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首页> 外文期刊>SIAM Journal on Scientific Computing >Identification of transport coefficient models in convection-diffusion equations
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Identification of transport coefficient models in convection-diffusion equations

机译:对流扩散方程中输运系数模型的辨识

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摘要

A rigorous method is presented for the systematic identification of the structure and the parameters of transport coefficient models in three-dimensional, transient convection-diffusion systems using high-resolution measurement data. The transport is represented by a convection term with known convective velocity and a diffusion term with an unknown, generally state-dependent, transport coefficient. The identification of a transport coefficient model constitutes an ill-posed, highly nonlinear inverse problem. In our previous work [Karalashvili et al., SIAM J. Sci. Comput., 30 (2008), pp. 3249-3269], we presented a novel incremental identification method, which decomposes this inverse problem into easier-to-handle inverse subproblems. This way, the incremental identification method not only allows for the identification of the structure and the parameters of the model, but also supports the rigorous decision making on the best-suited transport model structure. Due to the decomposition approach, the identified transport model structure and parameters are subject to errors. To cope with the error propagation inherent in the incremental method, the present work suggests a model correction procedure as a supplement to the incremental identification method of our previous work, which results in a transport model of higher precision. The correction refers to both the model structure and parameters. No a priori knowledge on the unknown transport model structure is necessary. The identification approach is numerically illustrated for a three-dimensional, transient convection-diffusion equation which has its origin in the modeling and simulation of energy transport in a laminar wavy film flow.
机译:提出了一种使用高分辨率测量数据对三维瞬态对流扩散系统中输运系数模型的结构和参数进行系统识别的严格方法。传输由具有对流速度的对流项和具有未知的,通常取决于状态的传输系数的扩散项表示。传输系数模型的识别构成了一个不适定的,高度非线性的逆问题。在我们以前的工作中[Karalashvili等,SIAM J. Sci。 Comput。,30(2008),pp。3249-3269],我们提出了一种新颖的增量识别方法,该方法将反问题分解为易于处理的反子问题。这样,增量识别方法不仅可以识别模型的结构和参数,而且还可以对最适合的运输模型结构进行严格的决策。由于采用了分解方法,因此识别出的运输模型结构和参数容易出错。为了应对增量方法中固有的错误传播,本工作提出了一种模型校正程序,作为对我们先前工作的增量识别方法的补充,从而得到了一种精度更高的传输模型。校正涉及模型结构和参数。不需要有关未知运输模型结构的先验知识。对三维瞬态对流扩散方程的数值识别方法进行了数值说明,其起源于层状波浪膜流中能量传输的建模和仿真。

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