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Uncontrolled curing-induced residual stress and strain are significant limitations to the efficient design of thermoset composites that compromise their structural durability and geometrical tolerance. Experimentally validated process modeling for the evaluation of processing parameter contributions to the residual stress build-up is crucial to identify residual stress mitigation strategies and enhance structural performance. This work presents an experimentally validated novel numerical approach based on higher-order finite elements for the process modeling of fiber-reinforced thermoset polymers across two composite characteristic length scales, the micro and macro-scale levels. The cure kinetics is described using an auto-catalytic phenomenological model. An instantaneous linear-elastic constitutive law, informed by time-dependent material characterization, is used to evaluate the stress state evolution as a function of the degree of cure and time. Micromechanical modeling is based on Representative Volume Elements (RVEs) that account for random fiber distribution verified against traditional 3D FE analysis. 0/90 laminate testing at the macroscale validates the proposed approach with an accuracy of 9%. 

Chemical shrinkage in thermosetting polymers drives residual stress development and induces residual deformation in composite materials. Accurate characterization of chemical shrinkage during curing is therefore vital to minimize residual stresses through process modeling and optimize composite performance. This work introduces a novel methodology to measure the pre- and post-gelation chemical shrinkage of an epoxy resin using three-dimensional digital image correlation (3D-DIC). Differential scanning calorimetry (DSC) is employed to calculate reaction kinetics and correlate chemical shrinkage with the degree of cure. Rheology experiments are conducted to quantify gelation and validate post-gelation. 3D-DIC post-gelation results show excellent agreement with rheology. Pre-gelation results show the effect of the in-situ curing in the proximity of constraints on the global strain behavior. This work introduced an innovative approach to characterize the chemical shrinkage of thermosets during curing, which will enable accurate residual stress prediction for enhancing thermoset composite performance and provide insight into the in-situ polymer behavior during processing. 

The transverse tensile strength of composites is susceptible to size effects. Therefore, it is paramount to develop length-scale specific physical test procedures to validate computational models that estimate the transverse composite response using micromechanics. To this end, a computational process modeling and virtual mechanical testing framework are presented in this study to predict the transverse response of composite microstructures subjected to processing conditions. Informed by a comprehensive material dataset, the numerical model is shown to reliably predict the process-induced residual stress generation in composite microstructures and accurately evaluate its influence on their transverse strength prediction. A novel procedure to fabricate thin composite laminates from a single ply of carbon fibers and characterize their transverse tensile response is presented to validate the numerical model. The results show excellent agreement with the virtual test predictions. This study highlights the importance of length-scale specific testing to minimize the influence of size effect on the transverse composite strength. 

Molecular dynamics simulation of a thermoset network and the glass transition by heating and cooling.