This study aims to develop a Probabilistic Seismic Demand Model (PSDM) for pounding risk assessment suitable for use within modern performance-based design frameworks. In developing a PSDM, different choices can be made regarding the intensity measures (IMs) to be used, the record selection, the analysis technique applied for estimating the system response for different IM levels, and the model to be employed for describing the response statistics given the IM. In the present paper, some of these choices are analyzed and discussed by considering the case of two adjacent buildings modeled as single-degree-of- freedom systems with linear and nonlinear hysteretic behavior. Based on the comparison, an optimal demand model is sought as the one that permits to achieve confident estimates of the response parameter of interest, i.e., the relative displacement demand, with few time-history analyses. This property allows reducing the complexity and computational cost associated with the pounding risk assessment. © 2013 Taylor & Francis Group, London.
Probabilistic seismic demand analysis for pounding risk assessment
Freddi, Fabio;
2013-01-01
Abstract
This study aims to develop a Probabilistic Seismic Demand Model (PSDM) for pounding risk assessment suitable for use within modern performance-based design frameworks. In developing a PSDM, different choices can be made regarding the intensity measures (IMs) to be used, the record selection, the analysis technique applied for estimating the system response for different IM levels, and the model to be employed for describing the response statistics given the IM. In the present paper, some of these choices are analyzed and discussed by considering the case of two adjacent buildings modeled as single-degree-of- freedom systems with linear and nonlinear hysteretic behavior. Based on the comparison, an optimal demand model is sought as the one that permits to achieve confident estimates of the response parameter of interest, i.e., the relative displacement demand, with few time-history analyses. This property allows reducing the complexity and computational cost associated with the pounding risk assessment. © 2013 Taylor & Francis Group, London.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione