Probabilistic Seismic Evaluation of Reinforced Concrete Structural Components and Systems, PEER Report 2006-04

Abstract: 

An accurate evaluation of the structural performance of reinforced concrete structural systems under seismic loading requires a probabilistic approach due to uncertainties in structural properties and the ground motion (referred to as basic uncertainties). The objective of this study is to identify and rank significant sources of basic uncertainties and structural components with respect to the seismic demand (referred to as the Engineering Demand Parameters, EDP) of reinforced concrete structural systems. The methodology for accomplishing this objective consists of three phases. In the first phase, the propagation of basic uncertainties to a structural system with respect to its EDPs is studied using the first-order second-moment (FOSM) method and the tornado diagram analysis to identify and rank significant sources of basic uncertainties. In the second phase, the propagation of basic uncertainties to structural components with respect to their capacities is studied. For this purpose, the stochastic fiber element model is developed to build probabilistic section models such as the moment-curvature relationships at critical sections of the structural component. In the third phase, the propagation of uncertainty in the capacities of structural components to the structural system with respect to its EDPs is studied. Using the FOSM method combined with probabilistic section models, EDP uncertainties induced by structural components are estimated to identify and rank significant components. Several case studies demonstrate the effectiveness and robustness of the developed procedure of propagating uncertainties.

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Author: 
Tae-Hyung Lee
Khalid M. Mosalam
Publication date: 
August 1, 2006
Publication type: 
Technical Report
Citation: 
Lee, T-H., & Mosalam, K. (2006). Probabilistic Seismic Evaluation of Reinforced Concrete Structural Components and Systems, PEER Report 2006-04. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA.