CFD-MRI : A coupled measurement and simulation approach for accurate fluid flow characterisation and domain identification
CFD-MRI : A coupled measurement and simulation approach for accurate fluid flow characterisation and domain identification
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DOI：
10.1016/j.compfluid.2018.02.022
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发表时间：
2018-04
影响因子：
2.8
通讯作者：
Fabian Klemens;S. Schuhmann;G. Guthausen;G. Thäter;M. Krause
中科院分区：
文献类型：
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作者：
Fabian Klemens;S. Schuhmann;G. Guthausen;G. Thäter;M. Krause
本文介绍了磁共振成像(MRI)测量和计算流体动力学(CFD)的耦合，以准确地描述流体流动和识别流动区域。目前，MRI测量是在时间和空间上平均的，假设速度和压力空间具有一定的平稳性。然而，流体问题的可能解决方案必须满足Navier-Stokes方程，该方程设置的条件比通常的曲线拟合中的光滑性假设更具限制性。新的CFD-MRI方法利用这种洞察力来减少统计噪声，并识别潜在领域的更精细的结构。该问题被描述为一个分布式控制问题，其目的是最小化测量和模拟的流场之间的距离。因此，模拟的流场是参数化孔介质BGK-Boltzmann方程的解，该方程在水动力极限下逼近齐次化的Navier-Stokes方程。这些参数表示在区域中分布的孔隙度，该区域产生与测量数据最匹配的区域和流体流动。这使得他们能够从具有一个速度分量的有限的2D空间分辨MRI数据中定位障碍物和流场。利用开放源码软件OpenLB1，用伴随格子Boltzmann方法(ALBM)求解了该问题。
This article presents the coupling of magnetic resonance imaging (MRI) measurements and computational fluid dynamics (CFD) for accurate characterisation of fluid flow and identification of flow domains. Currently, MRI measurements are averaged over time and space, assuming a certain smoothness of the velocity and pressure space. However, a possible solution of a fluid problem must fulfil the Navier–Stokes equations, which sets up a condition that is much more restrictive than the usual smoothness assumptions in e.g. curve fitting. The novel CFD-MRI method uses this insight to reduce the statistical noise and to identify finer structures of the underlying domain. The problem is formulated as a distributed control problem which minimises the distance between measured and simulated flow field. Thereby, the simulated flow field is the solution of a parametrised porous media BGK-Boltzmann equation which approaches a homogenised Navier–Stokes equation in the hydrodynamic limit. The parameters represent the porosity distributed in the domain which yields a domain and a fluid flow that fits best to the measured data. This enables the method they locate an obstacle and the flow field from limited 2Dspatially resolved MRI data with one velocity component. The problem is solved with an adjoint lattice Boltzmann method (ALBM) using the open source software OpenLB1.