2011
DOI: 10.1016/j.cma.2010.09.018
|View full text |Cite
|
Sign up to set email alerts
|

Concurrent coupling of atomistic and continuum models at finite temperature

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
12
0

Year Published

2012
2012
2019
2019

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 19 publications
(12 citation statements)
references
References 21 publications
0
12
0
Order By: Relevance
“…However, as other authors have suggested [3,4], an approximate separation may be obtained by splitting the frequency spectrum into low and high frequency phonons using a cut-off frequency. This is achieved by monitoring the mechanical component of the relative motion of pairs of atoms.…”
Section: Methodsmentioning
confidence: 99%
“…However, as other authors have suggested [3,4], an approximate separation may be obtained by splitting the frequency spectrum into low and high frequency phonons using a cut-off frequency. This is achieved by monitoring the mechanical component of the relative motion of pairs of atoms.…”
Section: Methodsmentioning
confidence: 99%
“…Note that the equation of motion given in Equation does not include thermal fluctuation of the atoms. To account for the temperature effect, one can employ the Langevin equation of motion in which a dissipative friction force and a random force due to thermal fluctuation are added to Equation . For a system with a large number of atoms, direct time integration of Equation becomes very expensive.…”
Section: Theorymentioning
confidence: 99%
“…For instance, Karpov et al [80] have developed a concurrent atomistic continuum model by using analytical expressions for Θ and including a random force term to allow the passage of thermal energy between the atomistic and continuum regions. Mathew et al [81] have used a time dependent friction force and a weighted random force to treat thermal fluxes across the atomistic-continuum interface. The common feature in all these methods is the time history kernel function, which is built using different techniques.…”
Section: State Of the Art Of Multiscale Methodsmentioning
confidence: 99%