DEVELOPMENT OF A PHYSICS-INFORMED MELT POOL MODEL FOR POROSITY PREDICTION IN ADDITIVE MANUFACTURING

Öz

Powder Bed Fusion–Laser Beam (PBF-LB) has emerged as a leading additive manufacturing technique for producing complex metallic components; however, its susceptibility to process-induced defects, particularly porosity, continues to limit its widespread application. In this study, a physics-informed computational framework was developed to predict porosity formation in Ti-6Al-4V parts by explicitly resolving transient thermal fields, melt pool dynamics, and layer-wise liquid fractions with temperature-dependent material properties. A dedicated graphical user interface was implemented, providing flexibility in defining the critical processing variables in PBF-LB. Model validation was performed using experimentally reported datasets from the literature. Benchmarking against melt pool geometries demonstrated that the algorithm successfully reproduced the depth and width evolution under different laser powers (100–195 W) and scan speeds (500–750 mm/s). Further comparisons with porosity data revealed strong quantitative consistency: for example, a numerical prediction of 0.19% porosity closely matched Archimedes (0.115%) and µ-CT (0.070%) results, while micrograph-based measurements indicated a higher value (0.204%). Across all investigated specimens, the algorithm reliably reflected experimentally observed porosity trends, including near fully dense conditions (<0.01%). The results demonstrate that the proposed framework provides an efficient and adaptable tool for predicting porosity in PBF-LB prior to fabrication.

Anahtar Kelimeler

• Porosity Prediction
• Thermal Modeling
• Ti-6Al-4V Alloy
• Additive Manufacturing.

Kaynakça

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