Solving fluid flow domain identification problems with adjoint lattice Boltzmann methods
Solving fluid flow domain identification problems with adjoint lattice Boltzmann methods
复制标题
DOI：
10.1016/j.camwa.2018.07.010
复制
发表时间：
2020-01
期刊：
影响因子：
--
通讯作者：
Fabian Klemens;Benjamin Förster;M. Dorn;G. Thäter;M. Krause
中科院分区：
文献类型：
--
作者：
Fabian Klemens;Benjamin Förster;M. Dorn;G. Thäter;M. Krause
本文介绍了Krause等人提出的求解不可压缩流体区域识别问题的伴随格子Boltzmann方法。（2016），并进行了改进和验证。该问题被制定为一个分布式控制问题，它最小化之间的距离给定的，例如从像MRI的测量，和一个模拟的流场。因此，模拟的流场是一个参数化的多孔介质BGK-Boltzmann问题的解决方案，其中的参数表示分布在域中的孔隙度。建议的参数化包括链接的变量代表一个晶格相关的孔隙度与控制变量。因此，应注意，给定的控制参数集产生独立于底层网格分辨率的结果。它能够解决具有不同分辨率的优化问题，而无需调整初始控制变量集。
In this article, the adjoint lattice Boltzmann method (ALBM) for solving fluid domain identification problems for incompressible fluids, proposed by Krause et al. (2016), is improved and validated. The problem is formulated as a distributed control problem which minimises the distance between a given, e.g. from measurements like MRI, and a simulated flow field. Thereby, the simulated flow field is the solution of a parametrised porous media BGK–Boltzmann problem, where the parameters represent porosity distributed in the domain. The proposed parametrisation consists of linking the variables representing a lattice-dependent porosity with the control variables. Hereby, it is paid attention that a given control parameter set yields results which are independent of the underlying grid resolution. It enables solving an optimisation problem with different resolutions without adapting the initial set of control variables.