高层建筑标准模型脉动风压特性大涡模拟适用方法研究

为提高钝体建筑结构绕流模拟结果的精度，基于两种大涡模拟(large eddy simulation, LES)入口湍流生成方法，分别为NSRFG（narrow band synthesis random flow generation）方法和CDRFG（consistent discretizing random flow generation）方法，进行CAARC(commonwealth advisory aeronautical research concil)高层建筑标准模型绕流的数值模拟比较研究。以风洞试验结果为参照，在对大气边界层湍流风场进行模拟验证的基础上，详细对比分析采用上述两种方法模拟得到的建筑表面平均和脉动风压系数、绕流场湍流结构、风压系数概率密度分布特性等的差异，并着重从脉动风压非高斯特性角度进行探讨，检验采用上述两种方法模拟钝体建筑结构绕流的适用性和准确性。结果显示：在受来流直接作用的建筑迎风面，采用两种方法模拟的脉动风压基本都符合高斯特性；而在受分离流和尾流作用的侧风面和背风面，采用NSRFG方法能更好地反映建筑表面脉动风压的非高斯特性。极值风压分析表明，为了满足99.38%的保证率，CAARC标准模型迎风面极大与极小峰值因子需分别取为3.0和2.5，侧风面和背风面极大和极小峰值因子需分别取为2.5和4.0。

Study on suitable method to simulate fluctuating wind pressurecharacteristics of standard high-rise building model based on LES

In order to improve the accuracy in simulations of the flow around bluff bodies, two new LES inflow turbulence generation methods, including the narrow band synthesis random flow generation (NSRFG) method and the consistent discrete random flow generation (CDRFG) method respectively, were adopted in the comparative study of the flow around the commonwealth advisory aeronautical research concil (CAARC) standard high-rise building model. The numerical verification work of the turbulent wind field for the atmospheric boundary layer (ABL) flow was conducted. Subsequently, the differences between the mean and fluctuating wind pressure coefficients, the turbulent flow characteristics, and the probability density distribution characteristics of the fluctuating wind pressure coefficients obtained by the two methods were analyzed by comparing with the wind tunnel test results. The non-Gaussian characteristics of the fluctuating wind pressure were addressed to verify their applicability and accuracy in simulating flow around bluff bodies. Results show that the fluctuating wind pressures obtained by the two methods on the windward side, which are directly affected by the incoming turbulent flow, both satisfy the Gaussian distribution. The NSRFG method reflects relatively better performance in simulating the non-Gaussian distribution for the fluctuating wind pressure on the lateral and leeward sides, which are more influenced by the separated and wake flow. To satisfy an insurance rate of 99.38%, analysis of peak wind pressure shows that the maximum and minimum peak factors on the windward side of the CAARC model should be taken as 3.0 and 2.5 respectively, while those values should be 2.5 and 4.0 on the lateral and leeward sides.