Abstract
This paper gives a systematic introduction to HMM, the heterogeneous multiscale methods, including the fundamental design principles behind the HMM philosophy and the main obstacles that have to be overcome when using HMM for a particular problem. This is illustrated by examples from several application areas, including complex fluids, micro-fluidics, solids, interface problems, stochastic problems, and statistically self-similar problems. Emphasis is given to the technical tools, such as the various constrained molecular dynamics, that have been developed, in order to apply HMM to these problems. Examples of mathematical results on the error analysis of HMM are presented. The review ends with a discussion on some of the problems that have to be solved in order to make HMM a more powerful tool.
Original language | English (US) |
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Pages (from-to) | 367-450 |
Number of pages | 84 |
Journal | Communications in Computational Physics |
Volume | 2 |
Issue number | 3 |
State | Published - Jun 2007 |
All Science Journal Classification (ASJC) codes
- Mathematical Physics
- Physics and Astronomy (miscellaneous)
- Computational Mathematics
Keywords
- Constrained micro-scale solver
- Data estimation
- Heterogeneous multi-scale method
- Multi-physics models
- Multi-scale modeling