Evaluation of the Progressive Collapse of the Reinforced Concrete Frames Considering the Soil–Structure Interaction: Parametric Study Based on the Sensitivity Index
Author(s): |
Seyed Ali Ekrami Kakhki
Ali Kheyroddin Alireza Mortezaei |
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Medium: | journal article |
Language(s): | English |
Published in: | International Journal of Concrete Structures and Materials, December 2022, n. 1, v. 16 |
DOI: | 10.1186/s40069-022-00523-x |
Abstract: |
In this essay, to investigate the progressive collapse of the reinforced concrete (RC) frames, a nonlinear static pushdown analysis was performed with column removal scenarios from the first story. At first, a numerical model was simulated and verified with the experimental model in SeismoStruct software without soil–structure interaction (SSI). Afterward, the foundation, soil, and the RC frame were modeled simultaneously in FLAC software and verified with the numerical model of the SeismoStruct software. Furthermore, the effect of SSI was studied on the progressive collapse of RC frames based on the sensitivity index (SI). The sensitivity index is defined as the ratio of the residual capacity under gravity loading of the structure by removing the column to the value of the undamaged structure. The results showed that by considering SSI, the sensitivity index decreases. Then, a parametric study of the framed structures (thickness of the foundation) and substructures (soil density, soil types, soil layers, and the soil saturation conditions) was performed to evaluate the progressive collapse-resisting capacity based on the sensitivity index. The results showed that by considering SSI, with an increase in the soil density and decrease in the groundwater level, the conditions would be better for preventing progressive collapse. It was also shown that rock and silty sands (SM), compared to other studied soil types, and SM and silty sands—silty clay with low plasticity—silty sands (SM-CL/ML-SM), compared to other studied soil layers, are better for preventing progressive collapse. |
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data sheet - Reference-ID
10746188 - Published on:
04/12/2023 - Last updated on:
04/12/2023