Lateral Boundary Conditions for Complex Terrain Wind Simulations with Oblique Inflow Direction

被引:0
|
作者
Ting-Hsuan Ma
Inanc Senocak
机构
[1] University of Pittsburgh,
来源
Boundary-Layer Meteorology | 2023年 / 187卷
关键词
Box-perturbation method; Complex terrain; Immersed boundary method; Inflow; Outflow;
D O I
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中图分类号
学科分类号
摘要
Large-eddy simulation is a formidable method for predicting winds around complex terrain, but predictions can be highly dependent on the lateral boundary conditions used in the computations. When periodic boundary conditions are not an option because of terrain complexity, inflow and outflow boundary conditions must be adopted. A common practice in micro-scale wind simulations with incompressible flow solvers is to orient the terrain such that the incoming wind is always orthogonal to the inflow face and impose constant pressure outlet boundary conditions on a flat terrain far away from the region of interest. However, terrain reorientation becomes computationally expensive to ingest meandering winds as inflow. In the present work, we demonstrate shortcomings of this existing practice when oblique inflow angle is imposed at the inlet faces. To address these shortcomings, we pursue a Neumann-type pressure boundary condition at the outflow boundaries with a global mass conservation correction step on the momentum field. Additionally, we revise the so-called box perturbation method to generate evenly distributed turbulence at inlet faces with oblique inflow direction. We use the canonical channel flow, the Perdigão terrain, and the Askervein hill examples to demonstrate the effectiveness of our proposed fixes. The major benefits of our proposed approach are savings in computational cost due to the ability to use a smaller simulation domain and elimination of laborious terrain reorientation and tapering, and mesh generation steps for every new wind direction. We expect our approach to be beneficial, particularly, for model-chain approaches for arbitrarily complex terrain simulations.
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页码:567 / 590
页数:23
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