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.

737

Publications

40.6K

Citations

1.9K

Authors

755

Institutions

Publications per year

2017–2026

210

Authors

1.9K

  1. YE
    Yalchin Efendiev

    Texas A&M University, United States

    14 publications · 740 citations

    14

    h-index

  2. WK
    Wing Kam Liu

    Northwestern University, United States

    9 publications · 873 citations

    9

    h-index

  3. GA
    Gregory A. Voth

    University of Chicago, United States

    8 publications · 1.6K citations

    8

    h-index

  4. AS
    Alan S. Willsky

    Massachusetts Institute of Technology, United States

    8 publications · 780 citations

    8

    h-index

  5. ET
    Eric T. Chung

    Chinese University of Hong Kong, Hong Kong SAR China

    8 publications · 270 citations

    8

    h-index

1–5 of 1.9K

Venues

  1. Journal of Computational Physics

    52 publications · 3K citations

    30

    h-index

  2. 30

    h-index

  3. Chemical Engineering Science

    14 publications · 931 citations

    15

    h-index

  4. Multiscale Modeling and Simulation

    MMS · 15 publications · 741 citations

    14

    h-index

  5. 13

    h-index

1–5