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首页> 外文期刊>Journal of Nondestructive Evaluation >Adaptive Cross Approximation Algorithm for Accelerating BEM in Eddy Current Nondestructive Evaluation
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Adaptive Cross Approximation Algorithm for Accelerating BEM in Eddy Current Nondestructive Evaluation

机译:用于加速BEM在涡流非破坏性评估中的自适应交叉近似算法

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摘要

This paper presents the adaptive cross approximation (ACA) algorithm to accelerate boundary element method (BEM) for eddy current nondestructive evaluation (NDE) problem. The eddy current problem is formulated by boundary integral equation and discretized into matrix equations by BEM. Stratton-Chu formulation is selected and implemented for the conductive medium which does not has low frequency breakdown issue. The ACA algorithm has the advantage of purely algebraic and kernel independent. It starts with hierarchically partitioning the object to get diagonal blocks, near blocks and far blocks. The far-block interactions which are rank deficient can be compressed by ACA algorithm meanwhile the elements for diagonal-block interactions and near-block interactions are stored and computed by BEM. We apply modified ACA (MACA) for more memory saving while keeping almost same accuracy compared with original ACA. For numerical testing, several practical NDE examples such as coil above a half space conductor, tube in a fast reactor and Testing Electromagnetic Analysis Methods ( TEAM) workshop benchmark problem are presented to show the robust and efficiency of our method. With the aid of ACA, for electrically small problems, the complexity of both the memory requirement and CPU time for BEM are reduced to O(N log N).
机译:本文介绍了自适应跨近似(ACA)算法,以加速边界元法(BEM)进行涡流非破坏性评估(NDE)问题。涡流问题由边界积分方程制定并由BEM离散化为矩阵方程。选择并为导电介质选择并实现了不具有低频分解问题的导电介质。 ACA算法具有纯代数和内核的优势。它从分层划分对象来获取对角线块,靠近块和远的块。作为秩缺陷的远块交互可以通过ACA算法压缩,同时,对角块相互作用和近块交互的元素被BEM存储和计算。我们将改进的ACA(MACA)应用于更多内存保存,同时与原始ACA相比保持几乎相同的准确性。对于数值测试,提出了几种实用的NDE示例,例如线圈上方的线圈,在快速反应器中的管和测试电磁分析方法(团队)车间基准问题上,以显示我们方法的稳健和效率。借助ACA,对于电信小问题,BEM的内存要求和CPU时间的复杂性被降低到O(n log n)。

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