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Data-driven Modeling in Mechanics

Laura de Lorenzis, ETHZ

Francisco Chinesta, ECN-Nantes

Pierre Ladeveze, ENS Paris-Saclay

Michael Ortiz, California Institute of Technology

The data-driven modeling paradigm is quickly emerging as a future game changer in the mechanics community. The exploration of its potential started recently but is attracting an enormous attention. The contributions welcomed in this Minisymposium focus on data-driven approaches in mechanics for purposes including (but not limited to) model-free solution of boundary value problems, automatic discovery of governing equations, and surrogate modeling. Research results on basic data-driven and mixed data-physics driven formulations, data generation procedures, probabilistic approaches, numerical implementation aspects, as well as extensions and relevant applications are all welcome.