| In the past several years,domestic and foreign researchers had conducted extensive studies on structures to resist progressive collapse.In existing studies,deterministic parameters were commonly selected while the uncertainties of the parameters were ignored.Therefore,in this study,the uncertainties in the loads,material properties,and geometric properties,were investigated.Moreover,the vulnerability and robustness of RC frame structures to resist progressive collapse were quantified by random pushdown analysis.The main contents were shown in below:(1)Based on the combination of the traditional pushdown method and correlation-reduced Latin hypercube sampling method,random pushdown method,which could consider the effects of uncertainties,was proposed and was utilized for vulnerability evaluation of RC frames to resist progressive collapse.The analysis results indicated that the normally cumulative distribution could describe the probabilistic characteristic of RC frames to resist progressive collapse.The loss of exterior column has higher risk than the loss of interior column.The building with larger floor numbers has higher risk when a ground column was lost.Based on regression analysis,empiric prediction formula could be obtained to correlate the floor number and the maximum load coefficient.(2)Based on "tornado diagram" method,the sensitivity of each uncertainty of RC frame structures for progressive collapse prevention was investigated.It was found that the uncertainties for structures to resist progressive collapse could not be ignored.Among them,the dead load,live load,yield strength and ultimate strength of the reinforcements,the compressive strength of concrete and reinforcement ratio have significant effects on RC frame structures to mitigate progressive collapse.(3)The quantitative assessment of robustness of RC frames to resist progressive collapse was carried out.It was demonstrated that the robustness was increasing with the increase of the floor number.For a building,the loss of a ground column has lowest robustness while the loss of a top column achieved the greatest robustness.Reducing the load combination and increase the reinforcement strength could enhance the robustness significantly. |