Development of a New Fundamental Period Formula for Steel Structures Considering the Soil-structure Interaction with the Use of Machine Learning Algorithms

Abstract

The fundamental period of buildings is an important parameter when designing seismic resistant structures. The current formulae proposed in design codes for determining the fundamental period of steel structures cannot accurately predict the fundamental period of real structures. In addition, most of the current formulae only consider the height of the structure in their formulation, while soil structure interaction (SSI) and the orientation of the I-columns that influence the fundamental period are usually neglected. This research focuses on the use of machine learning algorithms to obtain a new formula that accounts for different geometrical features of the superstructure, where the SSI effect is also considered. After training and testing a 40-feature formula, an additional 138 out-of-sample numerical results were used to further test the accuracy of the proposed formula’s prediction abilities. The validation resulted in a correlation of 99.71%, which suggests that the proposed formula exhibits high predictive features for the steel structures considered in this study.