Performance of different inflow turbulence methods for wind engineering applications
Performance of different inflow turbulence methods for wind engineering applications
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DOI：
10.1016/j.jweia.2022.105141
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发表时间：
2022-08-26
影响因子：
4.8
通讯作者：
Chowdhury, Arindam Gan
中科院分区：
文献类型：
--
作者：
Mansouri, Zahra;Selvam, Rathinam Panneer;Chowdhury, Arindam Gan
确定大涡模拟的入口边界条件是计算风工程中的一个关键问题。由于合成流入湍流不需要像循环或前体方法那样进行昂贵的预先流动模拟，因此是一种更可取的方法。在本研究中，考虑了不同的合成湍流发生器方法，研究了它们在风力工程中的应用性能。考虑的方法是a)数字滤波法（DFM）， b)不同形状函数的合成涡流法（SEM）， c)无散度合成涡流法（DFSEM）， d)两种各向异性湍流斑法（ATSM）。这些方法在SimCenter （https://simcenter.designsafe-ci）的湍流流入工具（TInF）中提供。org/backend-components/tinf/)。此外，将入口和建筑物位置的速度谱与不同入流方法的冯·卡门谱进行比较，以确定能量从入口携带到建筑物位置的情况。此外，评估了不同的方法，以查看它们是否在域中产生虚假压力。结果表明，除采用高斯形状函数的扫描电镜法（SEM- g）外，其他方法均存在伪压力。此外，SEM-G法是一种适用于建筑物峰值压力预测的方法，误差不超过30%。
Defining the correct inlet boundary conditions for large eddy simulations is a critical issue in computational wind engineering. Since synthetic inflow turbulence does not require costly prior flow simulations like recycling or precursor methods, it is a preferable approach. In this study, different synthetic turbulence generator methods are considered to investigate their performance in wind engineering applications. The considered methods are a) Digital Filter Methods (DFM), b) Synthetic eddy methods (SEM) with different shape functions, c) Divergence Free Synthetic Eddy Method (DFSEM), and d) two types of Anisotropy Turbulent Spot Method (ATSM). These methods are provided in Turbulence Inflow Tool (TInF) from the SimCenter (https://simcenter.designsafe-ci. org/backend-components/tinf/). Additionally, velocity spectrum at the inlet and building location is compared to the Von Karman spectrum for different inflow methods to determine how well the energy is carried from the inlet to the building location. Furthermore, different methods are evaluated to see whether they produce spurious pressure in the domain. It is concluded that spurious pressure exists in all the considered methods except SEM method with the Gaussian shape function (SEM-G). In addition, SEM-G is found to be a suitable method for peak pressure prediction on buildings with upmost 30% error.