Transition Dynamics for a bistable membrane-type acoustic metamaterial system

Xia Feng; Jinqian Feng; Jin Su; Qin Guo; Youpan Han

doi:10.47297/taposatWSP2633-456931.20250602

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Transition Dynamics for a bistable membrane-type acoustic metamaterial system

Volume 6, Issue 2

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Transition Dynamics for a bistable membrane-type acoustic metamaterial system
Transition Dynamics for a bistable membrane-type acoustic metamaterial system
1.School of Science, Xi'an Polytechnic University, Xi'an, 710048, China
2.Xi'an International Science and Technology Cooperation Base For Big Data Analysis;and Algorithms, Xi'an, 710048, China.
Vol. 6, Issue 2, Pages: 163-170(2025)
Published：25 February 2025
DOI：10.47297/taposatWSP2633-456931.20250602
Accepted：

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Feng Xia,Feng Jinqian,Su Jin,et al.Transition Dynamics for a bistable membrane-type acoustic metamaterial system[J].Theory and Practice of Science and Technology,2025,06(02):163-170.
DOI：

Feng Xia,Feng Jinqian,Su Jin,et al.Transition Dynamics for a bistable membrane-type acoustic metamaterial system[J].Theory and Practice of Science and Technology,2025,06(02):163-170. DOI： 10.47297/taposatWSP2633-456931.20250602.

摘要

Abstract

Transition phenomena between bistable states induced by noise fluctuations have emerged as a critical topic in ensuring the reliability of complex systems. These transitions cause abrupt jumps between states

often compromising the structural stability of metamaterials. This paper investigates the transition dynamics in an acoustic metamaterial model. The Onsager-Machlup action functional theory provides a potential way to capture the most probable transition path within a small tube

governed by the Euler-Lagrange equation. Solving this boundary-value problem efficiently presents a significant challenge. To address this

we employ the physics-informed neural networks(PINNs) method enhanced with a combined optimizer. Our results demonstrate that the AdamW+LBFGS optimization approach consistently achieves the higher accuracy and the faster convergence. Additionally

we analyze the effects of transition time and noise fluctuations on the transition path. The findings reveal that noise fluctuations can trigger transitions

altering the transition path through various manifold orientations. The minimum probable transition time is also derived numerically.

关键词

Keywords

references

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