利用大涡模拟研究高层建筑入流湍流不确定性对风压的敏感性

IF 9.1 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
L. W. Chew, A. F. Melaku, M. F. Ciarlatani, C. Gorlé
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引用次数: 0

摘要

大涡模拟(LES)可以帮助预测建筑物的风荷载,只要规定了具有代表性的入流湍流特性。本研究采用LES来评估建筑物表面的平均、均方根(rms)波动和峰值压力系数(Cp)对来流湍流不确定性的敏感性。与风洞测量结果相比,模拟的平均Cp预测得很好,入流湍流变化的影响可以忽略不计。均方根Cp随湍流强度和湍流长度尺度的增大而增大。增加湍流强度和湍流长度尺度的进口值可使流动分离侧壁的均方根Cp误差(RMSE)分别从0.049减小到0.026和0.047减小到0.024。最小Cp的响应类似,其中RMSE从0.382减少到0.280,从0.385减少到0.286。迎风面最大Cp在标称进口值下达到最低RMSE 0.089。在将输入湍流特性的不确定性纳入计算后,通过对输入湍流估计值的大小进行重复模拟,LES和实验之间的一致性显著提高。风洞实验往往不能测量来流的完整湍流特性,从而模糊了模拟结果的验证过程。研究结果建议通过风洞实验来测量和报告来流的完整湍流特性,以准确预测风荷载。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensitivity of inflow turbulence uncertainty on wind pressure on high‐rise buildings using large eddy simulations
Large eddy simulations (LES) can aid the prediction of wind loading on buildings, provided that representative inflow turbulence properties are prescribed. This study conducts LES to assess the sensitivity of the mean, root mean square (rms) fluctuation, and peak pressure coefficients (Cp) on building surfaces to the uncertainties in the incoming flow turbulence. Compared to wind tunnel measurements, the simulated mean Cp is well predicted, and the variation in inflow turbulence has a negligible effect. The rms Cp increases with increasing turbulence intensities and increasing turbulence length scales. Increasing inlet values of turbulence intensities and turbulence length scales reduces the root mean square errors (RMSE) of rms Cp from 0.049 to 0.026 and from 0.047 to 0.024, respectively, on the side surfaces with flow separation. The minimum Cp responds similarly, where the RMSE is reduced from 0.382 to 0.280 and from 0.385 to 0.286. The maximum Cp on the windward surface achieves the lowest RMSE of 0.089 at nominal inlet values. The agreement between LES and experiment improves significantly after incorporating uncertainties in the input turbulence properties by repeating simulations with smaller and larger values from the estimated turbulence inputs. Wind tunnel experiments often do not measure the complete turbulence properties of the incoming flow, thereby obscuring the validation process of simulation results. The findings recommend wind tunnel experiments to measure and report the complete turbulence properties of the incoming flow for accurate prediction of wind loading.
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来源期刊
CiteScore
17.60
自引率
19.80%
发文量
146
审稿时长
1 months
期刊介绍: Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms. Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.
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