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定制边缘单元有限元求解器及其在真实200万个单元人类脑模型涡流模拟中的应用。

Custom edge-element FEM solver and its application to eddy-current simulation of realistic 2M-element human brain phantom.

作者信息

Yin Wuliang, Lu Mingyang, Tang Jiawei, Zhao Qian, Zhang Zhijie, Li Kai, Han Yan, Peyton Anthony

机构信息

School of Instrument and Electronics, North University of China, Taiyuan, Shanxi, China.

School of Electrical and Electronic Engineering, University of Manchester, Manchester, United Kingdom.

出版信息

Bioelectromagnetics. 2018 Dec;39(8):604-616. doi: 10.1002/bem.22148. Epub 2018 Oct 5.

Abstract

Extensive research papers of three-dimensional computational techniques are widely used for the investigation of human brain pathophysiology. Eddy current analyzing could provide an indication of conductivity change within a biological body. A significant obstacle to current trend analyses is the development of a numerically stable and efficiency-finite element scheme that performs well at low frequency and does not require a large number of degrees of freedom. Here, a custom finite element method (FEM) solver based on edge elements is proposed using the weakly coupled theory, which separates the solution into two steps. First, the background field (the magnetic vector potential on each edge) is calculated and stored. Then, the electric scalar potential on each node is obtained by FEM based on Galerkin formulations. Consequently, the electric field and eddy current distribution in the object can be obtained. This solver is more efficient than typical commercial solvers since it reduces the vector eddy current equation to a scalar one, and reduces the meshing domain to just the eddy current region. It can therefore tackle complex eddy current calculations for models with much larger numbers of elements, such as those encountered in eddy current computation in biological tissues. An example is presented with a realistic human brain mesh of 2 million elements. In addition, with this solver, the equivalent magnetic field induced from the excitation coil is applied, and therefore there is no need to mesh the excitation coil. In combination, these significantly increase the efficiency of the solver. Bioelectromagnetics. 39:604-616, 2018. © 2018 Wiley Periodicals, Inc.

摘要

大量关于三维计算技术的研究论文被广泛用于人类大脑病理生理学的研究。涡流分析可以提供生物体内电导率变化的指示。当前趋势分析的一个重大障碍是开发一种数值稳定且高效的有限元方案,该方案在低频下表现良好且不需要大量自由度。在此,基于弱耦合理论提出了一种使用边元的定制有限元方法(FEM)求解器,该方法将求解过程分为两步。首先,计算并存储背景场(每条边上的磁矢量势)。然后,基于伽辽金公式通过有限元方法获得每个节点上的电标势。因此,可以得到物体中的电场和涡流分布。该求解器比典型的商业求解器更高效,因为它将矢量涡流方程简化为标量方程,并将网格划分域仅缩小到涡流区域。因此,它可以处理具有大量元素的模型的复杂涡流计算,例如生物组织中涡流计算中遇到的模型。给出了一个具有两百万个元素的真实人脑网格的示例。此外,使用该求解器时,施加了由激励线圈感应的等效磁场,因此无需对激励线圈进行网格划分。综合起来,这些显著提高了求解器的效率。《生物电磁学》。39:604 - 616,2018年。© 2018威利期刊公司。

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