Stochastic virtual tests for fiber composites

Virtual tests combine experiments and theory to address physical, mathematical, and engineering aspects of material definition and failure prediction. The main research steps are: high resolution three-dimensional (3D) imaging of the microstructure, statistical characterization of the microstructure, formulation of a probabilistic generator for creating virtual specimens that replicate the measured statistics, creation of a computational model for a virtual specimen that allows general representation of discrete damage events, calibration of the model using high temperature tests, simulation of failure, and model validation. Key new experiments include digital surface image correlation and m-resolution 3D imaging of the microstructure and evolving damage, both executed at temperatures exceeding 1500°C. Conceptual advances include using both geometry and topology to characterize stochastic microstructures. Computational methods include new probabilistic algorithms for generating stochastic virtual specimens and a new Augmented Finite Element Method (A-FEM) that yields extreme efficiency in dealing with arbitrary cracking in such heterogeneous materials. The challenge of predicting the probability of an extreme failure event for a given stochastic microstructure in a computationally tractable manner, while retaining necessary physical details in models, is discussed.