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Adaptive methodology for the meshless Galerkin boundary node method

机译:无网格Galerkin边界节点法的自适应方法

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The Galerkin boundary node method (GBNM) is a boundary-type meshless method that combines a variational form of boundary integral formulations for governing equations with the moving least-squares approximations for generation of the trial and test functions. In this paper, a posteriori error estimate and an effective adaptive h-refinement procedure are developed in conjunction with the GBNM. The error estimator is based on the difference between numerical solutions obtained using two successive nodal arrangements. The reliability and efficiency of this error estimator and the convergence of this adaptive meshless scheme are verified theoretically. Numerical examples are also given to show the efficiency of the adaptive methodology.
机译:Galerkin边界节点方法(GBNM)是一种边界类型的无网格方法,该方法将用于控制方程的边界积分公式的变体形式与用于生成试验和测试函数的移动最小二乘近似相结合。本文结合GBNM提出了后验误差估计和有效的自适应h细化程序。误差估计器基于使用两个连续的节点布置获得的数值解之间的差异。理论上验证了该误差估计器的可靠性和效率以及该自适应无网格方案的收敛性。数值例子也表明了自适应方法的效率。

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