首页> 外文期刊>Journal of Fluids Engineering: Transactions of the ASME >Inverse Computational Fluid Dynamics: Influence of Discretization and Model Errors on Flows in Water Network Including Junctions
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Inverse Computational Fluid Dynamics: Influence of Discretization and Model Errors on Flows in Water Network Including Junctions

机译:逆计算流体动力学:离散化和模型误差对包括结点在内的水网络流量的影响

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摘要

We address the reconstruction of relevant two-dimensional (2D) flows in drinking water networks, especially in key elements such as pipe junctions, in view of representative water quality simulations. From the optimal control theory, a specific inverse technique using few sensors and computational fluid dynamics (CFD) models has been developed. First, we determine the boundary velocities, i.e., the control parameters, by minimizing a data misfit functional. Then, knowing the boundary velocities, a direct solve of the flow model is performed to get the space-time cartography of the water flow. To reduce the number of control parameters to be determined and thus restrict the number of sensors, the spatial shape of the boundary velocities is considered as an a priori information given by the water pipes engineering literature. Thus, only the time evolution of the boundary velocities has to be determined. The whole numerical procedure proposed in this paper easily fits in a general purpose finite element software, featuring user's friendliness for a wide engineering audience. Two ways are investigated to reduce the computation time associated to the flow reconstruction. The adjoint framework is used in the minimization process. The reconstruction of the flow using coarse discretizations and simple flow models, instead of 2D Navier-Stokes equations, is studied. The influence of the flow modeling and of the dicretization on the quality of the reconstructed velocity is studied on two examples: a water pipe junction and a 200m subsection from a French water network. In the water pipe junction, we show that at a Reynolds number of 200 a hybrid approach combining an unsteady Stokes reconstruction and a single direct Navier-Stokes simulation outperforms the algorithms based on a single model. In the network subsection, we obtain an L-2 error less than 1% between the reference velocity based on Navier-Stokes equations (Reynolds number of 200) and the velocity reconstructed from Stokes equation. In this case, the reconstruction lasts less than 1 min. Stokes based reconstruction of a Navier-Stokes flow in junctions at Reynolds number up to 100 yields the same accuracy and proves fast.
机译:考虑到代表性的水质模拟,我们着眼于重建饮用水网络中相关的二维(2D)流量,特别是在关键元素(如管道连接处)中。从最佳控制理论出发,已开发出一种使用较少传感器和计算流体动力学(CFD)模型的特定逆向技术。首先,我们通过最小化数据失配函数来确定边界速度,即控制参数。然后,在知道边界速度的情况下,对流模型进行直接求解,以获得水流的时空制图。为了减少要确定的控制参数的数量并因此限制传感器的数量,边界速度的空间形状被视为水管工程文献给出的先验信息。因此,仅需确定边界速度的时间演化。本文提出的整个数值程序很容易安装在通用的有限元软件中,具有广泛的用户友好性。研究了两种方法来减少与流重构相关的计算时间。伴随框架用于最小化过程。研究了使用粗糙离散化和简单流模型代替二维Navier-Stokes方程重建流的方法。在两个示例中研究了流量建模和离散化对重构速度质量的影响:一个水管连接点和一个法国水网的200m分段。在水管交界处,我们表明,在雷诺数为200时,结合了非稳态Stokes重构和单个直接Navier-Stokes仿真的混合方法优于基于单个模型的算法。在网络小节中,我们基于Navier-Stokes方程(雷诺数为200)与从Stokes方程重建的速度之间的参考速度之间的L-2误差小于1%。在这种情况下,重建持续不到1分钟。雷诺数最大为100的路口中基于Navier-Stokes流的基于Stokes的重构产生了相同的精度并且证明了速度很快。

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