针对复杂动脉模型流动的 GPU 优化多区块多网格沉浸边界法

IF 2.5 3区 工程技术 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Debajyoti Kumar , Siddharth D. Sharma , Somnath Roy
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引用次数: 0

摘要

沉浸边界法(IBM)被广泛用于使用结构化网格模拟复杂几何形状中的流动。然而,在模拟通过弯曲管道的内部流动时,这种方法存在缺点。流体域外网格的存在会导致内存浪费和计算开销。在此,我们提出了一种多网格块-多网格框架,利用靠近管体的多个网格块来捕捉复杂的几何形状,从而减少多余的网格。这样做的另一个好处是在不同的网格块中使用不同的非均匀网格间距。网格的减少使单个 GPU 可以处理更大的工作量。在 GPU 上使用 OpenACC 对求解器进行了加速,并与 CPU 的顺序模拟进行了比较。所获得的速度提升可与大型多核系统相媲美。该框架针对具有轴对称狭窄的直动脉和具有轴对称窦道的双叶机械心脏瓣膜进行了广泛验证。然后,该框架模拟了复杂的动脉流动,如狭窄的主动脉、患者特异性分支主动脉、带有瓦尔萨尔瓦窦和主动脉的双叶机械心脏瓣膜,最后是患者特异性髂主动脉瘤。该框架大大降低了复杂动脉模型对 GPU 内存的需求,使我们能够在单个 GPU 中对狭窄主动脉和机械心脏瓣膜进行直接数值模拟(DNS)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

GPU optimized multi-block-multi-mesh immersed boundary method for flows in complex arterial models

GPU optimized multi-block-multi-mesh immersed boundary method for flows in complex arterial models

Immersed boundary method (IBM) is widely used for simulating flow in complex geometries using structured grids. However, this entails a disadvantage when simulating internal flows through curved and bent tubes. The presence of grids outside the fluid domain leads to the wastage of memory and computational overheads. Here, we propose a multi-block-multi-mesh framework to capture the complex geometry using multiple grid blocks fitted close to the body, reducing excess grids. This also has the advantage of using different and non-uniform grid spacing in different blocks. The reduction of the grid enables encompassing bigger caseloads on a single GPU. The solver is accelerated on GPU using OpenACC, compared to sequential CPU simulations, and speedup is presented. The speedup obtained is comparable to that of large multicore systems. The framework is extensively validated for straight artery with axisymmetric stenosis and bileaflet mechanical heart valve with axisymmetric sinus. This framework then models complex arterial flows like stenosed aorta, patient-specific branched aorta, bileaflet mechanical heart valve with Valsalva sinus and aorta, and lastly, patient-specific iliac aortic aneurysm. This framework achieves a significant reduction in GPU memory requirement for complex arterial models, enabling us to perform direct numerical simulation (DNS) of the stenosed aorta and mechanical heart valve cases in a single GPU.

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来源期刊
Computers & Fluids
Computers & Fluids 物理-计算机:跨学科应用
CiteScore
5.30
自引率
7.10%
发文量
242
审稿时长
10.8 months
期刊介绍: Computers & Fluids is multidisciplinary. The term ''fluid'' is interpreted in the broadest sense. Hydro- and aerodynamics, high-speed and physical gas dynamics, turbulence and flow stability, multiphase flow, rheology, tribology and fluid-structure interaction are all of interest, provided that computer technique plays a significant role in the associated studies or design methodology.
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