A Rapid Predictive Model for Unsupported Printability of Inclined Metal Rods in Additive Manufacturing
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Wire Arc Additive Manufacturing offers an efficient and cost-effective route for printing large metal lattice or truss structures, where inclined rods are key components typically fabricated without supports. However, unsupported printing of these rods remains particularly challenging. Existing approaches largely rely on empirical tuning of pulsed processes, lacking a mechanistic understanding of the forming process and a rapid predictive model for process-parameter selection. Thermo-fluid simulations were performed for rods inclined at 0–45° based on phenomenological models. The simulations were validated against experimentally observed melt-pool morphologies and metallographically measured fusion boundaries. The results indicate that controlling melt-pool sagging is crucial for unsupported formation, as both insufficient and excessive sagging can shift the deposition path off the intended trajectory. Dimensionless analysis shows that sagging is driven by gravity and arc pressure, while being resisted by surface tension and mushy-zone resistance. Accordingly, a melt-pool dynamic model was developed by accounting for these dominant factors using scaling laws. Building on the rod’s heat transfer characteristics, a one-dimensional transient temperature model for pulsed heat input was derived via the Laplace transform. Coupling the thermal model with the dynamic model enables rapid prediction of melt-pool sagging. The model predictions were further benchmarked against measured temperature histories and surface roughness. Compared with constant-current processing, pulsed current enhances the melt pool’s heat dissipation capability, helping to mitigate excessive heat accumulation and thereby prevent melt pool collapse. During the initial stage of printing, the heat input should be reduced progressively to maintain the melt pool in a dynamic balance between heat absorption and dissipation. The developed model enables rapid optimization of pulsed process parameters and provides mechanistic insights into material-dependent differences in unsupported printability.
