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Nonlinear model reduction for transport-dominated problems
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DOI：10.1017/S0962492926100294.png)
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Abstract
En 中文
This article surveys nonlinear model reduction methods that remain effective in regimes where linear reduced-space approximations are intrinsically inefficient; such as transport-dominated problems with wave-like phenomena and moving coherent structures; which are commonly associated with the Kolmogorov barrier. The article organizes nonlinear model reduction techniques around three key elements – nonlinear parametrizations; reduced dynamics and online solvers – and categorizes existing approaches into transformation-based methods; online adaptive techniques; and formulations that combine generic nonlinear parametrizations with instantaneous residual minimization.
Keywords:
65M99
41A46
65F55
68T07
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IF:
11.3
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89
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3.4K
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