Moment Lyapunov exponents and stochastic stability of non-linear systems under white-noise excitation
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Bibliographic record
Abstract
The moment Lyapunov exponent (MLE) is a critical index for assessing the stochastic stability of structures and has been widely applied to linear systems. However, its application to strongly nonlinear systems remains limited due to the inadequacy of traditional methods, such as the method of stochastic averaging. This paper addresses this gap by analyzing the stochastic stability of strongly nonlinear structural systems subjected to parametric excitations modeled as white noise, using MLEs. The analysis begins with the formulation of a strongly nonlinear system. A stochastic averaging method based on a transformed energy envelope is developed to derive a system of Itô stochastic differential equations. Unlike conventional approaches that rely on the Euclidean norm of the state vector, a modified Khasminskii-type transformation is employed, using the square root of the system's Hamiltonian to study stability. To validate the analytical findings, Monte Carlo simulations are conducted to independently compute the MLE. Additionally, the largest Lyapunov exponents and a stability index are evaluated to further characterize the system's stochastic behavior. The effects of key parameters on stability are systematically investigated. This study offers novel insights into the stochastic dynamics of strongly nonlinear structural systems.
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| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
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| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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