Stochastic Generalized‐Order Constitutive Modeling of Viscoelastic Spectra of Polyurea‐Graphene Nanocomposites

ABSTRACT Polyurea (PUA) elastomers are extensively used in a wide range of applications spanning from biomedical to defense fields due to their enabling mechanical properties. These materials can be further reinforced through the incorporation of nanoparticles to form nanocomposites. This study focuses on an IPDI‐based (isophorone diisocyanate) PUA matrix with exfoliated graphene nanoplatelet (xGnP) fillers. We propose a generalized‐order constitutive model by combining one Fractional Maxwell Model (FMM) and one Fractional Maxwell Gel (FMG) branch in a parallel configuration. This has been accomplished via introducing a new dimensionless number that bridges between these branches physically and mathematically. This model exhibits a maximum relative error of less than 2% when validated against the experimental master curves across more than ten decades of shifted frequency, demonstrating its robustness and accuracy. Through our systematic local and global (variance‐based) sensitivity analyses, we further investigate the behavior of the nanocomposites, leading to a priority list of model parameters in the order of their contribution to model uncertainty/sensitivity. The main contribution of the present study is to develop a robust and efficient framework to construct the most parsimonious constitutive models from data with a high degree of physical interpretability and generality of use in a range of applications.