2-D Microstructure Modeling based on Micrographs of Laser Powder Bed Fusion Melted Specimens

Year 2024, , 609 - 615, 03.10.2024

Ali Can Kaya

https://doi.org/10.21605/cukurovaumfd.1559938

Abstract

2D microstructural modeling based on the optical micrographs was successfully carried out. Creating a realistic microstructural model containing microstructural features such as fusion boundaries and phases makes it possible to analyze the relationship between the microstructure and property. We implemented this method to the 316 stainless steel (SS) laser powder bed fusion melted specimens. The optical micrographs were meshed and imported into finite element (FE) software. According to the results, the orientation of the fusion boundaries significantly influenced the mechanical properties of the printed parts. Stress localization was significant when the fusion boundaries were parallel to the loading direction. The situation differed when the fusion boundaries were perpendicular to the loading direction. In this case, the large amount and size of fusion boundaries showed significant ductility with homogenously distributed straining.

Keywords

Microstructure, FE method, Additive manufacturing, Fusion boundary

Lazer Toz Yataklı Füzyon ile Eritilmiş Numunelerin Mikrograflarına Dayalı 2 Boyutlu Mikroyapı Modellemesi

Abstract

Optik mikrograflara dayalı 2 boyutlu mikroyapısal modelleme başarıyla gerçekleştirildi. Füzyon sınırları ve fazlar gibi mikroyapısal özellikleri içeren gerçekçi bir mikroyapısal modelin oluşturulmasıyla mikroyapı ve özellik arasındaki ilişkinin analiz edilmesi mümkün olmuştur. Bu yöntemi 316 paslanmaz çelik (SS) lazer toz yataklı füzyon ile sinterlenmiş numunelere uyguladık. Optik mikrograflara mesh atıldı ve sonlu elemanlar (FE) yazılımına aktarıldı. Sonuçlara göre, füzyon sınırlarının yönelimi, 3d yazıcı ile üretilmiş parçaların mekanik özelliklerini önemli ölçüde etkilemektedir. Füzyon sınırları yükleme eksenine paralel olduğunda önemli bir gerilim lokalizasyonu oluşmuştur. Füzyon sınırları yükleme doğrultusuna dik olduğunda ise durum faklıdır. Bu durumda büyük miktarda ve boyuttaki füzyon sınırları, homojen olarak dağılmış bir şekil değiştirme ile önemli bir süneklik göstermiştir.

Keywords

Mikroyapı, Sonlu elemanlar metodu, İmalat, Füzyon sınırları

References

• 1. Kaya, A.C., Salamcı, M.U., Fleck, C., 2023. Influence of anisotropy on the deformation behavior in microtensile 316L steel specimens fabricated by laser powder bed fusion (PBF-LB/M). Materials Science & Engineering A, 863, 144521.
• 2. Shifeng, W., Shuai, L., Qingsong, W., Yan, C., Sheng, Z., Yusheng, S., 2014. Effect of molten pool boundaries on the mechanical properties of selective laser melting parts. Journal of Materials Processing Technology, 214, 2660-2667.
• 3. Guan, K., Wang, Z., Gao, M., Li, X., Zeng, X., 2013. Effects of processing parameters on tensile properties of selective laser melted 304 stainless steel. Materials & Design, 50, 581-586.
• 4. Rehme, O., Emmelmann, C., 2006. Rapid manufacturing of lattice structures with selective laser melting, in: Bachmann, F.G., Hoving, W., Lu, Y., Washio, K., (Eds.), Proc. SPIE 6107, Laser-Based Micropackaging, San Jose, CA, USA, p. 61070K.
• 5. Güden, M., Yavas, H., Tanrıkulu, A.A., Tasdemirci, A., Akın, B., Enser, S., Karakus, A., Hamat, B.A., 2021. Orientation dependent tensile properties of a selective-laser-melt 316L stainless steel. Materials Science & Engineering A, 824, 141808.
• 6. Hitzler, L., Hirsch, J., Heine, B., Merkel, M., Hall, W., Ochsner, A., 2017. On the anisotropic mechanical properties of selective laser-melted stainless steel. Materials, 10, 1136.
• 7. Ahmadi, A., Mirzaeifar, R., Moghaddam, N.S., Turabi, A.S., Karaca, H.E., Elahinia, M., 2016. Effect of manufacturing parameters on mechanical properties of 316L stainless steel parts fabricated by selective laser melting: a computational framework. Materials & Design, 112, 328-338.
• 8. Rodgers, T.M., Madison, J.D., Tikare, V., 2017. Simulation of metal additive manufacturing microstructures using kinetic Monte Carlo. Computational Materials Science, 135, 78-89.
• 9. Abramoff, M.D., Magelhaes, P.J., Ram, S.J., 2004, Image processing with Image J Biophoton. Int., 11, 36-42.
• 10. Ma, J., 2024. Im2mesh (2D image to triangular meshes) (https://www.mathworks.com/matlabcentral/ fileexchange/71772-im2mesh-2d-image-to-triangular-meshes), MATLAB Central File Exchange. Retrieved March 23, 2024.
• 11. Engwirda, D., 2014, Locally-optimal Delaunay-refinement and optimisation-based mesh generation. Ph.D. Thesis, School of Mathematics and Statistics, The University of Sydney, http://hdl.handle.net/2123/13148.
• 12. Kaya, A.C., 2020. In situ shear behavior of open-cell austenitic 316L steel foams. Materials Chemistry and Physics, 252, 123303.