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Meshless Local Petrov-Galerkin Mixed Collocation Method for Solving Cauchy Inverse Problems of Steady-State Heat Transfer

机译:解决稳态传热柯西逆问题的无网格局部Petrov-Galerkin混合配置方法

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In this article, the Meshless Local Petrov-Galerkin (MLPG) Mixed Collocation Method is developed to solve the Cauchy inverse problems of Steady-State Heat Transfer In the MLPG mixed collocation method, the mixed scheme is applied to independently interpolate temperature as well as heat flux using the same meshless basis functions The balance and compatibility equations are satisfied at each node in a strong sense using the collocation method. The boundary conditions are also enforced using the collocation method, allowing temperature and heat flux to be over-specified at the same portion of the boundary. For the inverse problems where noise is present in the measurement, Tikhonov regularization method is used, to mitigate the inherent ill-posed nature of inverse problem, with its regularization parameter determined by the L-Curve method. Several numerical examples are given, wherein both temperature as well as heat flux are prescribed at part of the boundary, and the data at the other part of the boundary and in the domain have to be solved for. Through these numerical examples, we investigate the accuracy, convergence, and stability of the proposed MLPG mixed collocation method for solving inverse problems of Heat Transfer.
机译:本文开发了无网格局部Petrov-Galerkin(MLPG)混合搭配方法来解决稳态传热的柯西逆问题。在MLPG混合搭配方法中,将混合方案应用于温度和热量的独立插值使用相同的无网格基函数的通量使用搭配方法,在每个节点上都可以很好地满足平衡和相容性方程。边界条件也可以使用搭配方法强制执行,从而可以在边界的同一部分过分指定温度和热通量。对于测量中存在噪声的反问题,使用Tikhonov正则化方法来缓解反问题的固有不适定性,其正则化参数由L曲线方法确定。给出了几个数值示例,其中在边界的一部分处规定了温度以及热通量,并且必须求解边界的另一部分和域中的数据。通过这些数值示例,我们研究了用于解决传热逆问题的MLPG混合配置方法的准确性,收敛性和稳定性。

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