Abstract
In this paper, we propose a multiscale coupling approach to perform Monte-Carlo simulations on systems described at the atomic scale and subjected to random phenomena. The method is based on the Arlequin framework, developed to date for deterministic models involving coupling a region of interest described at a particle scale with a coarser model (continuum model). The new method can result in a dramatic reduction in the number of degrees of freedom necessary to perform Monte-Carlo simulations on the fully atomistic structure. The focus here is on the construction of an equivalent stochastic continuum model and its coupling with a discrete particle model through a stochastic version of the Arlequin method. Concepts from the Stochastic Finite Element Method, such as the Karhünen-Loeve expansion and Polynomial Chaos, are extended to multiscale problems so that Monte-Carlo simulations are only performed locally in subregions of the domain occupied by particles. Preliminary results are given for a 1D structure with harmonic interatomic potentials.
Original language | English (US) |
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Pages (from-to) | 3530-3546 |
Number of pages | 17 |
Journal | Computer Methods in Applied Mechanics and Engineering |
Volume | 197 |
Issue number | 43-44 |
DOIs | |
State | Published - Aug 1 2008 |
Externally published | Yes |
Keywords
- Arlequin method
- Particle model
- Polynomial Chaos
- Stochastic PDE's
ASJC Scopus subject areas
- Computational Mechanics
- Mechanics of Materials
- Mechanical Engineering
- General Physics and Astronomy
- Computer Science Applications