Hierarchical Multiscale Modeling

Hierarchical Multiscale Modeling is a multiscale modeling framework that systematically integrates distinct scales of physical phenomena through sequentially nested, one-way coupled models, where information is passed from finer to coarser scales in a top-down or bottom-up structure without feedback loops, thereby enabling the prediction of macro-scale behavior based on micro-scale constitutive or structural details.

221

Publications

14.8K

Citations

698

Authors

328

Institutions

Publications per year

2017–2026

74

Authors

698

  1. DG
    Dionisios G. Vlachos

    University of Delaware, United States

    7 publications · 511 citations

    7

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  2. JZ
    Jidong Zhao

    Hong Kong University of Science and Technology, Hong Kong SAR China

    6 publications · 608 citations

    6

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  3. WK
    Wing Kam Liu

    Northwestern University, United States

    5 publications · 551 citations

    5

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  4. NG
    Ning Guo

    Zhejiang University, China

    4 publications · 518 citations

    4

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  5. SL
    Shaofan Li

    University of California, Berkeley, United States

    3 publications · 98 citations

    3

    h-index

1–5 of 698

Venues

  1. 9

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  2. 6

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  3. Chemical Engineering Science

    5 publications · 255 citations

    5

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  4. Computers & Chemical Engineering

    5 publications · 215 citations

    5

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  5. 5

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1–5