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Cited by 687

The DOI matches its OpenAlex record; 85 of the 85 references it cites were found in a registry or an index.

Heterogeneous Multiscale Methods: A Review

E Weinan, Björn Engquist, Xiantao Li, Weiqing Ren, Eric Vanden‐Eijnden·2007·Communications in Computational Physics

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.

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OpenAlex · 10.4208/cicp.2007.v2.p367

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Metadata

Authors
Weinan, E., Engquist, B., Li, X., Ren, W., & Vanden‐Eijnden, E.
Venue
Communications in Computational Physics
Publisher
Cambridge University Press
Published
2007-02-01
Volume
2
Issue
3
Pages
367-450
ISSN
1815-2406 (ISSN-L)
OpenAlex
W1390923
Cited by
687
References
85
FWCI
44.91
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Heterogeneous Multiscale Methods: A Review. https://app.cochat.ai/papers/10.4208/cicp.2007.v2.p367
The paper
Weinan, E., Engquist, B., Li, X., Ren, W., & Vanden‐Eijnden, E. (2007). Heterogeneous Multiscale Methods: A Review. Communications in Computational Physics. https://doi.org/10.4208/cicp.2007.v2.p367

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.