Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published August 2019 | Accepted Version
Journal Article Open

Model-free data-driven methods in mechanics: material data identification and solvers


This paper presents an integrated model-free data-driven approach to solid mechanics, allowing to perform numerical simulations on structures on the basis of measures of displacement fields on representative samples, without postulating a specific constitutive model. A material data identification procedure, allowing to infer strain–stress pairs from displacement fields and boundary conditions, is used to build a material database from a set of mutiaxial tests on a non-conventional sample. This database is in turn used by a data-driven solver, based on an algorithm minimizing the distance between manifolds of compatible and balanced mechanical states and the given database, to predict the response of structures of the same material, with arbitrary geometry and boundary conditions. Examples illustrate this modelling cycle and demonstrate how the data-driven identification method allows importance sampling of the material state space, yielding faster convergence of simulation results with increasing database size, when compared to synthetic material databases with regular sampling patterns.

Additional Information

© 2019 Springer-Verlag GmbH Germany, part of Springer Nature. Received 15 February 2019; Accepted 19 May 2019; First Online 04 June 2019.

Attached Files

Accepted Version - 1903.07983.pdf


Files (5.1 MB)
Name Size Download all
5.1 MB Preview Download

Additional details

August 22, 2023
October 20, 2023