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.
SIAM Journal on Applied Mathematics39(1), 67–82 (Aug 1980)
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Data-driven equation discovery applied to liquid film flows identifies identifiability issues from multi-collinearity in monomial bases and early-time transients with large residuals.
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Adjoint-based optimization with quantized local reduced-order models for spatiotemporally chaotic systems
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.