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Numerical simulations of 1D inverse heat conduction problems using overdetermined RBF-MLPG method

机译:超额确定的RBF-MLPG方法对一维逆热传导问题的数值模拟

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This paper proposes a numerical method to deal with the one-dimensional inverse heat conduction problem (IHCP). The initial temperature, a condition on an accessible part of the boundary and an additional temperature measurements in time at an arbitrary location in the domain are known, and it is required to determine the temperature and the heat flux on the remaining part of the boundary. Due to the missing boundary condition, the solution of this problem does not depend continuously on the data and therefore its numerical solution requires special care especially when noise is present in the measured data. In the proposed method, the time variable is eliminated by using finite differences approximation. The method uses a weak formulation of the problem to enjoy the stability condition. To avoid the numerical integration on the whole domain, the weak form equations are constructed on local subdomains. The approximate solution is assumed to be a linear combination of Multi Quadric (MQ) radial basis function (RBF) constructed on nodal points in the domain and on the boundary. Since the problem is known to be ill-posed, Thikhonov regularization strategy is employed to solve effectively the discrete ill-posed resultant linear system.
机译:本文提出了一种数值方法来解决一维逆导热问题(IHCP)。已知初始温度,边界可访问部分的条件以及在域中任意位置及时进行的其他温度测量,并且需要确定边界其余部分的温度和热通量。由于缺少边界条件,此问题的解决方案并不连续依赖于数据,因此,其数值解决方案需要特别注意,尤其是当测量数据中存在噪声时。在所提出的方法中,通过使用有限差分近似消除了时间变量。该方法使用问题的弱公式来表示稳定性条件。为了避免在整个域上进行数值积分,在局部子域上构造了弱形式方程。假定近似解是构造在域内和边界上的节点上的多重二次曲面(MQ)径向基函数(RBF)的线性组合。由于已知问题是不适定的,因此采用Thikhonov正则化策略来有效解决离散的不适定结果线性系统。

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