Failure behavior of PA12 based SLS lattice structure with macro-porosity

Abstract

Abstract. Nowadays the demands of high reliability, high mechanical properties under fatigue loading and ultra-light-weight design are topics of pressing needs in different industry applications. Additive manufacturing technique has great potential to meet such demands and Selective Laser Sintering (SLS) is the dominantly used one due to its versatility in material design, construction and the much higher achievable mechanical strength compared to its competing technologies like fused filament fabrication. In this study, it is aimed to give an insight to the fracture behaviour of SLS produced lattice structure with macro-porosity under compression load. The stress type and distribution on the lattice structure under compression load are anisotropic because of the unit cell topologies and the anisotropic processing condition. Therefore, different kinds of fracture types are evident depending on the region of the fractured struts.

Application of Machine Learning Techniques to Predict the Mechanical Properties of Polyamide 2200 (PA12) in Additive Manufacturing

“…Tables 2-4 describe the data based on the Tukey range test (looking at percentiles), including standard deviation values. The results illustrated in Figure 4 support the anisotropic behaviour of PA 12 reported earlier [13,23]. While the Tensile moduli for the XYZ and XZY orientations have similar distributions, the tensile modulus for the ZYX orientation has the widest variance and the lowest value.…”

“…A limited number of investigated features could be considered as another reason for such model performance. Since many studies have earlier reported that material properties have a significant impact on mechanical properties [3,13,18,23,41], and in this study they are not considered, this may have an impact on the obtained results.…”

“…Futhermore, Drummer et al [18] and Gümüs et al [23] studied how the size of the particles of the polymer powder and its viscosity influence mechanical properties. While Drummer et al [18] investigated the degradation behavior of PA12 based on the analysis of phase transition temperature and melt viscosity for both virgin and aged powder, Gümüs et al [23] have reported that the size and morphology of the particles could lead to the creation of pores, gaps, or/and voids in the fabricated parts. Thus, Flores Ituarte et al [22] have proposed to use a machine vision in combination with Design of Experiment (DOE) to monitor and control powder morphology.…”

Application of Machine Learning Techniques to Predict Mechanical Properties for Polyamide 2200 (PA12) in Additive Manufacturing

“…limited number of investigated features could be considered as another reason of such model performance. Since many studies have earlier reported that material properties has significant impact on mechanical properties[3,13,18,22,38], and in this study they are not considered, this may have an impact on the obtained results.However, prediction of Tensile Modulus based only on part positioning and STL model properties in ZYX orientation has promising results. Model based on the gradient boost regressor algorithm Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 5 March 2019 Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 5 March 2019 doi:10.20944/preprints201903.0051.v1…”

“…Besides, Drummer et al [18] and Gümüs et al [22] studied how size of the parcticles of polymer powder and its viscosity influence mechanical properties. While Drummer et al [18] investigated degradation behavior of PA12 based on the analysis of phase transition temperature and melt viscosity for both virgin and aged powder, Gümüs et al [22] have reported that size of the particles and morphology could lead to the creation of pores, gaps or/and voids in the fabricated parts. The influence of part orientation on mechanical properties has already been described in the details by [12,23,24].…”