Determination of the Fundamental Period of Infilled Reinforced Concrete Structures Through Probabilistic Analysis

Designing earthquake-resistant buildings requires an accurate computation of the fundamental period. Therefore, it is crucial to estimate it through a probabilistic approach. This paper aims to forecast the period of infilled RC structures using a probabilistic method, taking into account the uncertainties in the multivariate adaptive regression splines equation. Sensitivity analysis revealed that building height and its interaction with opening percentage have the most significant impact on period estimation, whereas span numbers have no significant effect. Moreover, the output statistical analysis of the Monte Carlo simulation-generated data revealed that the multivariate distribution fits all features. The 95% confidence interval demonstrated that the period standard deviation is more sensitive to feature variations than the mean. The uncertainty in the variation of span length and masonry stiffness had negligible effects on the mean period, while the opening percentage had the highest impact on period statistics. Furthermore, two expressions for period prediction with three and four features were developed, achieving an accuracy of 97% and 99%, respectively. The 95% prediction interval showed that most data points fell within the predicted intervals, illustrating low uncertainty in the developed formulas, and comparing them with the authors’ and building code formulas highlighted their superiority by achieving the lowest errors.