Predicting the long-term viscoelastic response by short-term tests in polymers - Reza Afshar; Nikhil Ebi; Bilen Emek Abali (Discover Applied Sciences)
Abstract Additive manufacturing, specifically Material EXtrusion (MEX) based 3-D printing technique in thermoplastic polymers, enables intricate geometries by depositing molten material out of a nozzle and building layer-upon-layer. By using sustainable thermoplastics, such as PolyLactic Acid (PLA) that generates less emission during production regarding conventional plastics, it is possible to produce parts with a smaller carbon footprint. However, the resulting anisotropic properties from this layered structure and unknown viscoelastic characteristics may introduce uncertainties in predicting the long-term mechanical performance of printed components. PLA is modeled as a linear elastic material, yet we emphasize that polymers may have a long relaxation time, hence, we conduct benchmark on significance of viscoelastic behavior and then model the response by exploiting the Time-Temperature Superposition (TTS) in order to predict viscoelastic response over a longer duration than measured. To model the viscoelastic behaviour, we use fractional time derivative. Then by using the inverse analysis, we obtain the best parameters, minimizing the error between the experiments and the predictive model. The determined parameters in the fractional Maxwell model, with the data of 16 h at three different temperatures, is then validated by predicting the response with an accuracy of ± 1% after 100 h.