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A reduced finite difference scheme based on singular value decomposition and proper orthogonal decomposition for Burgers equation

机译:基于Burgers方程奇异值分解和适当正交分解的有限差分格式

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摘要

In this article, a reduced optimizing finite difference scheme (FDS) based on singular value decomposition (SVD) and proper orthogonal decomposition (POD) for Burgers equation is presented. Also the error estimates between the usual finite difference solution and the POD solution of reduced optimizing FDS are analyzed. It is shown by considering the results obtained for numerical simulations of cavity flows that the error between the POD solution of reduced optimizing FDS and the solution of the usual FDS is consistent with theoretical results. Moreover, it is also shown that the reduced optimizing FDS is feasible and efficient.
机译:本文提出了一种基于奇异值分解(SVD)和固有正交分解(POD)的Burgers方程的简化优化有限差分方案(FDS)。还分析了通常的有限差分解决方案与简化优化FDS的POD解决方案之间的误差估计。通过对腔体流动数值模拟的结果表明,简化的优化FDS的POD解与常规FDS的解之间的误差与理论结果相符。而且,还表明减少的优化FDS是可行和有效的。

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