Prediction of Crystallinity for Large-Scale Additive Manufacturing with Complex Temperature Histories

Kurzfassung

The introduction of additive manufacturing techniques using material extrusion may provide a means of bonding stiffening structures onto thermoplastic composite skins in-situ, offering a reduction in complexity, cost and lead time. Aerospace-grade semi-crystalline polymers, however, are difficult to process using these such techniques, largely owing the complex temperature histories and the crystallization behaviour affecting the diffusion bonding. In this paper, a Nakamura-based crystallization model for the new material grade 231GRA of short-fibre reinforced LM-PAEK is derived by means of re-fitting a published model for the similar TC1225 prepreg and introducing a new induction sub-model. Complex temperature histories are extracted from real printed structures with an infrared camera, and the final part crystallinity value is determined from DSC. The crystallinity simulation shows great sensitivity to the selection of emissivity, but matches the experimental values with some offset.