IS - Simulation and Fatigue in Metal Additive Manufacturing
3 MODELING APPROACH
Numerical simulations using FEM using the surface scans obtained by profilometry and tomography were recently reported in [10]. Based on extreme values statistics of a non-local fatigue indicator parameter (FIP), a methodology was proposed to take into account the effect of the surface roughness on the HCF life. Here a similar modeling approach based on transformation of the measured surface topography into a 3D finite element (FE) model of a thin surface layer is developed to quantify the effect of surface roughness on the resulting stress distribution. The approach is preliminarily applied to the specimen achieving the highest fatigue strength amongst those that were tested (i.e. Type C).
3.1 FE model generation
Tetrahedral elements were used within the FE model, with material behavior assumed to be linear elastic. The FE mesh, see the example of Fig. 4 was defined on the surface with nodes corresponding to data obtained from the optical profiler on the surface. The mesh size was therefore approximately 1.3 µm on the surface, increasing gradually towards the bulk to limit calculation times. A fixed constrain was applied to one of the two smaller faces orthogonal to the measured surface, while a constant axial load was applied to the other parallel face.
This configuration led to a nominal tensile stress state in the same direction as was induced during fatigue testing. Following calculation of the resulting stress state, the local stress concentration factor (Kt) was calculated by dividing the local elastic surface principal stress by the nominal stress calculated as the applied axis load divided by the nominal cross-section
Gianni Nicoletto, Giancarlo Tinelli. Adrian Lutey and Luca Romoli
of the modelled object.
Figure 4: Finite element model of the surface layer (Type C specimen)
3.2 FEM results
The stress concentration factor distribution on the as-built surface of the selected Type C sample is shown in Figure 5. The maximum value of Kt is 3.81, implying that the surface roughness has a significant influence on the resulting localized stress state.
Figure 5: Stress concentration factor (Kt) distribution on the as-built surface
Values of Kt for each node were imported into MATLAB to determine the stress concentration factor distribution over the entire surface. Values are presented in Fig. 6, where it can be seen that most of the surface has a value of Kt < 1.5, corresponding to limited or no
Gianni Nicoletto, Giancarlo Tinelli. Adrian Lutey and Luca Romoli
stress concentration. A small but significant proportion of nodes has values of 1.5 < Kt < 2.5.
A negligible fraction of the surface reaches even higher Kt values possibly due to discretization effects. These are only preliminary observations, while the on-going activity involves the FE modeling of the surface layers of the other specimen types to address the role of surface orientation (i.e. specimen fabrication direction).
Figure 6: Kt distribution vs percentage of surface area (Specimen Type C).
5 CONCLUSIONS
Two approaches have been presented correlating the surface topography of metallic specimens produced by SLM and the fatigue strength.
The first involved acquisition of the surface topography of SLM specimens built in different orientations with an optical profiler and correlation of the experimental fatigue strength with the average areal surface roughness and skewness. In most cases, an inverse correlation was found between the surface roughness and fatigue strength; however, this was not the case for all samples. By also considering skewness, the fatigue behavior could more accurately be accounted for as lower skewness factors were strongly correlated with lower fatigue strength due to the greater influence of surface valleys or incisions on crack formation and propagation.
The second approach, still at the preliminary stage, involved modelling a thin layer of the acquired surface with a FEM software and considering the ratio of the local elastic surface principal stress to the nominal stress for calculation of the local stress concentration factor (Kt). The distribution of Kt with respect to the surface area fraction shows that fatigue crack initiation occurs at localized areas of high stress. Here only Type C specimen surface was modeled. On-going work is directed in the FE modeling of the as-built surfaces of the other three specimen orientations.
Gianni Nicoletto, Giancarlo Tinelli. Adrian Lutey and Luca Romoli
REFERENCES
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[8] ISO 25178-2,2012 Geometrical product specifications (GPS)- surface texture: areal- part 2: terms, definitions and surface texture parameters
[9] ISO 13565-1:1996 Geometrical Product Specifications (GPS) -- Surface texture: Profile method; Surfaces having stratified functional properties -- Part 1: Filtering and general measurement conditions
[10] B. Vayssette, N. Saintier et al., Numerical modelling of surface roughness effect on the fatigue behavior of Ti-6Al-4V obtained by additive manufacturing, International Journal of Fatigue, 123 (2019) 180-195
Simulation of residual stresses due to SLM fabrication and correlation with directional fatigue behavior of AlSi10Mg
G. Nicoletto, D. Daviddi and A. Fornaci
II International Conference on Simulation for Additive Manufacturing - Sim-AM 2019 F. Auricchio, E. Rank, P. Steinmann, S. Kollmannsberger and S. Morganti (Eds)