Article ID Journal Published Year Pages File Type
11003687 Optics & Laser Technology 2019 16 Pages PDF
Abstract
A physics-based process model of laser powder-fed additive manufacturing (LPF-AM), a class of directed energy deposition, is established in this paper. The model can perform an efficient prediction of the melt pool dimension, wetting angle, dilution, process heating/cooling rates and clad 3D profiles from single-track to multi-track and multi-layer deposition, and has the potential to be employed for the fast process optimization and controller design. The novelty of the model lies in three fronts: (1) the melt pool geometry variation as the liquid melt pool bead spreading on the solid surface is counted by the wetting angle alternation, in which the dynamic wetting angle is computed based on the Hoffman-Voinov-Tanner law; (2) the heat accumulation effect in the multi-track, multi-layer scanning is compensated by adding the accumulated temperature field to the initial temperature field of the following layers/tracks. The accumulated temperature is calculated by summing up the transient temperature solutions of the prior layers/tracks based on the superposition principle; and (3) the feeding powder distribution is incorporated into the transient thermal field simulation of the multi-layer and multi-track deposition process by analytically coupling the powder mass flows and laser heat flux, in which the powder mass flow is expressed as an equivalent heat flux. Experiments were conducted to validate the built model. The single-track measurements (clad height, clad width, dilution and wetting angle) show that the prediction error of the built model is less than 14%. The multi-track and multi-layer measurements also indicate that the model can perform a high accuracy dimension prediction of the built features. Besides, a sensitivity analysis was conducted based on the built model and the results show that the powder feed rate is the most sensitive parameter that substantially varies the clad height, followed by the process speed, whereas the specific heat has the least sensitivity.
Related Topics
Physical Sciences and Engineering Engineering Electrical and Electronic Engineering
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