Reduced-order Multiscale Modeling

Reduced-Order Multiscale Modeling is a computational modeling framework that belongs to the class of multiscale methods by integrating information across multiple spatial or temporal scales, distinguished by its use of dimensionality reduction techniques to simplify high-fidelity models while preserving essential system dynamics for efficient simulation and analysis.

58

Publications

2.2K

Citations

168

Authors

89

Institutions

Publications per year

2017–2026

29

Authors

168

  1. TI
    Traian Iliescu

    Virginia Tech, United States

    4 publications · 172 citations

    4

    h-index

  2. AE
    Alfredo E. Huespe

    Centro de Investigación de Métodos Computacionales, Argentina

    3 publications · 241 citations

    3

    h-index

  3. JO
    J. Oliver

    Universitat Politècnica de Catalunya, Spain

    3 publications · 241 citations

    3

    h-index

  4. CO
    Caglar Oskay

    Vanderbilt University, United States

    3 publications · 111 citations

    3

    h-index

  5. RC
    Ramon Codina

    Universitat Politècnica de Catalunya, Spain

    2 publications · 67 citations

    2

    h-index

1–5 of 168

Venues

  1. 8

    h-index

  2. Journal of Computational Physics

    6 publications · 508 citations

    6

    h-index

  3. 4

    h-index

  4. 3

    h-index

  5. 3

    h-index

1–5