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利用实验数据分析和机理建模减轻增材制造中的气孔缺陷

Mitigation of Gas Porosity in Additive Manufacturing Using Experimental Data Analysis and Mechanistic Modeling.

作者信息

Sinha Satyaki, Mukherjee Tuhin

机构信息

Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA.

出版信息

Materials (Basel). 2024 Mar 29;17(7):1569. doi: 10.3390/ma17071569.

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

雾化过程中,保护气体、金属蒸汽以及被困在粉末内部的气体会导致气孔形成,众所周知,这会降低激光粉末床熔融增材制造部件的疲劳强度和拉伸性能。通过后处理以及反复调整工艺条件来减少气孔既耗时又昂贵。在此,我们将机理建模与实验数据分析相结合,提出了一种易于使用、可验证的无量纲气孔率指数,以减轻气孔的形成。针对独立的实验数据,对机理模型的结果进行了严格测试。结果发现,该指数能够准确预测包括316不锈钢、Ti-6Al-4V、因科镍合金718和AlSi10Mg在内的常用合金中气孔的出现情况,准确率达92%。此外,实验数据表明,指数值越高,气孔数量越多。在这四种合金中,AlSi10Mg被发现最易产生气孔,其气孔率指数值可能比其他合金高出5至10倍。基于这些结果,构建了一张气孔率图,可在实际应用中用于选择合适的工艺变量集,以减轻气孔问题,而无需进行经验测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42c4/11013015/1a90e0ae738f/materials-17-01569-g001.jpg

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