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Using domain decomposition techniques for the calculation of low-frequency electric current densities in high-resolution 3D human anatomy models

机译:使用域分解技术计算高分辨率3D人体解剖模型中的低频电流密度

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Purpose - Improved numerical calculation techniques for low-frequency current density distributions within high-resolution anatomy models caused by ambient electric or magnetic fields or direct contact to potential drops using the finite integration technique (FIT). Design/methodology/approach - The methodology of calculating low-frequency electromagnetic fields within high-resolution anatomy models using the FIT is extended by a local grid refinement scheme using a non-matching-grid formulation domain. Furthermore, distributed computing techniques are presented. Several numerical examples are analyzed using these techniques. Findings - Numerical simulations of low-frequency current density distributions may now be performed with a higher accuracy due to an increased local grid resolution in the areas of interest in the human body voxel models when using the presented techniques. Originality/value - The local subgridding approach is introduced to reduce the number of unknowns in the very large-scale linear algebraic systems of equations that have to be solved and thus to reduce the required computational time and memoryresources. The use of distributed computation techniques such as, e.g. the use of a parallel solver package as PETSc follows the same goals.
机译:用途-改进的数值计算技术,用于使用有限积分技术(FIT)由环境电场或磁场或直接接触电位降引起的高分辨率解剖模型中的低频电流密度分布。设计/方法/方法-使用FIT在高分辨率解剖模型中计算低频电磁场的方法通过使用非匹配网格公式化域的局部网格细化方案得到扩展。此外,提出了分布式计算技术。使用这些技术分析了几个数值示例。发现-由于使用人体模型技术时,由于人体体素模型感兴趣区域中局部网格分辨率的提高,低频电流密度分布的数值模拟现在可以以更高的精度执行。独创性/值-引入局部细分方法以减少必须解决的超大规模线性代数方程组中未知数的数量,从而减少所需的计算时间和内存资源。分布式计算技术的使用,例如使用并行求解器程序包(如PETSc)也遵循相同的目标。

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