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Comparison between the modal identification method and the POD-Galerkin method for model reduction in nonlinear diffusive systems

机译:非线性扩散系统模型辨识的模态辨识方法与POD-Galerkin方法比较

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This paper presents a comparison between the modal identification method (MIM) and the proper orthogonal decomposition-Galerkin (POD-G) method for model reduction. An example of application on a nonlinear diffusive system is used to illustrate the study. The study shows that in both methods, the state formulation of the nonlinear diffusive equation may be similar. However, the ideas behind both methods are completely different. The considered example shows that, for both methods, reducing the order up to 99.5% gives enough accuracy to simulate the dynamic of the original system. It is also seen in this example that the reduced model given through the MIM are slightly faster and more accurate than the ones given through the POD-G method. Copyright (c) 2006 John Wiley & Sons, Ltd.
机译:本文比较了模态识别方法(MIM)和适当的正交分解-Galerkin方法(POD-G)。以在非线性扩散系统上的应用为例说明了这项研究。研究表明,在两种方法中,非线性扩散方程的状态公式可能相似。但是,这两种方法背后的思想是完全不同的。所考虑的示例表明,对于这两种方法,将阶数降低到99.5%都可提供足够的精度来模拟原始系统的动态。在此示例中还可以看到,通过MIM给出的精简模型比通过POD-G方法给出的精简模型更快,更准确。版权所有(c)2006 John Wiley&Sons,Ltd.

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