153 publications from this institution
The main goal of this research is to better understand progressive collapse mechanisms of buildings, and to evaluate the current modeling and analysis techniques and design methodologies. Field experiments and numerical simulations were performed to investigate the progressive collapse potential of several reinforced concrete and steel frame buildings. Up to four first-story columns were physically removed from the buildings to understand the subsequent load redistribution within each building. Experimental data from the field tests were used to compare and verify the computational models and analysis results. Due to the scarcity of data from full-scale tests, the experimental data of this research is a valuable addition to the state of knowledge on progressive collapse of buildings. The design guidelines typically recommend simplified analysis procedures involving instantaneous removal of specified critical columns in a building. This research investigates the effectiveness of such commonly used progressive collapse evaluation and design methodologies through numerical simulation and experimental data.
Collapse performance of two existing buildings was investigated through experimental testing and computational simulations. Each building was tested in the field by physically removing four first-story perimeter columns from each building prior to building's scheduled demolition. Linear static and nonlinear dynamic analyses were performed using two- and three-dimensional building frame models. Experimental data from the field tests of two buildings were used to compare and verify the computational analyses. The measured strain data compared relatively well with the analysis results. In particular, 3-D model was more accurate than the 2-D model. The strain values calculated from the nonlinear dynamic analysis were smaller than those from the linear static analysis, and were closer to the measured strains. Also, linear static analysis resulted in larger remandto- capacity ratios (DCR) and vertical displacements than nonlinear dynamic analysis for both 2-D and 3-D models.
