JOURNAL ARTICLE

Nonlinear Stochastic Oscillation of a Single-Degree-of-Freedom Dielectric Elastomer Generator.

  • Published In: International Journal of Structural Stability & Dynamics, 2026, v. 26, n. 5. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Hao, Ying; Yu, Xinmiao 3 of 3

Abstract

This paper investigates the stochastic nonlinear dynamic response of a single-degree-of-freedom dielectric elastomer generator under the combined action of harmonic excitation and stochastic disturbance. First, the nonlinear vibration model of a single-degree-of-freedom dielectric elastomer generator is established. The average method and fourth-order Runge–Kutta method are used to analyze the influence of pre-stretching, the initial membrane length, the charge amount, and the external excitation amplitude on the system response. Considering stochastic disturbance, the stochastic average method is applied to determine the probability density function (PDF) of the system's steady-state response, and Monte Carlo numerical simulations are compared with the theoretical calculations for verification. The oscillation amplitude of the steady-state response can be increased by increasing the pre-stretching, harmonic excitation amplitude, and stochastic disturbance intensity. In the case of stochastic disturbance, as the intensity of the disturbance increases, the system becomes more likely to exhibit large amplitude responses for longer durations. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Structural Stability & Dynamics. 2026/02, Vol. 26, Issue 5, p1
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2026
  • ISSN:0219-4554
  • DOI:10.1142/S0219455425502645
  • Accession Number:191103694
  • Copyright Statement:Copyright of International Journal of Structural Stability & Dynamics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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