{"title":"风压的相关性分析和联合概率密度函数模型:关注台风气候下低层建筑的多元风荷载场","authors":"Bingchang Cui , Peng Huang , Zifeng Huang","doi":"10.1016/j.jweia.2024.105866","DOIUrl":null,"url":null,"abstract":"<div><p>The characteristics of the multivariate wind loads field on the roof are crucial to the wind-resistant design of low-rise buildings, which contain the correlation characteristics in space and probability characteristics in the time domain. This paper proposes a framework for constructing a Joint Probability Density Function (Joint PDF) model for a multivariate wind loads field. It provides a detailed correlation analysis for the first time. This paper employs wind pressure data collected from the roof of a low-rise building during Typhoon Muifa. It was found that the correlation becomes more robust with increasing roof pitch and the wind pressures are strongly correlated with a correlation coefficient exceeding 0.50 when the roof pitch is above 15°. The mixture distribution model is applied to the probability density function fitting procedure of wind pressure time series under typhoon climate, and the fitting effect is significantly better than other classical probability density functions. The optimal copula function is determined according to the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) for estimating the Joint PDF. The results reveal that Gumbel-copula and Student-copula have the highest proportion in optimal copula functions, accounting for over 90% of the total copula functions. Then, a bivariate Joint PDF for wind pressures are established with the optimal copula function. Additionally, the comparison between measured bivariate Joint PDF and that constructed using copula functions verifies the accuracy of the proposed framework for constructing Joint PDFs. The Joint PDF of wind pressures can enhance the understanding of the stochastic characteristics of local wind load fields on roofs, and the correlation characteristics in space provide crucial references for improving the accuracy of wind load random field simulation and saving the cost of wind resistance design.</p></div>","PeriodicalId":54752,"journal":{"name":"Journal of Wind Engineering and Industrial Aerodynamics","volume":"253 ","pages":"Article 105866"},"PeriodicalIF":4.2000,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Correlation analysis and joint probability density function model of wind pressures: Focusing on multivariate wind loads field on low-rise building under typhoon climate\",\"authors\":\"Bingchang Cui , Peng Huang , Zifeng Huang\",\"doi\":\"10.1016/j.jweia.2024.105866\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The characteristics of the multivariate wind loads field on the roof are crucial to the wind-resistant design of low-rise buildings, which contain the correlation characteristics in space and probability characteristics in the time domain. This paper proposes a framework for constructing a Joint Probability Density Function (Joint PDF) model for a multivariate wind loads field. It provides a detailed correlation analysis for the first time. This paper employs wind pressure data collected from the roof of a low-rise building during Typhoon Muifa. It was found that the correlation becomes more robust with increasing roof pitch and the wind pressures are strongly correlated with a correlation coefficient exceeding 0.50 when the roof pitch is above 15°. The mixture distribution model is applied to the probability density function fitting procedure of wind pressure time series under typhoon climate, and the fitting effect is significantly better than other classical probability density functions. The optimal copula function is determined according to the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) for estimating the Joint PDF. The results reveal that Gumbel-copula and Student-copula have the highest proportion in optimal copula functions, accounting for over 90% of the total copula functions. Then, a bivariate Joint PDF for wind pressures are established with the optimal copula function. Additionally, the comparison between measured bivariate Joint PDF and that constructed using copula functions verifies the accuracy of the proposed framework for constructing Joint PDFs. The Joint PDF of wind pressures can enhance the understanding of the stochastic characteristics of local wind load fields on roofs, and the correlation characteristics in space provide crucial references for improving the accuracy of wind load random field simulation and saving the cost of wind resistance design.</p></div>\",\"PeriodicalId\":54752,\"journal\":{\"name\":\"Journal of Wind Engineering and Industrial Aerodynamics\",\"volume\":\"253 \",\"pages\":\"Article 105866\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Wind Engineering and Industrial Aerodynamics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167610524002290\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Wind Engineering and Industrial Aerodynamics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167610524002290","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
摘要
屋顶多元风荷载场的特征对低层建筑的抗风设计至关重要,它包含空间的相关特征和时域的概率特征。本文提出了一个构建多元风荷载场联合概率密度函数(Joint Probability Density Function,Joint PDF)模型的框架。它首次提供了详细的相关性分析。本文采用了台风 "梅花 "期间从一栋低层建筑屋顶收集到的风压数据。研究发现,随着屋顶间距的增加,相关性变得更加稳健,当屋顶间距超过 15° 时,风压具有很强的相关性,相关系数超过 0.50。将混合分布模型应用于台风气候下风压时间序列的概率密度函数拟合过程,拟合效果明显优于其他经典概率密度函数。根据 Akaike 信息准则(AIC)和贝叶斯信息准则(BIC)确定了最佳 copula 函数,用于估计联合 PDF。结果显示,Gumbel-copula 和 Student-copula 在最优 copula 函数中所占比例最高,占全部 copula 函数的 90% 以上。然后,利用最优 copula 函数建立了风压的双变量联合 PDF。此外,测量的双变量 Joint PDF 与使用 copula 函数构建的 Joint PDF 之间的比较验证了所提出的构建 Joint PDF 框架的准确性。风压 Joint PDF 可以加深对屋顶局部风荷载场随机特征的理解,其空间相关特征为提高风荷载随机场模拟的精度和节约抗风设计成本提供了重要参考。
Correlation analysis and joint probability density function model of wind pressures: Focusing on multivariate wind loads field on low-rise building under typhoon climate
The characteristics of the multivariate wind loads field on the roof are crucial to the wind-resistant design of low-rise buildings, which contain the correlation characteristics in space and probability characteristics in the time domain. This paper proposes a framework for constructing a Joint Probability Density Function (Joint PDF) model for a multivariate wind loads field. It provides a detailed correlation analysis for the first time. This paper employs wind pressure data collected from the roof of a low-rise building during Typhoon Muifa. It was found that the correlation becomes more robust with increasing roof pitch and the wind pressures are strongly correlated with a correlation coefficient exceeding 0.50 when the roof pitch is above 15°. The mixture distribution model is applied to the probability density function fitting procedure of wind pressure time series under typhoon climate, and the fitting effect is significantly better than other classical probability density functions. The optimal copula function is determined according to the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) for estimating the Joint PDF. The results reveal that Gumbel-copula and Student-copula have the highest proportion in optimal copula functions, accounting for over 90% of the total copula functions. Then, a bivariate Joint PDF for wind pressures are established with the optimal copula function. Additionally, the comparison between measured bivariate Joint PDF and that constructed using copula functions verifies the accuracy of the proposed framework for constructing Joint PDFs. The Joint PDF of wind pressures can enhance the understanding of the stochastic characteristics of local wind load fields on roofs, and the correlation characteristics in space provide crucial references for improving the accuracy of wind load random field simulation and saving the cost of wind resistance design.
期刊介绍:
The objective of the journal is to provide a means for the publication and interchange of information, on an international basis, on all those aspects of wind engineering that are included in the activities of the International Association for Wind Engineering http://www.iawe.org/. These are: social and economic impact of wind effects; wind characteristics and structure, local wind environments, wind loads and structural response, diffusion, pollutant dispersion and matter transport, wind effects on building heat loss and ventilation, wind effects on transport systems, aerodynamic aspects of wind energy generation, and codification of wind effects.
Papers on these subjects describing full-scale measurements, wind-tunnel simulation studies, computational or theoretical methods are published, as well as papers dealing with the development of techniques and apparatus for wind engineering experiments.