Probabilistic assessment of dynamic instability of frame structures under seismic excitations

Mitigation of collapses of structural systems caused by a strong earthquake shaking is crucial to reduce the potential casualties, injuries and economic losses. Hence, accurate risk assessment of structural collapse under seismic excitations is critical in efforts to promote hazard-resilience of the society. This paper summarizes the authors’ recent efforts for accurate prediction of structural collapse with systematic incorporation of uncertainty. Computational simulation models are developed for collapse test frames in the literature and validated using experimental data. Through the validated computational simulations of collapse, alternative collapse criteria are proposed in terms of dynamic instability, i.e. the loss of the ability to sustain the gravity loads. Using the new collapse criteria, key parameters that govern collapse capacity and collapse limit state functions are identified for more effective risk assessment. A probabilistic framework is also being developed for systematic treatment of uncertainties in the ground motion time histories and for risk-informed design of frame structures under earthquake hazards. multiple EDPs to predict the collapse more accurately. It is also noteworthy that the collapse capacity of a structure evaluated by the IDA-approach may be sensitive to a particular selection of ground motions as well as possible chaotic behavior of the IDA curve such as “structural resurrection. ” Although some deterministic rules have been proposed to handle such unusual behaviors of IDA (Vamvatsikos & Cornell 2002, 2004), it appears that there is a need for developing collapse criteria based on simulated collapse phenomena and a systematic procedure to identify impact of uncertainties in ground motions on the collapse capacity of a structural system. In order to overcome these challenges, a new probabilistic framework has been developed for accurate assessment of collapse of frame structures under stochastic ground motions. First, nonlinear dynamic analyses are performed for selected experimental case studies reported in the literature (Kanvinde 2003, Rodgers & Mahin 2004, Lignos et al. 2008) by use of OpenSees, an object-oriented software framework developed by Pacific Earthquake Engineering Center (PEER). Using OpenSees computational models validated by corresponding experimental results, new dynamic-instability-based collapse criteria are developed in terms of energy from the input ground motions and the gravity loads. The selected case studies are then used to test the new collapse criteria and to identify key parameters that govern the collapse of a structural system. Currently, procedures are being developed for probabilistic prediction of collapse limit states and corresponding structural demands, and for identification of critical parameters in collapse predictions. Using these procedures, the impact of uncertain ground motion details on the collapse limit states and structural demands is being investigated to provide guidelines on selection of ground motions for IDAbased studies and designs. This paper presents ongoing research activities in the proposed framework. First, the details of computational simulations of collapse test cases in the literature are presented. Second, the proposed collapse criteria based on dynamic instability, i.e. the loss of the ability to sustain the gravity loads are introduced. Using the selected experimental case studies, the new collapse criteria are compared with the traditional IDA-based approach. Finally, the paper introduces ongoing research activities for probabilistic assessment of collapse limit states, structural demands at collapse levels and for identification of critical parameters for collapse predictions. 2 VALIDATED COMPUTATIONAL SIMULATION OF COLLAPSE In order to develop the framework described in the previous section, it is necessary to build computational simulation models of collapse that are validated by available experimental test results. This section briefly describes the simulation tool and provides details of the computational simulation models of the selected collapse-case studies considered in this study.