arXivDaily arXiv每日学术速递 周一至周五更新
北美退伍军人节(Veterans Day),12 日无更新
arXiv 1504.06164math.NAcs.NA
收藏

自适应二维IGA边界元方法

Adaptive 2D IGA boundary element methods

Michael Feischl, Gregor Gantner, Alexander Haberl, Dirk Praetorius

AI总结:

本文提出自适应二维IGA边界元方法,基于后验误差估计器分析,结合局部网格细化和NURBS,验证了该方法在能量误差上的可靠性及优于传统边界元方法的性能。

摘要:

我们推导并讨论了用于弱奇异积分方程的一阶边界元方法的后验误差估计器,包括Galerkin和collocation IGA方法。本文重点分析了collocation和加权残差误差估计器,提供了能量误差的可靠上界。我们的分析允许边界参数化为分段光滑,局部网格细化以及相关的分段多项式和NURBS。我们提出了一种自适应算法,指导局部网格细化和结点多重性。数值实验表明,所提出的自适应策略实现了最优收敛性,相关IGA边界元方法优于使用分段多项式的传统边界元方法。

英文摘要:

We derive and discuss a posteriori error estimators for Galerkin and collocation IGA boundary element methods for weakly-singular integral equations of the first-kind in 2D. While recent own work considered the Faermann residual error estimator for Galerkin IGA boundary element methods, the present work focuses more on collocation and weighted- residual error estimators, which provide reliable upper bounds for the energy error. Our analysis allows piecewise smooth parametrizations of the boundary, local mesh-refinement, and related standard piecewise polynomials as well as NURBS. We formulate an adaptive algorithm which steers the local mesh-refinement and the multiplicity of the knots. Numerical experiments show that the proposed adaptive strategy leads to optimal convergence, and related IGA boundary element methods are superior to standard boundary element methods with piecewise polynomials.

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。

↑