Model Order Reduction for Problems with large Convection Effects

Abstract : The reduced basis method allows to propose accurate approximations for many parameter dependent partial differential equations, almost in real time, at least if the Kolmogorov n-width of the set of all solutions is small, under variation of the parameters. The idea is that any solutions may be well approximated by the linear combination of some well chosen solutions that are computed once and for all (by another, more expensive, discretization) for some well chosen parameter values. In some cases however, such as for problems with large convection effects, the linear representation is not sufficient and, as a consequence, the set of solutions needs to be transformed/twisted so that the combination of the proper twist and the appropriate linear combination recovers an accurate approximation. This paper presents a simple approach towards this direction, preliminary simulations support this approach.
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Submitted on : Thursday, November 10, 2016 - 8:13:02 PM
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Nicolas Cagniart, Yvon Maday, Benjamin Stamm. Model Order Reduction for Problems with large Convection Effects. 2016. ⟨hal-01395571⟩

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