Nonlinear dynamic analysis of frames with stochastic non-Gaussian material properties

Abstract The efficient prediction of the nonlinear dynamic response of structures with uncertain system properties poses a major challenge in the field of computational stochastic mechanics. In order to investigate realistic problems of structures subjected to transient seismic actions, an efficient approach is introduced. The presented methodology is used to assess the response of a steel frame modeled with a mixed fiber-based, beam–column element. The adopted modeling provides increased accuracy compared to traditional displacement-based elements and offers significant computational advantages for the analysis of systems with stochastic properties. The uncertain parameters considered are the Young’s modulus and the yield stress, both described by homogeneous non-Gaussian translation stochastic fields. The frame is subjected to natural seismic records that correspond to three levels of increasing seismic intensity as well as to spectrum-compatible artificial accelerograms. Under the assumption of a pre-specified power spectral density function of the stochastic fields that describe the two uncertain parameters, the response variability is computed using Monte Carlo simulation. A parametric investigation is carried out providing useful conclusions regarding the influence of different non-Gaussian distributions (lognormal and beta) and of the spectral characteristics of the stochastic fields on the response variability.

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