PSI - Issue 38

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Benaouda Abdellaoui et al / Structural Integrity Procedia 00 (2021) 000 – 000

Benaouda Abdellaoui et al. / Procedia Structural Integrity 38 (2022) 116–131

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6. Conclusions and perspective The new design of the cable real in additive manufacturing (pivot) has an endurance limit of 10 6 approximately 2 times greater than the original part. On the other hand, according to the results obtained during the E-N fatigue characterization tests, we see very little plasticization. The material is very fragile. Finite element (FE) calculations were performed to provide the stress range for the damage estimation during repetitions of a constant amplitude stress spectrum. The modeling was carried out with Ansys and the fatigue analysis was performed with nCode DesignLife software. The FE results post-processing, using the E-N approach, leads to the critical zones mapping. However, the damage level and the critical zones are not in accordance with those obtained from the tested prototypes, because of the influence factors, the very flat EN curve and the quasi-straight cyclic stress-strain curve which leads to a strong scattering of the experimental results. A numerical modeling study was carried out and allowed to reproduce the critical areas as well as the values of the influencing factors that explain the behavior of the tested prototypes. That study led to the development of an analysis approach based on a damage density function calculation when applying distributed values of the different parameters that determine fatigue strength. The predicted failure probabilities were in good agreement with the results obtained during the tests on the prototypes. The approach that has been developed has allowed to extract from tests, sufficient information to evaluate the fatigue life of parts designed by topological optimization. The results of that study are currently being published [15] and will complement and enhance the work presented here. [1] Todd M.Mower, Michael J.Long, 2016. Mechanical behavior of additive manufactured,powder-bed laser-fused materials. Materials Science & Engineering A651 [2] M S I N Kamariahl et al., 2021. Effect of heat treatment on mechanical properties and microstructure of selective laser melting 316L stainless steel. 4th International Conference on Mechanical Engineering Research (ICMER2017). doi:10.1088/1757-899X/257/1/012021 [3] Andreau O., PhD thesis, 2019. Nocivité en fatigue et contrôle de défauts produits par fabrication additive. ENSAM. 2019-ENAM-0037 [4] Afkhamia S., Dabiria M., Alavib S. H., Björka T., Salminenc A., 2019, Fatigue characteristics of steels manufactured by selective laser melting. International Journal of Fatigue, Volume 122, Pages 72-83 [5] Liang X., thesis, 2020, High cycle fatigue behavior of additive manufactured stainless steel 316L: free surface effect and microstructural heterogeneity. HAL Id: tel-02951486 [6] ASTM E 1012-19. Verification of Testing Frame and Specimen Alignment - Under Tensile and Compressive Axial Force Application [7] ASTM E606/E606M – 19. Standard Test Method for Strain-Controlled Fatigue Testing [8] ASTM E466 – 15. Conducting Force Controlled Constant Amplitude Axial Fatigue Tests of Metallic Materials [9] Bonnet P., Hermite X., Huther I., Lefebvre F., 2016. Guide pour le choix d’une méthode d’essais de fatigue et de l’analyse statistique associée. CETIM References

[10] ISO 23788:2012(E). Metallic materials — Verification of the alignment of fatigue testing machines [11] ISO 12106:2017(E). Metallic materials — Fatigue testing — Axial-strain-controlled method [12] ISO 1099:2017(E). Metallic materials — Fatigue testing — Axial force-controlled method

[13] Flavenot J-F., Galtier A., Mongis J., Huther I., Thoquenne G., 2014. Comportement en fatigue des matériaux métalliques. CETIM [14] Lieurade H-P. & la Commission Fatigue des Métaux de la S.F.M., 1982. La pratique des essais de fatigue, Méthodes expérimentales et analyse des résultats, pyc edition, Paris [15] Amuzuga, P. et al.,2021, Fatigue behavior assessment of an additive manufactured topologically optimized part, by a probabilistic correlation approach based on a genetic algorithm (provisional title, soon published)