Model-Free Data-Driven Inference in Computational Mechanics

Understand

We extend the model-free Data-Driven computing paradigm to solids and structures that are stochastic due to intrinsic randomness in the material behavior.

• The behavior of such materials is characterized by a likelihood measure instead of a constitutive relation.
• We specifically assume that the material likelihood measure is known only through an empirical point-data set in material or phase space.
• The state of the solid or structure is additionally subject to compatibility and equilibrium constraints.