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Minimization of Nonlinear Energies in Python Using FEM and Automatic Differentiation Tools

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00641368" target="_blank" >RIV/67985556:_____/25:00641368 - isvavai.cz</a>

  • Alternative codes found

    RIV/68145535:_____/25:00641368 RIV/60076658:12310/25:43910782

  • Result on the web

    <a href="https://doi.org/10.1007/978-3-031-85703-4_11" target="_blank" >https://doi.org/10.1007/978-3-031-85703-4_11</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-85703-4_11" target="_blank" >10.1007/978-3-031-85703-4_11</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Minimization of Nonlinear Energies in Python Using FEM and Automatic Differentiation Tools

  • Original language description

    This contribution examines the capabilities of the Python ecosystem to solve nonlinear energy minimization problems, with a particular focus on transitioning from traditional MATLAB methods to Python's advanced computational tools, such as automatic differentiation. We demonstrate Python's streamlined approach to minimizing nonlinear energies by analyzing three problem benchmarks - the p-Laplacian, the Ginzburg-Landau model, and the Neo-Hookean hyperelasticity. This approach merely requires the provision of the energy functional itself, making it a simple and efficient way to solve this category of problems. The results show that the implementation is about ten times faster than the MATLAB implementation for large-scale problems. Our findings highlight Python's efficiency and ease of use in scientific computing, establishing it as a preferable choice for implementing sophisticated mathematical models and accelerating the development of numerical simulations.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10102 - Applied mathematics

Result continuities

  • Project

    <a href="/en/project/GA24-10366S" target="_blank" >GA24-10366S: Coupled dissipative processes and deformation mechanisms in metastable titanium alloys</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Lecture Notes in Computer Science

  • ISBN

    978-3-031-85702-7

  • ISSN

    0302-9743

  • e-ISSN

    1611-3349

  • Number of pages

    15

  • Pages from-to

    159-173

  • Publisher name

    Springer Nature Switzerland AG

  • Place of publication

    Berlin

  • Event location

    Ostrava

  • Event date

    Sep 8, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001529693400011