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一种用于心脏电生理学的自适应可杂交间断伽辽金方法。

An adaptive hybridizable discontinuous Galerkin approach for cardiac electrophysiology.

作者信息

Hoermann Julia M, Bertoglio Cristóbal, Kronbichler Martin, Pfaller Martin R, Chabiniok Radomir, Wall Wolfgang A

机构信息

Institute for Computational Mechanics, Technical University Munich, Boltzmannstr 15, Garching b. München, 85748, Germany.

Center for Mathematical Modeling, Universidad de Chile, Beaucheff 851, Santiago 8370456, Chile.

出版信息

Int J Numer Method Biomed Eng. 2018 May;34(5):e2959. doi: 10.1002/cnm.2959. Epub 2018 Feb 12.

Abstract

Cardiac electrophysiology simulations are numerically challenging because of the propagation of a steep electrochemical wave front and thus require discretizations with small mesh sizes to obtain accurate results. In this work, we present an approach based on the hybridizable discontinuous Galerkin method (HDG), which allows an efficient implementation of high-order discretizations into a computational framework. In particular, using the advantage of the discontinuous function space, we present an efficient p-adaptive strategy for accurately tracking the wave front. The HDG allows to reduce the overall degrees of freedom in the final linear system to those only on the element interfaces. Additionally, we propose a rule for a suitable integration accuracy for the ionic current term depending on the polynomial order and the cell model to handle high-order polynomials. Our results show that for the same number of degrees of freedom, coarse high-order elements provide more accurate results than fine low-order elements. Introducing p-adaptivity further reduces computational costs while maintaining accuracy by restricting the use of high-order elements to resolve the wave front. For a patient-specific simulation of a cardiac cycle, p-adaptivity reduces the average number of degrees of freedom by 95% compared to the nonadaptive model. In addition to reducing computational costs, using coarse meshes with our p-adaptive high-order HDG method also simplifies practical aspects of mesh generation and postprocessing.

摘要

心脏电生理模拟在数值计算上具有挑战性,因为存在陡峭的电化学波前传播,因此需要使用小网格尺寸的离散化方法来获得准确结果。在这项工作中,我们提出了一种基于可杂交间断伽辽金方法(HDG)的方法,该方法允许在计算框架中高效地实现高阶离散化。特别是,利用间断函数空间的优势,我们提出了一种有效的p自适应策略来精确跟踪波前。HDG方法能够将最终线性系统中的总体自由度减少到仅在单元界面上的自由度。此外,我们根据多项式阶数和细胞模型提出了一种适用于离子电流项的积分精度规则,以处理高阶多项式。我们的结果表明,对于相同数量的自由度,粗粒度的高阶单元比细粒度的低阶单元提供更准确的结果。引入p自适应进一步降低了计算成本,同时通过限制使用高阶单元来解析波前来保持精度。对于特定患者的心动周期模拟,与非自适应模型相比,p自适应将平均自由度数量减少了95%。除了降低计算成本外,使用带有我们的p自适应高阶HDG方法的粗网格还简化了网格生成和后处理的实际操作。

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