Single Track Geometry Prediction of Laser Metal Deposited 316L-Si Via Multi-Physics Modelling and Regression Analysis with Experimental Validation

Biyikli M., Karagoz T., Calli M., Muslim T., ÖZALP A. A., BAYRAM A.

METALS AND MATERIALS INTERNATIONAL, cilt.29, sa.3, ss.807-820, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 3
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1007/s12540-022-01243-3
  • Dergi Adı: METALS AND MATERIALS INTERNATIONAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.807-820
  • Anahtar Kelimeler: Additive manufacturing, Laser metal deposition, Multi-physics model, Finite volume method, Cladding track geometry, PARAMETERS, SOLIDIFICATION, OPTIMIZATION, CLAD
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

Laser metal deposition (LMD) is an additive manufacturing process used in manufacturing freeform geometries, repair applications, coating and surface modification, fabrication of functionally graded materials. It has a broad range of applications in various industries, including aviation, space, defence, automotive, tooling, etc. In this work, a multi-physics model of the LMD process was developed to rapidly predict the geometrical characteristics of the single clad track using the commercial software package Flow-3D. The volume of fluid (VOF) method was integrated to differentiate the interface between the metallic and gaseous cells. To validate the numerical model single bead tracks were deposited, and cross-sections of the beads were analysed. Mathematical formulae to predict different aspects of the single clad track (height, width, and depth) were derived using regression analysis. The influence of the process parameters on the geometrical characteristics of the single clad track was analysed in detail using analysis of variance (ANOVA). Both multi-physics model and mathematical regression model results were compared to the experimental measurements. The results were in good agreement with the experimental results.