Evaluation on the progressive collapse resistance of infilled reinforced concrete frames based on numerical and semi-analytical methods. (15th September 2022) - Pang, Bo; Wang, Feiliang; Yang, Jian; Zhang, Wangxi; Huang, Xu-Hao; Azim, Iftikhar
Highlights: 3D solid-based numerical model of infilled RC frame specimen under progressive collapse scenario was established and validated. Failure behaviours and load–deflection curves for models with varying reinforcement configurations were predicted by FEM. Semi-analytical design models were proposed using gene expression programming approach based on the data from test and FEM. Abstract: The effect of infill walls on the progressive collapse behaviour of reinforced concrete (RC) frames should be fully considered due to the formation of alternative load paths. To explore the configuration that could affect the progressive collapse resistance of infilled RC frames, parametric analyses are performed based on the validated simulation method. In the study, the impact introduced by the extra tie and integrity rebars in walls is emphasised. It is indicated that the variation in the reinforcement ratio of tie rebars leads to a limited change in structural progressive collapse resistance. In contrast, with the arrangement of the integrity reinforcement, the progressive collapse resistance of the infilled frames is enhanced and the propagation of the diagonal cracks in partial infill walls is suppressed. The notable re-ascending trend in the resistance curve for models with integrity rebars reveals the significant development of the catenary action in the integrity reinforcement. Then, with the help of linear regression and gene expression programming (GEP) techniques, a semi-analytical model is proposed for the prediction of the load-bearing capacity of infilled frames after column loss. In the prediction model, the linear effect of geometrical parameters and the non-linear effect of openings on the progressive collapse resistance are included by introducing three modification coefficients. Based on the statistical assessment, the capability of this explainable model is verified, and the appropriate amount of integrity reinforcement to mitigate the progressive collapse is discussed.