PDF(Pubmed)
Abstract：
Shielding gas, metal vapors, and gases trapped inside powders during atomization can result in gas porosity, which is known to degrade the fatigue strength and tensile properties of components made by laser powder bed fusion additive manufacturing. Post-processing and trial-and-error adjustment of processing conditions to reduce porosity are time-consuming and expensive. Here, we combined mechanistic modeling and experimental data analysis and proposed an easy-to-use, verifiable, dimensionless gas porosity index to mitigate pore formation. The results from the mechanistic model were rigorously tested against independent experimental data. It was found that the index can accurately predict the occurrence of porosity for commonly used alloys, including stainless steel 316, Ti-6Al-4V, Inconel 718, and AlSi10Mg, with an accuracy of 92%. In addition, experimental data showed that the amount of pores increased at a higher value of the index. Among the four alloys, AlSi10Mg was found to be the most susceptible to gas porosity, for which the value of the gas porosity index can be 5 to 10 times higher than those for the other alloys. Based on the results, a gas porosity map was constructed that can be used in practice for selecting appropriate sets of process variables to mitigate gas porosity without the need for empirical testing.
摘要：
屏蔽气体,金属蒸气,雾化过程中被困在粉末内部的气体会导致气体孔隙度，已知这会降低由激光粉末床熔融增材制造制成的部件的疲劳强度和拉伸性能。后处理和试错调整处理条件以降低孔隙率是耗时且昂贵的。这里,我们将机械建模和实验数据分析相结合，提出了一种易于使用的方法，可验证，无量纲气体孔隙度指数，以减轻孔隙形成。来自机械模型的结果针对独立的实验数据进行了严格的测试。发现该指标可以准确预测常用合金孔隙率的发生,包括不锈钢316，Ti-6Al-4V，铬镍铁合金718和AlSi10Mg，准确率为92%。此外,实验数据表明，孔的数量在较高的指标值增加。在四种合金中，发现AlSi10Mg最容易受到气体孔隙率的影响，气体孔隙率指数的值可以比其他合金高5到10倍。根据结果,构建了一个气体孔隙度图，该图可在实践中用于选择适当的过程变量集以减轻气体孔隙度，而无需进行经验测试。
