optimal AD in CFD flux Jacobian calculations

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2002-01-01T00:00:00Z

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Tadjouddine M, Forth S, Pryce J. (2002). AD Tools and Prospects for Optimal AD in CFD Flux Jacobian Calculations. In: Automatic Differentiation of Algorithms. Springer, New York, NY

Abstract

We consider the problem of linearising the short (approximately 100 lines of) code that defines the numerical fluxes of mass, energy and momentum across a-cell face in a finite volume compressible flow calculation. Typical of such formulations is the numerical flux due to Roe, widely used in the numerical approximation of flow fields containing moderate to strong shocks. Roe's flux takes as input 10 variables describing the flow either side of a cell face and returns as output the 5 variables for the numerical flux. We present results concerning the efficiency of derivative calculations for Roe's flux using several currently available AD tools. We also present preliminary work on deriving near optimal differentiated code using the node elimination approach. We show that such techniques, within a source transformation approach, will yield substantial gains for application code such as the Roe flux.

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Github

Keywords

automatic differentiation, computational fluid dynamics, Jacobian

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