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.
Cambridge University Press, 1 edn
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2026 2verdicts
UNVERDICTED 2representative citing papers
Quantized local reduced-order models paired with adjoint optimization reconstruct full trajectories in the chaotic Kuramoto-Sivashinsky equation up to 0.25 Lyapunov times with 3.5x speedup over full-order models.
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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.