Multibody Dynamics Analysis Under Uncertainty Using Time-Dependent Polynomial Chaos

EasyChair Preprint 13381

Abstract

The uncertainty of mechanical systems can occur from a lack of information, such as uncertain system parameters, random inputs, random initial conditions, and random forces. To consider these uncertainties, statistical approaches are commonly adopted. Recently, the polynomial chaos method has gained attention because of its fast convergence property and ability to describe uncertainty with functional representation. The polynomial chaos method can provide a stochastic representation of the response of multibody dynamics systems in both time and frequency domains. However, the polynomial chaos method loses its accuracy in the time domain with long-time evaluation. Especially in the multibody dynamics formulation, the polynomial chaos fails rapidly due to the high non-linearity of the system. In this work, we apply the time dependent polynomial chaos in the multibody dynamics problem to investigate the statistical uncertainty of the response after a long-time integration with only a few terms on a low order basis.

Keyphrases: Multibody dynamics, polynomial chaos, time-dependent, uncertainty quantification

@booklet{EasyChair:13381,
  author    = {Seok-Hee Han and Hee-Sun Choi and Jin Hwan Choi and Jin-Gyun Kim},
  title     = {Multibody Dynamics Analysis Under Uncertainty Using Time-Dependent Polynomial Chaos},
  howpublished = {EasyChair Preprint 13381},
  year      = {EasyChair, 2024}}