Nonlinear Dynamic Response Variability and Reliability of Frames with Stochastic Non-Gaussian Parameters

Abstract

Current research efforts for the efficient prediction of the dynamic response of structures with parameter uncertainty concentrate on the development of new and the improvement of existing methods. However, they are usually limited to linear elastic analysis considering only monotonic loading. In order to investigate realistic problems of structures subjected to transient seismic actions, a novel approach has been recently introduced by the authors. This approach is used here to assess the nonlinear stochastic response and reliability of a three-storey steel moment-resisting frame in the framework of Monte Carlo simulation (MCS) and translation process theory. The structure is modeled with a mixed fiber-based, beam-column element, whose kinematics is based on the natural mode method. The adopted formulation leads to the reduction of the computational cost required for the calculation of the element stiffness matrix, while increased accuracy compared to traditional displacement-based elements is achieved. The uncertain parameters of the problem are the Young modulus and the yield stress, both described by homogeneous non-Gaussian translation stochastic fields that vary along the element. The frame is subjected to natural seismic records that correspond to three levels of increasing seismic intensity. Under the assumption of a pre-specified power spectral density function of the stochastic fields that describe the two uncertain parameters, the response variability of the frame is computed using MCS. Moreover, a parametric investigation is carried out providing useful conclusions regarding the influence of the correlation length of the stochastic fields on the response variability and reliability of the frame.