Uncertainty quantification of multiscale composite damage initiation and progression

Uncertainty is inherent in composite materials, and causes several challenges when modeling and characterizing complex structures. There are uncertainties present at each length scale in composites, and quantifying these uncertainties is necessary in order to accurately model the mechanical response and damage progression of these materials. The ability to exchange information between length scales permits multiscale models to transport uncertainties from one scale to the next. Limitations in the physics and errors in numerical methods pose additional challenges for composite models. By replacing deterministic inputs with random inputs, stochastic methods can be implemented within these multiscale models making them more robust. A multiscale sectional model is used due to its efficiency and capacity to incorporate stochastic methods with little difficulty. A Latin hypercube sampling technique is used, due to its reported computational savings over other methods such as a completely random Monte Carlo simulation. Within this multiscale modeling framework, a progressive failure theory is implemented using these stochastic methods and a modified Hashin failure theory. A stochastic multiscale model with a progressive failure theory successfully captures variations of mechanical properties in composite materials.