A computational framework for Bayesian inference in plasticity models characterisation

The study presented offers at least two main contributions. Firstly, the design of CBPC to solve the main inference problems in plasticity, in an efficient way, is novel. In addition, its practical application in plasticity model characterisation problems, namely hardening and anisotropy parameter inference and the model class comparison in a multi-axial state of stress is justified and demonstrated.