Abstract
Efficient choice of the initial guess for the iterative solution of series of systems is considered. The series of systems are typical for unsteady nonlinear fluid flow problems. The history of iterative solution at previous time steps is used for computing a better initial guess. This strategy is applied for two iterative linear system solvers (GCR and GMRES). A reduced model technique is developed for implicitly discretized nonlinear evolution problems. The technique computes a better initial guess for the inexact Newton method. The methods are successfully tested in parallel CFD simulations. The latter approach is suitable for GRID computing as well.
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Tromeur-Dervout, D., Vassilevski, Y. (2010). Acceleration of iterative solution of series of systems due to better initial guess. In: Tromeur-Dervout, D., Brenner, G., Emerson, D., Erhel, J. (eds) Parallel Computational Fluid Dynamics 2008. Lecture Notes in Computational Science and Engineering, vol 74. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14438-7_3
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DOI: https://doi.org/10.1007/978-3-642-14438-7_3
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