Kuhl, Ellen, Prof. Dr.-Ing.

Prof. Dr.-Ing. Ellen Kuhl

Department of Mechanical Engineering
Institute of Applied Mechanics (LTM, Prof. Steinmann)

Room: Raum 01.053
Egerlandstr. 5
91058 Erlangen

  • Automated Model Discovery for Soft Matter Systems

    (Third Party Funds Single)

    Project leader: ,
    Term: 1. July 2024 - 30. June 2029
    Acronym: DISCOVER
    Funding source: EU / European Research Council

    Automated models boosting research on soft matter

    Soft materials, which can be easily deformed or structurally altered by thermal or mechanical stress, are essential in modern life, affecting autonomy, sustainability and health. However, accurately modelling these materials is complex and usually limited to a few well-trained experts. The ERC-funded DISCOVER project aims to make constitutive modelling more accessible through automated model discovery. Objectives include developing neural networks that autonomously find the best models, parameters and experiments for various soft matter systems. Furthermore, researchers will assess model performance in different experiments and use Bayesian analysis to measure uncertainties. Automated model discovery should enable exploration of a vast range of model parameters, offering insight into soft matter systems that traditional methods cannot achieve.

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