Abstract

Under the action of the same wind azimuth, the extreme values of the wind load effect components of building structures are generated in the along-wind, cross-wind, vertical, and torsional directions. In designing the wind-resistant structure, the extreme values of effect components need to be combined to determine the internal force envelope values of members. Complete quadratic combination (CQC) and Turkstra combination rules are often used to determine the combination value of extreme values of wind effect components. The extreme probability distribution expressions of the CQC, and the Turkstra and approximate rules, are derived. The simplified combination Equations and combination coefficients of the CQC and Turkstra approximate rules are proposed in this paper. We use the combination Equations and Monte Carlo simulation method to analyze the accuracy of Turkstra and its approximate rules. The results show that the combination extreme is associated with the correlation coefficients, mean values, ratios of standard deviations, and fluctuating extremes of effect components. The errors between Turkstra and its approximate rules are small when load effect components show a positive correlation. The errors are largest when the standard deviations of components are equal. Our research results provide a theoretical basis for the combination method of wind load effect components of building structures.

Highlights

  • The stationary random wind loads acting on each surface of a building structure have spatial correlation

  • Based on the TR rule, Tamura et al [6,7,8,9,10,11] undertook intensive research on the combination extreme of wind load effects of low-rise and medium-rise building structures, and the results showed that the extreme value of wind load effect combination derived from the TR rule is related to the correlation coefficient of the effect component, the aspect ratio of the building plane, the building height, the wind direction angle, and the wind pressure distribution when the wind load combination effect reaches the maximum

  • CHEN [12] studied the combination of wind load effect components according to the TR rule, and the results showed that the combination extreme value is affected by the correlation coefficient of the effect component and its amplitude ratio, whereas the correlation coefficient of the wind load effect component differs from the correlation coefficient of the wind load component

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Summary

Introduction

The stationary random wind loads acting on each surface of a building structure have spatial correlation. The CQC rule is based on reliability theory and has rigorous theoretical foundations, but it is not convenient in engineering applications, especially when multi-effect components are combined. This paper derives the probability distribution expressions of combination extremes of wind load effect components according to CQC combination rules and Turkstra and its approximate combination rules, and proposes simplified combination Equations and combination coefficients of CQC combination rules and Turkstra approximate combination rules. The approximate combination Equations and combination coefficients proposed in this paper enable engineers to calculate the extreme values of the wind load combination effect directly and by applying the extreme values of effect components in engineering design. The simplified combination Equations and combination coefficients of the CQC rule and Turkstra approximation rules proposed in this paper provide a theoretical basis for the extreme value combination method of wind load effect components of a building structure, which is convenient for engineering application

CQC Combination Rules and Simplified Combination Coefficients
TR Rule and Its Approximate Combination Rules
TR combination rule
TR1 Combination Rule and Simplified Combination Coefficients
TR2 Combination Rule
Applicability of TR and Its Approximate Combination Rules
Applicability of TR Rule
Example—Combination of Wind
Example—Combination of Wind Load Effect of a Portal Frame Structure
Findings
Conclusions
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