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Steel and Composite Structures
  Volume 3, Number 3, June 2003 , pages 185-198

Statistical properties of the maximum elastoplastic story drift of steel frames subjected to earthquake load
Gang Li

    The concept of performance based seismic design has been gradually accepted by thernearthquake engineering profession recently, in which the cost-effectiveness criterion is one of the mostrnimportant principles and more attention is paid to the structural performance at the inelastic stage. Since there are many uncertainties in seismic design, reliability analysis is a major task in performance based seismic design. However, structural reliability analysis may be very costly and time consuming because the limit state function is usually a highly nonlinear implicit function with respect to the basic design variables, especially for the complex large-scale structures for dynamic and nonlinear analysis. Understanding statistical properties of the structural inelastic deformation, which is the aim of the present paper, is helpful to develop an efficient approximate approach of reliability analysis. The present paper studies the statistical properties of the maximum elastoplastic story drift of steel frames subjected to earthquake load. The randomness of earthquake load, dead load, live load, steel elastic modulus, yield strength and structural member dimensions are considered. Possible probability distributions for the maximum story are evaluated using K-S test. The results show that the choice of the probability distribution for the maximum elastoplastic story drift of steel frames is related to the mean value of the maximum elastoplastic story drift. When the mean drift is small (less than 0.3%), an extreme value type I distribution is the best choice. However, for large drifts (more than 0.35%), an extreme value type II distribution is best.
Key Words
    steel frames; elastoplastic analysis; seismic design; probability distribution; K-S test.
Department of Engineering Mechanics, State Key Laboratory of Structural Analysis of Industrial Equipment, Dalian University of Technology, Dalian, 116024, China

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