This paper deals with the static and dynamic response of a cantilever beam affected by Gaussian and non-Gaussian vector processes. The load is modeled by three different correlation structures based on the second-order Markov process, and the non-Gaussian random features are described by translation processes. Both the linear and geometrically nonlinear behavior are described using the finite element approach, and the beam mechanical characteristics (natural frequencies and damping) are varied to investigate their influence on the response. Finally, the Monte Carlo approach is used to estimate the response tatistics. The transverse displacement and the bending moment at the beam joints are used to summarize the obtained results in terms of skewness and kurtosis coefficients, and probability density functions. The study presented in this paper provides nformation on the influence of the load nature and the structural behavior on the response random features.

Geometrically Nonlinear Cantilever under Stochastic Loading Vectors

GIOFFRE', Massimiliano;GUSELLA, Vittorio
2002

Abstract

This paper deals with the static and dynamic response of a cantilever beam affected by Gaussian and non-Gaussian vector processes. The load is modeled by three different correlation structures based on the second-order Markov process, and the non-Gaussian random features are described by translation processes. Both the linear and geometrically nonlinear behavior are described using the finite element approach, and the beam mechanical characteristics (natural frequencies and damping) are varied to investigate their influence on the response. Finally, the Monte Carlo approach is used to estimate the response tatistics. The transverse displacement and the bending moment at the beam joints are used to summarize the obtained results in terms of skewness and kurtosis coefficients, and probability density functions. The study presented in this paper provides nformation on the influence of the load nature and the structural behavior on the response random features.
2002
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/123966
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