Error estimates for SUPG-stabilised Dynamical Low Rank Approximations
CoRR(2024)
摘要
We perform an error analysis of a fully discretised Streamline Upwind Petrov
Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent
advection-dominated problems. The time integration scheme has a splitting-like
nature, allowing for potentially efficient computations of the factors
characterising the discretised random field. The method allows to efficiently
compute a low-rank approximation of the true solution, while naturally
"inbuilding" the SUPG stabilisation. Standard error rates in the L2 and
SUPG-norms are recovered. Numerical experiments validate the predicted rates.
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