Treffer: DEVELOPMENT OF A TOOL FOR AUTOMATED CURE KINETICS INVESTIGATION AND UNCERTAINTY QUANTIFICATION.

Process modeling of polymer composites manufacturing is a strategic approach that organizations within the composites industry are leveraging to more rapidly design and mature new processes and optimize existing ones. For composite material systems with a thermosetting polymer matrix, the degree of cure is the primary state variable that governs the evolution of material properties during processing. The cure-induced evolution of material properties influences the development of residual stresses and manufacturing defects and subsequently effects the final part performance. Therefore, one of the first steps in modeling the manufacturing process of composites with a thermosetting polymer matrix is to develop a cure kinetics model. Common procedures for developing a cure kinetics model to describe the curing behavior of a thermosetting resin system are mature and codified in various standards. However, variability in the differential scanning calorimetry (DSC) experiments used to develop the models and uncertainty in the post-processing techniques are typically not accounted for in the model. This research developed a practical Python script-based tool for automated cure kinetics model development (TACKI) with experimental DSC data. The tool uses Bayesian methods for model calibration and uncertainty quantification and supports calibration of theoretically any phenomenological cure reaction model. Using TACKI cure kinetics models for three different epoxy resin systems (Aerotuf 275-34 ^TM, Quintum Q1, and Epolam 2015) were calibrated with limited prior information, and the resulting model predictions showed good agreement with the experiments. This paper also briefly touches on the challenges associated with using traditional phenomenological cure reaction models, and ongoing research that is being performed to model the behavior of rate-dependent cure reactions. [ABSTRACT FROM AUTHOR]

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