Abstract

This thesis presents a comprehensive investigation into the progressive collapse resistance of reinforced concrete (RC) framed structures using the Alternate Path Method (APM), a widely used threat-independent approach aimed at ensuring building stability after localized structural damage. Progressive collapse, characterized by disproportionate structural failure following the loss of one or more critical components, is often triggered by extreme events like explosions, impacts, or material degradation. The primary objective of this research is to evaluate the ability of RC frames to withstand progressive collapse under various column loss scenarios, while examining the effects of structural simplifications and modeling reductions on analysis accuracy.
The study investigates the behavior of full-frame and bare-frame models under the sudden removal of interior and corner columns. Nonlinear static and dynamic analyses were conducted using finite element modeling. Analytical models were validated against experimental data to ensure the reliability of numerical results, followed by the design and analysis of a multi-story case study building. Dynamic Increase Factors (DIFs) were calculated to account for the increased demands on structural elements due to the dynamic nature of column removal scenarios. Average values of approximately 1.33 and 1.67 were observed for full-frames and bare-frames, respectively. These results were more critical compared to the average DIF of 1.17 prescribed by the General Services Administration (GSA) and Unified Facilities Criteria (UFC) guidelines.
The influence of floor slabs on structural robustness was quantified, revealing enhancements ranging from 87% to 114% under quasi-static analysis and from 160% to 187% under dynamic analysis, further highlighting their contribution to resisting inertial forces. Model reduction techniques focusing on interior column loss showed that simplified models could predict load capacity within 2% error, offering significant computational savings without compromising reliability.
Finally, a simplified approximate method was developed to evaluate progressive collapse, estimating peak flexural/arch capacity with average errors of 5.6% for peak load and 17% for corresponding displacement compared to experimental results. This method, validated against experimental data, offers a practical tool for early-stage design evaluations, balancing accuracy and efficiency in progressive collapse assessment.