Khan M O, Valen-Sendstad K, Steinman D A
From the Biomedical Simulation Laboratory (M.O.K., K.V.-S., D.A.S.), Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada Center for Biomedical Computing (M.O.K., K.V.-S.), Simula Research Laboratory, Lysaker, Norway.
From the Biomedical Simulation Laboratory (M.O.K., K.V.-S., D.A.S.), Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada
AJNR Am J Neuroradiol. 2015 Jul;36(7):1310-6. doi: 10.3174/ajnr.A4263. Epub 2015 Mar 5.
Recent high-resolution computational fluid dynamics studies have uncovered the presence of laminar flow instabilities and possible transitional or turbulent flow in some intracranial aneurysms. The purpose of this study was to elucidate requirements for computational fluid dynamics to detect these complex flows, and, in particular, to discriminate the impact of solver numerics versus mesh and time-step resolution.
We focused on 3 MCA aneurysms, exemplifying highly unstable, mildly unstable, or stable flow phenotypes, respectively. For each, the number of mesh elements was varied by 320× and the number of time-steps by 25×. Computational fluid dynamics simulations were performed by using an optimized second-order, minimally dissipative solver, and a more typical first-order, stabilized solver.
With the optimized solver and settings, qualitative differences in flow and wall shear stress patterns were negligible for models down to ∼800,000 tetrahedra and ∼5000 time-steps per cardiac cycle and could be solved within clinically acceptable timeframes. At the same model resolutions, however, the stabilized solver had poorer accuracy and completely suppressed flow instabilities for the 2 unstable flow cases. These findings were verified by using the popular commercial computational fluid dynamics solver, Fluent.
Solver numerics must be considered at least as important as mesh and time-step resolution in determining the quality of aneurysm computational fluid dynamics simulations. Proper computational fluid dynamics verification studies, and not just superficial grid refinements, are therefore required to avoid overlooking potentially clinically and biologically relevant flow features.
近期的高分辨率计算流体动力学研究发现,在一些颅内动脉瘤中存在层流不稳定性以及可能的过渡流或湍流。本研究的目的是阐明计算流体动力学检测这些复杂流动的要求,特别是区分求解器数值与网格和时间步长分辨率的影响。
我们聚焦于3个大脑中动脉动脉瘤,分别代表高度不稳定、轻度不稳定或稳定的血流表型。对于每个动脉瘤,网格单元数量变化320倍,时间步数变化25倍。使用优化的二阶、最小耗散求解器以及更典型的一阶、稳定求解器进行计算流体动力学模拟。
使用优化的求解器和设置,对于每个心动周期约800,000个四面体和约5000个时间步长的模型,流动和壁面切应力模式的定性差异可忽略不计,并且可以在临床可接受的时间范围内求解。然而,在相同的模型分辨率下,稳定求解器的精度较差,并且完全抑制了2个不稳定流动病例中的流动不稳定性。使用流行的商业计算流体动力学求解器Fluent验证了这些发现。
在确定动脉瘤计算流体动力学模拟的质量时,求解器数值至少应被视为与网格和时间步长分辨率同样重要。因此,需要进行适当的计算流体动力学验证研究,而不仅仅是表面的网格细化,以避免忽略潜在的临床和生物学相关的流动特征。