Degradation modelling of chaotic systems via random walks in phase space.

ABSTRACT: Accurately predicting long-term degradation in chaotic systems remains a fundamental challenge due to their sensitive dependence on initial conditions and non-periodic dynamics. Conventional numerical models, which rely on fine time-step integration, are computationally demanding and prone to cumulative errors. Here we present a phase-space random walk framework for degradation modeling in chaotic systems. The approach characterizes local degradation velocity distributions through short-time averaging and reconstructs the long-term evolution as stochastic transitions across phase-space regions. Validation on chaotic electronic and mechanical systems demonstrates that the method improves computational efficiency by over two orders of magnitude while maintaining prediction errors below five

SUBMITTER: Lu Z 

PROVIDER: S-EPMC12913597 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature