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Convergence acceleration of continuous adjoint solvers using a reduced‐order model

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Summary A novel acceleration technique using a reduced-order model is presented to speed up convergence of continuous adjoint solvers. The acceleration is achieved by projecting to an improved solution within… Click to show full abstract

Summary A novel acceleration technique using a reduced-order model is presented to speed up convergence of continuous adjoint solvers. The acceleration is achieved by projecting to an improved solution within an iterative process solely using early solution results. This is achieved by forming basis vectors from early iteration adjoint solutions to perform model order reduction of the adjoint equations. The reduced-order model of the adjoint equations is then substituted into the full-order discretized governing equations to determine weighting coefficients for each basis vector. With these coefficients, a linear combination of the basis vectors is used to project to an improved solution. The method is applied to three inviscid quasi-1D nozzle flow cases including fully subsonic flow, subsonic inlet to supersonic outlet flow, and transonic flow with a shock. Significant cost reductions are achieved for a single application as well as repeated applications of the convergence acceleration technique. This article is protected by copyright. All rights reserved.

Keywords: reduced order; adjoint; order model; order; acceleration

Journal Title: International Journal for Numerical Methods in Fluids
Year Published: 2018

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