Probabilistic analysis of resistance for RC columns with wind-dominated combination considering random biaxial eccentricity

Abstract

For reinforced concrete (RC) column with biaxial eccentricity, the conventional design methods usually use the fixed eccentricity criterion to check its resistance, which may underestimate the variations of column resistance. Based on the load statistics compatible with the codes, the random properties of biaxial eccentricity are analyzed with Monte Carlo simulation (MCS) for representative columns in regular frame structures under both vertical load and wind load. Then, the tested capacity results of 103 relevant column specimen are collected from literatures. The uncertainty of the resistance model is analyzed for the reciprocal load method in code ACI 318-14. Based on the criterion of both random eccentricity and fixed eccentricity, the probability regarding load bearing capacity exceedance is analyzed for columns by MCS with different design parameters (e.g. axial compression ratio, etc.). The results indicate that based on the prescribed load statistics, the random properties of eccentricities along two principal directions are mainly controlled by the stochastic wind load, leading to that the eccentricities along two principal directions show an approximate perfect correlation; the random biaxial eccentricity has a significant influence on resistance variations and the maximum coefficient of variation is as large as 0.73.

Keywords:

• RC column
• biaxial bending and axial compression
• wind-dominated combination
• random biaxial eccentricity
• resistance statistics

Acknowledgments

The research is supported by the National Key R&D Program of China (Grant No. 2021YFB2600900), Natural Science Fund for Distinguished Young Scholars of Hunan Province, China (Grant No. 2022JJ10050), Hunan Provincial Natural Science Foundation of China (Grant No. 2021JJ30716), Open Fund of Bridge Engineering of Changsha University of Science and Technology (Grant No. 19KC01) and Key Discipline Foundation of Civil Engineering of Changsha University of Science and Technology (Grant No. 18ZDXK01). This support is gratefully acknowledged.

Data available statement

All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Disclosure statement

No potential conflict of interest was reported by the authors.