Prediction and visualization of 3D wake field of a rectangular high-rise building in tropical island cities based on UAV measurements

IF 7.1 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
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Abstract

It is especially crucial to utilize measured data as samples to increase the accuracy of wind field prediction. However, scarce wake field measured data of high-rise buildings leads to the deviation between prediction results and the actual wake distribution. In this study, a six-rotor unmanned aerial vehicle wind measurement system (UAVWMS) equipped with an anemometer is used to measure the wake field of a rectangular high-rise building in a tropical island city, and the characteristics of fluctuating wind velocity spectra and distribution patterns of the wind velocity and turbulence intensity in the wake region are analyzed; the Kriging method is adopted to predict and visualize the three-dimensional (3D) wake field based on the measured data from UAVWMS. The results show that the exponential law is better than the logarithmic law in fitting the incoming wind velocity profile in the tropical island city. The measured points in the wake region, located near the central axis of the building, exhibit a pronounced reduction in wind velocity and an increase in turbulence intensity compared to those in the incoming region. Compared to the incoming wind velocity spectra and empirical spectra, the peak frequencies of wake wind velocity spectra shift to the high-frequency band. In addition, the wake wind velocity spectra are lower in the low-frequency band and higher in the high-frequency band. When designing a measured scheme based on UAVWMS, it's crucial to place measured points surrounding the target spatial wake field as much as possible. It helps enhance the accuracy of predicting wind parameters within the 3D spatial wake field. The research results provide a theoretical reference for the measurement, prediction and visualization of the wake field of high-rise buildings in dense urban buildings.
基于无人机测量的热带岛屿城市矩形高层建筑三维尾流场预测与可视化
利用实测数据作为样本来提高风场预测的准确性尤为重要。然而,高层建筑的尾流场测量数据稀少,导致预测结果与实际尾流分布存在偏差。本研究利用配备风速计的六旋翼无人机测风系统(UAVWMS)对某热带海岛城市矩形高层建筑的尾流场进行了测量,分析了尾流区域风速频谱的波动特征以及风速和湍流强度的分布规律,并基于 UAVWMS 的测量数据,采用克里金法对三维(3D)尾流场进行了预测和可视化。结果表明,在拟合热带海岛城市的入风风速曲线方面,指数规律优于对数规律。位于建筑物中轴线附近的尾流区的测量点与入风区的测量点相比,风速明显减小,湍流强度增加。与入射风速频谱和经验频谱相比,尾流风速频谱的峰值频率向高频段移动。此外,尾流风速频谱在低频段较低,而在高频段较高。在设计基于无人机尾流监测系统的测量方案时,尽可能将测量点置于目标空间尾流场周围至关重要。这有助于提高三维空间尾流场内风参数预测的准确性。研究成果为城市密集建筑中高层建筑尾流场的测量、预测和可视化提供了理论参考。
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来源期刊
Building and Environment
Building and Environment 工程技术-工程:环境
CiteScore
12.50
自引率
23.00%
发文量
1130
审稿时长
27 days
期刊介绍: Building and Environment, an international journal, is dedicated to publishing original research papers, comprehensive review articles, editorials, and short communications in the fields of building science, urban physics, and human interaction with the indoor and outdoor built environment. The journal emphasizes innovative technologies and knowledge verified through measurement and analysis. It covers environmental performance across various spatial scales, from cities and communities to buildings and systems, fostering collaborative, multi-disciplinary research with broader significance.
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