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In order to characterise the material and damage behaviour of additively manufactured polyamide 12 (PA12) under quasi-static load and to implement it in a numerical model, experiments under quasi-static load as well as microstructural investigations were carried out. Selective laser sintering (SLS) was used as the manufacturing process. For the classification of the material behaviour, quasi-static cyclic tests with holding times as well as tensile tests were performed. X-ray refraction and computed tomography (CT) were used to investigate the damage behaviour. The Chaboche model, which has already been applied for metallic materials under thermomechanical loading, served as the basis for the selection of the numerical material model. The same procedure was used for the selection of the damage model, where the Gurson–Tvergaard–Needleman (GTN) model was chosen, which was already used for porous metallic materials. The Chaboche model shows very good agreement with experimental results. Furthermore, the coupling with the GTN model allows a very good modelling of the damage behaviour. Finally, it could be shown that the selected models are suitable to simulate the material and damage behaviour of 3D printed PA12.
The material and damage behaviour of additively manufactured polyamide 12 under cyclic loading was characterized by cyclic tests and microstructure analysis by using microscopy, X-ray refraction, and computed tomography. The results were used to determine parameters for the viscoplastic material model by Chaboche and a damage model by Gurson-Tvergaard-Needleman. The temperature was monitored during the experiments and the self-heating effect was observed. By including this effect, a higher accuracy could be achieved with the results of mechanical experiments.
Complex materials (e.g., porous ceramics) need high resolution techniques at multi-scale levels. Microstructure is intimately linked to properties and performance. One technique (or even a few techniques) is not enough. X-ray refraction and CT are very powerful tools. Non-destructive characterisation and quantitative image analysis techniques (2D and 3D) are necessary to understand the anisotropy.