  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.
