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Window Proper Orthogonal Decomposition: Application to Continuum and Atomistic Data

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Book cover Reduced Order Methods for Modeling and Computational Reduction

Part of the book series: MS&A - Modeling, Simulation and Applications ((MS&A,volume 9))

Abstract

Proper Orthogonal Decomposition (POD) is a powerful tool for analyzing multidimensional data, especially of vector fields in large-scale simulations. In this article we review the Window Proper Orthogonal Decomposition (WPOD) proposed in [7] for analysis of continuum data and in [5] for analysis of atomistic fields.

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Author information

Authors and Affiliations

  1. BM T.J. Watson Research Center, 02142, Cambridge, MA, USA

    Leopold Grinberg

  2. Division of Applied Mathematics, Brown University, 02912, Providence, RI, USA

    Leopold Grinberg

  3. Division of Applied Mathematics, Brown University, 02912, Providence, RI, USA

    Mingge Deng

  4. Department of Mechanical Engineering, Ben-Gurion University, 84105, Beersheva, Israel

    Alexander Yakhot

  5. Division of Applied Mathematics, Brown University, 02912, Providence, RI, USA

    George Em Karniadakis

Authors
  1. Leopold Grinberg
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  2. Mingge Deng
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  3. George Em Karniadakis
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  4. Alexander Yakhot
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Corresponding author

Correspondence to Leopold Grinberg .

Editor information

Editors and Affiliations

  1. CMCS-MATHICSE, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Alfio Quarteroni

  2. MOX, Department of Mathematics “F. Brioschi”, Politecnico di Milano, Milan, Italy

    Alfio Quarteroni

  3. SISSA mathLab, International School for Advanced Studies, Trieste, Italy

    Gianluigi Rozza

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Grinberg, L., Deng, M., Karniadakis, G.E., Yakhot, A. (2014). Window Proper Orthogonal Decomposition: Application to Continuum and Atomistic Data. In: Quarteroni, A., Rozza, G. (eds) Reduced Order Methods for Modeling and Computational Reduction. MS&A - Modeling, Simulation and Applications, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-319-02090-7_10

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