Flaschel, Moritz Dr.
Dr. Moritz Flaschel
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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 CouncilAutomated 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.
2026
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Material Fingerprinting for rapid discovery of hyperelastic models: First experimental validation
In: Journal of the Mechanics and Physics of Solids 208 (2026), Article No.: 106463
ISSN: 0022-5096
DOI: 10.1016/j.jmps.2025.106463 - , , :
Shape-Space Graphs: Fast and Collision-Free Path Planning for Soft Robots
In: IEEE Robotics and Automation Letters 11 (2026), p. 5582-5589
ISSN: 2377-3766
DOI: 10.1109/LRA.2026.3674004
2025
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Material Fingerprinting: A shortcut to material model discovery without solving optimization problems
In: Computer Methods in Applied Mechanics and Engineering 450 (2025)
ISSN: 0045-7825
DOI: 10.1016/j.cma.2025.118573 - , , , :
Convex neural networks learn generalized standard material models
In: Journal of the Mechanics and Physics of Solids 200 (2025), Article No.: 106103
ISSN: 0022-5096
DOI: 10.1016/j.jmps.2025.106103
2023
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Automated Discovery of Material Models in Continuum Solid Mechanics (Dissertation, 2023)
DOI: 10.3929/ETHZ-B-000602750