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Purpose

As an additive manufacturing technology, selective laser melting (SLM) has garnered significant attention due to its ability to fabricate complex samples. Ti-6Al-4V, characterized by its superior strength-to-weight ratio and corrosion resistance, is one of the most important raw materials for SLM printing. Nonetheless, Ti-6Al-4V samples, fabricated via SLM, frequently present high porosity and elevated surface roughness as defects. Given the swift thermal cycling inherent in the SLM process, studying the melt pool’s evolution using simulation tools is essential. The aim to this paper is to establish a reliable simulation model to study the influence of laser power and scanning speed on the melt track forming quality during the SLM processing. And the advantage of the visualization of the internal flow of the molten pool in the simulation model is used to analyze the formation reasons of some defects in the melt track.

Design/methodology/approach

This paper uses Fluent to create a model for the Ti-6Al-4V melt pool during the single-track formation in SLM. The developed model considers factors such as fluid dynamics, heat transfer, surface tension, the Marangoni effect and recoil pressure.

Findings

The simulation reveals the evolution patterns of the melt pool under different process parameters. The results demonstrate that both the laser power and scanning speed substantially impact the melt pool’s thermal properties and morphological features. At a lower energy density, defects such as unmelted particles and balling tend to occur, while at a higher energy density, defects such as keyholes and spattering tend to occur. This paper further analyzes the causes of these defects. In addition, the simulation analysis conclusions regarding the impact of process parameters on the melt track quality of Ti-6Al-4V samples are validated through experiments.

Originality/value

In summary, the findings of this study provide a reliable theoretical analysis of the evolution of the melt pool. This serves as a rational basis for optimizing process parameters and improving the quality of the melt track.

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