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arXiv 1408.2693math.NAcs.NA
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可靠且高效的后验误差估计方法用于适应性IGA边界元方法处理弱奇异积分方程

Reliable and efficient a posteriori error estimation for adaptive IGA boundary element methods for weakly-singular integral equations

Vienna University of Technology(维也纳工业大学)

Michael Feischl, Gregor Gantner, Dirk Praetorius

AI总结:

本文提出了一种可靠的后验误差估计方法,用于适应性IGA边界元方法处理弱奇异积分方程,通过分析残差型后验误差估计器,提供误差下界和上界,并展示了适应性算法的最优收敛性。

摘要:

我们考虑了用于处理二维第一类弱奇异积分方程的伽辽金边界元法(BEM)。我们分析了一些残差型后验误差估计器,该估计器为未知的伽辽金BEM误差提供了下界和上界。所要求的假设是弱的,允许对边界进行分段光滑参数化、局部网格细化以及相关的标准分段多项式以及NURBS。特别是,我们的分析为适应性BEM在等几何分析(IGABEM)框架下的首次贡献,我们提出了一个适应性算法,该算法引导局部网格细化和节点的多重性。数值实验验证了理论发现,并显示所提出的适应性策略导致最优收敛性。

英文摘要:

We consider the Galerkin boundary element method (BEM) for weakly-singular integral equations of the first-kind in 2D. We analyze some residual-type a posteriori error estimator which provides a lower as well as an upper bound for the unknown Galerkin BEM error. The required assumptions are weak and allow for piecewise smooth parametrizations of the boundary, local mesh-refinement, and related standard piecewise polynomials as well as NURBS. In particular, our analysis gives a first contribution to adaptive BEM in the frame of isogeometric analysis (IGABEM), for which we formulate an adaptive algorithm which steers the local mesh-refinement and the multiplicity of the knots. Numerical experiments underline the theoretical findings and show that the proposed adaptive strategy leads to optimal convergence.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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