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Tensor-product adaptive grids based on coordinate transformations

机译:基于坐标变换的张量积自适应网格

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摘要

In this paper we discuss a two-dimensional adaptive grid method that is based on a tensor-product approach. Adaptive grids are a commonly used tool for increasing the accuracy and reducing computational costs when solving both partial differential equations (PDEs) and ordinary differential equations. A traditional and widely used form of adaptivity is the concept of equidistribution, which is well-defined and well-understood in one space dimension. The extension of the equidistribution principle to two or three space dimensions, however, is far from trivial and has been the subject of investigation of many researchers during the last decade. Besides the nonsingularity of the transformation that defines the nonuniform adaptive grid, the smoothness of the grid (or transformation) plays an important role as well. We will analyse these properties and illustrate their importance with numerical experiments for a set of time-dependent PDE models with steep moving pulses, fronts, and boundary layers.
机译:在本文中,我们讨论了基于张量积方法的二维自适应网格方法。自适应网格是求解偏微分方程(PDE)和常微分方程时提高精度和降低计算成本的常用工具。均衡的概念是一种广泛使用的传统形式的适应性概念,它在一个空间维度上定义明确且易于理解。但是,将公平分配原则扩展到两个或三个空间维度并不是一件容易的事,并且在过去十年中一直是许多研究人员研究的主题。除了定义非均匀自适应网格的变换的非奇异性之外,网格(或变换)的平滑度也起着重要的作用。我们将对这些特性进行分析,并通过数值实验说明一组具有时间变化的脉冲,前沿和边界层的时间相关的PDE模型的重要性。

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