Abstract
Laser powder bed fusion (LPBF) is an additive manufacturing technique that prints objects layer-by-layer by selectively melting powders using a focused laser. The mechanical properties of LPBF parts are affected by processing parameters that influence the flow within the melt pool. Marangoni convection is a surface tension dependent mass transfer process from the region of lower surface tension to the region of higher surface tension, influenced by temperature and the presence of surface-active elements. The Marangoni convection-induced flow pattern in the molten metal pool can induce different surface characteristics and defects. Tracking the surface oxide particles in the melt pool can be a potential mechanism for assessing the properties of the fabricated parts. Therefore, in this work, a particle tracking algorithm was developed to track the surface oxide particles in a melt pool produced using LPBF. The flow patterns in the melt pool were observed using high-speed camera. Binary images of the melt pool were simulated using MATLAB script based on the experimental observations. The particle tracking algorithm was used for different flow patterns: radially outward, radially inward, and rotational. Various factors affecting the accuracy of the particle tracking algorithm were identified, such as melt pool size, image pixel size, size and number of surface oxides, flow pattern, and particle velocity. The image pixel size, number of surface oxides, and particle velocity were found to have maximum influence on the accuracy. The probability of error has been quantified, and the causes of errors have been explored.
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