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Least squares shadowing sensitivity analysis of a modified Kuramoto–Sivashinsky equation

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  • Blonigan, Patrick J.
  • Wang, Qiqi

Abstract

Computational methods for sensitivity analysis are invaluable tools for scientists and engineers investigating a wide range of physical phenomena. However, many of these methods fail when applied to chaotic systems, such as the Kuramoto–Sivashinsky (K–S) equation, which models a number of different chaotic systems found in nature. The following paper discusses the application of a new sensitivity analysis method developed by the authors to a modified K–S equation. We find that least squares shadowing sensitivity analysis computes accurate gradients for solutions corresponding to a wide range of system parameters.

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  • Blonigan, Patrick J. & Wang, Qiqi, 2014. "Least squares shadowing sensitivity analysis of a modified Kuramoto–Sivashinsky equation," Chaos, Solitons & Fractals, Elsevier, vol. 64(C), pages 16-25.
    • Handle: RePEc:eee:chsofr:v:64:y:2014:i:c:p:16-25
    DOI: 10.1016/j.chaos.2014.03.005
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    Cited by:

    1. Craske, John, 2019. "Adjoint sensitivity analysis of chaotic systems using cumulant truncation," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 243-254.

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