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SIMPLEX STOCHASTIC COLLOCATION FOR PIECEWISE SMOOTH FUNCTIONS WITH KINKS

机译:单纯表随机搭配,用于扭结的分段平滑功能

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Most approximation methods in high dimensions exploit smoothness of the function being approximated. These methods provide poor convergence results for nonsmooth functions with kinks. For example, such kinks can arise in the uncertainty quantification of quantities of interest for gas networks. This is due to the regulation of the gas flow, pressure, or temperature. But, one can exploit that, for each sample in the parameter space it is known if a regulator was active or not, which can be obtained from the result of the corresponding numerical solution. This information can be exploited in a stochastic collocation method. We approximate the function separately on each smooth region by polynomial interpolation and obtain an approximation to the kink. Note that we do not need information about the exact location of kinks, but only an indicator assigning each sample point to its smooth region. We obtain a global order of convergence of (p + 1)/d, where p is the degree of the employed polynomials and d the dimension of the parameter space.
机译:高尺寸的大多数近似方法利用近似函数的平滑度。这些方法为具有扭结的非机动功能提供了较差的收敛结果。例如,这种扭结可以以气体网络的利益量的不确定性量化出现。这是由于气体流动,压力或温度的调节。但是,一个人可以利用,对于参数空间中的每个样本,如果稳压器是有效的,则可以从相应的数字解决方案的结果获得。该信息可以以随机搭配方法利用。我们通过多项式插值在每个平滑区域上单独地近似功能,并获得扭结的近似。请注意,我们不需要有关Kinks的确切位置的信息,而是仅指示每个采样点到其平滑区域的指示。我们获得(P + 1)/ D的全局收敛顺序,其中P是所用多项式的程度和参数空间的维度。

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