An iSVD-based adaptive ROM framework updates reduced bases with occasional full-order snapshots, showing improved accuracy and efficiency over direct adaptation baselines on Burgers, Sod, and rotating detonation engine problems.
On-the-fly reduced order modeling of passive and reactive species via time-dependent manifolds,
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A dynamic subspace method parameterizes low-dimensional bases as geodesic paths on the Grassmannian to track evolving physics in nonlinear systems, achieving higher accuracy than static approximations at the same rank.
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History-aware adaptive reduced-order models via incremental singular value decomposition
An iSVD-based adaptive ROM framework updates reduced bases with occasional full-order snapshots, showing improved accuracy and efficiency over direct adaptation baselines on Burgers, Sod, and rotating detonation engine problems.
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A Dynamic Subspace Approach for Low-rank Approximation of Large-scale Nonlinear Systems
A dynamic subspace method parameterizes low-dimensional bases as geodesic paths on the Grassmannian to track evolving physics in nonlinear systems, achieving higher accuracy than static approximations at the same rank.