积分方程几何建模与离散化的新趋势

Jie Li, D. Dault, B. Shanker
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引用次数: 1

摘要

在本章中,作者沿着这些思路提出了一些想法,重点介绍了两种不同的数值方法,即GMM和IGA,这两种方法都依赖于几何的细分表示。两种方法都采用不同的方法来求解积分方程。GMM是一种高度灵活的方案,允许为每个补丁使用不同的基函数,因此,它是高度可定制的。该方法的关键是局部表面参数化和斑块重叠区域不同局部参数化之间的过渡图。细分提供了克服这一瓶颈的有效方法。通过实例证明了其有效性和相关挑战。实际上,可以将细分GMM与[14]中开发的方法配对,以有效地评估积分,以解决电力大且几何复杂的问题。
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New trends in geometric modeling and discretization for integral equations
In this chapter, the author have presented ideas along these lines, focusing on two different numerical approaches, i.e., GMM and IGA, both of which rely on subdivision representation of geometries. Both methods take different approaches to solving integral equations. GMM is a highly flexible scheme that permits the use of different basis functions for each patch and, as a result, is highly customizable. The crux to this approach is local surface parameterization and transition maps between different local parameterizations in regions where patches overlap. Subdivision offers an effective approach to overcome this bottleneck. Its efficacy and related challenges have been demonstrated through examples. Indeed, it is possible to pair subdivision GMM with methods developed in [14] to efficiently evaluate integrals to solve problems that are electrically large and geometrically complex.
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Back Matter New trends in geometric modeling and discretization for integral equations New trends in algebraic preconditioning New trends in uncertainty quantification for large-scale electromagnetic analysis: from tensor product cubature rules to spectral quantic tensor-train approximation New trends in frequency-domain volume integral equations
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