Physics-Based porosity prediction in powder bed fusion – laser beam using a thermal simulation algorithm


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ÜLKE İ., YILMAZ O., MOLLAMAHMUTOĞLU M.

International Journal of Advanced Manufacturing Technology, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1007/s00170-026-17545-4
  • Dergi Adı: International Journal of Advanced Manufacturing Technology
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, Compendex, INSPEC, DIALNET
  • Anahtar Kelimeler: Additive manufacturing, Porosity prediction, Thermal modeling, Ti6Al4V alloy
  • Gazi Üniversitesi Adresli: Evet

Özet

Powder Bed Fusion–Laser Beam (PBF-LB) is a widely used additive manufacturing technique that enables the fabrication of geometrically complex components, yet it remains susceptible to internal defects, particularly porosity, which can compromise mechanical performance. This study presents a physics-based thermal simulation algorithm developed to predict porosity in Ti6Al4V parts fabricated via PBF-LB without relying on extensive training datasets. The algorithm numerically solves the transient three-dimensional heat conduction problem using the finite volume method, incorporating temperature-dependent material properties, a Gaussian-distributed laser heat source, and relevant thermal loss mechanisms. To validate the predictive capability of the model, six Ti6Al4V specimens were fabricated under varying process parameters using a PBF-LB system, and porosity levels were experimentally evaluated through Archimedes density measurements and high-resolution X-ray micro-Computed Tomography (µ-CT). Additional characterization by Scanning Electron Microscopy (SEM), optical microscopy, and Energy-Dispersive X-ray Spectroscopy (EDS) was performed on cross-sectioned subsurface regions to assess pore morphology and elemental homogeneity. The porosity values predicted by the simulation algorithm exhibited strong agreement with experimental findings in terms of trend and ranking, with predicted porosity ranging from 4.78% to 15.75% and µ-CT results ranging from 3.54% to 13.41%, thereby demonstrating the model’s effectiveness in capturing the relative impact of process parameters on porosity formation in PBF-LB fabricated components.