Hierarchical Multiscale Methods
Hierarchical Multiscale Methods is a computational modeling framework that systematically decomposes a physical system into distinct, sequentially coupled scales—where each scale is governed by its own set of equations and solution methods—such that information is passed unidirectionally from finer to coarser scales through precomputed effective properties or responses, distinguishing it from concurrent or fully integrated multiscale approaches.
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C. W. Gear, James M. Hyman, Panagiotis G Kevrekidid et al. · Communications in Mathematical Sciences · 2003 · 798 citations · Full text
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Centre National de la Recherche Scientifique
Paris, France
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50 publications
2.8K citations
Texas A&M University
College Station, United States
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38 publications
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Stanford University
Stanford, United States
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Princeton University
Princeton, United States
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Massachusetts Institute of Technology
Cambridge, United States
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The University of Texas at Austin
Austin, United States
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1.2K citations
Rensselaer Polytechnic Institute
Troy, United States
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Northwestern University
Evanston, United States
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MMS · 15 publications · 741 citations
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