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Reproducing kernel formulation of B-spline and NURBS basis functions: A meshfree local refinement strategy for isogeometric analysis

机译:再现B样条和NURBS基本函数的内核公式:等几何分析的无网格局部细化策略

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A reproducing kernel meshfree formulation is presented for the B-spline and non-uniform rational B-spline (NURBS) basis functions used in isogeometric analysis. It is shown that after properly introducing meshfree nodes, support size and consistency conditions, the reproducing kernel meshfree shape functions are capable of exactly representing the isogeometric B-spline and NURBS basis functions. Consequently, the proposed formulation successfully establishes a correspondence or close link between the meshfree methods and the isogeometric analysis. More importantly, the proposed reproducing kernel meshfree representation of isogeometric basis functions provides a reliable meshfree strategy to the local model refinement in isogeometric analysis. This strategy inherits the strength of meshfree methods and gives considerable easiness for the local refinement, i.e., the shape functions in the refined regions can be naturally constructed in a straightforward meshfree manner. Meanwhile, the consistency and independence of the shape functions required by the subsequent computational analysis are ensured by the consistency conditions of reproducing kernel meshfree formulation. A detailed illustration of the proposed approach for isogeometric local model refinement is presented. The effectiveness of the proposed meshfree local refinement strategy for isogeometric analysis is demonstrated through numerical examples. (C) 2017 Elsevier B.V. All rights reserved.
机译:针对等几何分析中使用的B样条和非均匀有理B样条(NURBS)基函数,提出了一种无核的再生公式。结果表明,在正确引入无网格节点,支持大小和一致性条件之后,可再生内核无网格形状函数能够准确表示等几何B样条和NURBS基函数。因此,所提出的公式成功地建立了无网格方法与等几何分析之间的对应关系或紧密联系。更重要的是,所提出的重现等几何基函数的内核无网格表示为等几何分析中的局部模型细化提供了可靠的无网格策略。该策略继承了无网格方法的优势,并为局部细化提供了极大的方便性,即,可以以一种简单的无网格方式自然地构造出细化区域中的形状函数。同时,通过再现无核无核配方的一致性条件,保证了后续计算分析所需的形状函数的一致性和独立性。提出了用于等几何局部模型细化的建议方法的详细说明。通过数值示例证明了提出的无网格局部细化策略用于等几何分析的有效性。 (C)2017 Elsevier B.V.保留所有权利。

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