UNCERTAINTY QUANTIFICATION OF THE DYNAMIC FRACTURE TOUGHNESS OF PARTICULATE POLYMER COMPOSITES USING A SURROGATE BASED METHODOLOGY

Abstract

This paper presents an efficient framework of quantifying the inherent uncertainties in determining the dynamic fracture toughness of particulate polymer composites. The size, shape and the volume fraction of the particles added as fillers are one of the key factors affecting the overall behaviour of these composite materials. For the accurate design and analysis of such composites, the uncertainties associated with these parameters must be taken into consideration. In this context, the present work has used an artificial neural network in conjunction with the Monte Carlo simulation approach to investigate the effects of uncertainty propagation onto the output space of dynamic fracture toughness. The results of this study indicate that among the different input parameters, the effect of uncertainty in the aspect ratio has the most prominent effect on the dynamic fracture toughness. ©2022 Sharma et al.