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Numerical model reduction with error control in computational homogenization of transient heat flow

机译:瞬态热流计算均匀化中带有误差控制的数值模型简化

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Numerical Model Reduction (NMR) is exploited for solving the finite element problem on a Representative Volume Element (RVE) that arises from the computational homogenization of a model problem of transient heat flow. Since the problem is linear, an orthogonal basis is obtained via the classical method of spectral decomposition. A symmetrized version of the space-time variational format is adopted for estimating the error from the model reduction in (i) energy norm and in (ii) given Quantities of Interest. This technique, which was recently developed in the context of the (non-selfadjoint) stationary diffusion-convection problem, is novel in the present context of NMR. By considering the discrete, unreduced, model as exact, we are able to obtain guaranteed bounds on the error while using only the reduced basis and with minor computational effort. The performance of the error estimates is demonstrated via numerical results, where the subscale is modeled in both one and three spatial dimensions. (C) 2017 The Authors. Published by Elsevier B.V.
机译:数值模型还原(NMR)用于解决代表体积元素(RVE)上的有限元问题,该问题是由瞬态热流模型问题的计算均质化引起的。由于问题是线性的,因此可以通过经典的光谱分解方法获得正交基础。采用时空变分格式的对称形式来估计模型降级所带来的误差,该模型降低了(i)能量范数和(ii)给定的关注数量。在(非自伴)平稳扩散-对流问题的背景下最近开发的这项技术在NMR的背景下是新颖的。通过将离散的,未简化的模型视为精确模型,我们能够获得误差的有保证的界限,而仅使用简化的基础并且只需很少的计算工作即可。误差估计的性能通过数值结果证明,其中在一个和三个空间维度上对子量表进行建模。 (C)2017作者。由Elsevier B.V.发布

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