A sensitivity-based approach for identifying dominant parameters in the progressive collapse response of reinforced concrete frames

Numerous incidents of progressive collapse in reinforced concrete (RC) buildings have demonstrated the severe consequences of localized failures propagating through the structural system. Although extensive research has identified governing factors, most studies rely on deterministic approaches that assume fixed material and geometric properties, neglecting inherent uncertainties. This study presents a sensitivity-based framework to evaluate the influence of uncertain material, geometric, and infill-related parameters on the progressive collapse response of RC buildings. Two structural configurations, bare frames and fully infilled frames, are analysed using nonlinear static pushdown analysis under multiple column removal scenarios representing different damage locations and levels of redundancy. Uncertainty is systematically incorporated, and the relative importance of input parameters is quantified using statistical and graphical sensitivity measures. The results reveal that collapse sensitivity is strongly scenario- and configuration-dependent, with corner and middle column removal cases exhibiting the highest sensitivity. In bare frames, beam depth and concrete compressive strength emerge as the dominant parameters, while in fully infilled frames, infill properties govern the response. Critically, the study demonstrates that collapse sensitivity is controlled not solely by uncertainty magnitude but by the structural significance of parameters under specific damage conditions. These findings provide a rational parameter prioritisation in progressive collapse design and possible uncertainty-aware basis for targeted robustness assessment.