Incremental SVD compression reduces memory and computational cost for history terms in finite element discretizations of nonlinear Oldroyd problems with general kernels while retaining accuracy for small tolerances under low-rank assumptions.
Oxberry, Tanya Kostova-Vassilevska, William Arrighi, and Kyle Chand
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Incremental SVD Compression for Nonlinear Oldroyd Equations with General Memory Kernels
Incremental SVD compression reduces memory and computational cost for history terms in finite element discretizations of nonlinear Oldroyd problems with general kernels while retaining accuracy for small tolerances under low-rank assumptions.