Probabilistic response and rare events in Mathieu's equation under correlated parametric excitation

Abstract

We derive an analytical approximation to the probability distribution function (pdf) for the response of Mathieu's equation under parametric excitation by a random process with a spectrum peaked at the main resonant frequency, motivated by the problem of large amplitude ship roll resonance in random seas. The inclusion of random stochastic excitation renders the otherwise straightforward response to a system undergoing intermittent resonances: randomly occurring large amplitude bursts. Intermittent resonance occurs precisely when the random parametric excitation pushes the system into the instability region, causing an extreme magnitude response. As a result, the statistics are characterized by heavy-tails. We apply a recently developed mathematical technique, the probabilistic decomposition-synthesis method, to derive an analytical approximation to the non-Gaussian pdf of the response. We illustrate the validity of this analytic approximation through comparisons with Monte-Carlo simulations that demonstrate our result accurately captures the strong non-Gaussianity of the response.

References in corpus (3)

• Spatial Process Generation
• A probabilistic decomposition-synthesis method for the quantification of rare events due to internal instabilities
• Probabilistic description of extreme events in intermittently unstable systems excited by correlated stochastic processes

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