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Seismic Damage and Collapse Assessment of Reinforced Concrete Frame Structures Using a Component-Classification Weighted Algorithm

Author

Listed:
  • Jizhi Su
  • Boquan Liu
  • Guohua Xing
  • Yudong Ma
  • Jiao Huang

Abstract

The seismic performance of reinforced concrete members under earthquake excitation is different from that of whole structures; collapse mechanism may occur because of severe damage to individual members, even if the structural damage is not significant. Therefore, the potential seismic damage of each member should be investigated specifically apart from that of overall structure. In this study, a global damage model based on component classification is proposed to analyze the structural damage evolution rule and failure mechanism; then, the computed damage is compared with the experimental phenomena of three 1/3-scale models of three-storey, three-bay reinforced concrete frame structures under low-reversed cyclic loading. In addition, a probabilistic approach is finally adopted to quantify the seismic performance of RC frame structures based on the proposed global damage model. Results indicate that the structures with lower vertical axial force and beam-to-column linear stiffness ratio still maintain a certain load-bearing capacity even when the interstorey drift angle exceeds the elastoplastic limit value and the cumulative damage of structures is mainly concentrated on the beam ends and column bottoms of the first floor at final collapse. Moreover, the structural failure probability at different performance levels would increase significantly if reinforced concrete frame structures suffer ground motions higher than the design fortification intensity, even up to eight times.

Suggested Citation

  • Jizhi Su & Boquan Liu & Guohua Xing & Yudong Ma & Jiao Huang, 2019. "Seismic Damage and Collapse Assessment of Reinforced Concrete Frame Structures Using a Component-Classification Weighted Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-19, August.
  • Handle: RePEc:hin:jnlmpe:6438450
    DOI: 10.1155/2019/6438450
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