Abstract

A semi-elliptical moving heat source approach is used to predict the in-process temperature profile inside the build part during laser-based metal additive manufacturing (AM) processes. The laser has a constant heat strength which releases its energy continuously on the semi-infinite medium. It is assumed that the medium is initially at room temperature. In the proposed analytical model, some details are considered to predict the melt pool geometry more accurately and realistically. The thermal material properties are considered to be temperature dependent since the existence of the steep temperature gradient affects the magnitude of the thermal conductivity and specific heat, and as a result, it changes the heat transfer mechanisms. Moreover, the melting/solidification phase change is considered using the modified heat capacity. The multi-layer aspect of the metal AM part is considered in the modeling of the temperature profile, since the thermal interaction of the successive layers has an influence on heat transfer mechanisms. The prediction of the temperature profile of an AM part is the building block for the prediction of the thermal stress, residual stress, part distortion, and microstructure evolution. Adding more details of the AM processes to the analytical models will help to increase the accuracy of the results. In this paper, the effect of time spacing (time delay between two irradiations) and hatch spacing on thermal material properties and melt pool geometry are studied. The effect of the number of scans on melt pool geometry is also investigated. The proposed model can be used to predict the temperature profile and melt pool geometry in laser-based metal additive manufacturing configurations of either direct metal deposition (DMD) or selective laser melting (SLM). In order to validate that the proposed model can capture the physical aspects of both powder bed systems, such as SLM, and powder feed systems, such as DMD, two sets of parts are chosen which are built using SLM and DMD processes and the predicted melt pool size is compared to experimental values.

Full Text
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