Static assessment of flawed thin AlSi10Mg parts produced by Laser Powder Bed Fusion

被引:3
作者
Minerva, G. [1 ]
Patriarca, L. [1 ]
Foletti, S. [1 ]
Beretta, S. [1 ]
机构
[1] Politecn Milan, Dept Mech Engn, via La Masa 1, I-20156 Milan, Italy
关键词
Laser Powder Bed Fusion; AlSi10Mg; Fracture toughness; Mechanical properties; Failure Assessment Diagram; Building orientation; MECHANICAL-PROPERTIES; PROCESS OPTIMIZATION; MICROSTRUCTURE; FATIGUE; DEFECTS; STRESS; ALLOYS; SLM;
D O I
10.1016/j.matdes.2022.111292
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Several factors must be considered within the assessment of parts produced by Additive Manufacturing (AM) such as, for example, heterogeneous microstructure, process-induced defects, surface quality, residual stresses, and dependence on the material's properties with the building orientation. All these factors severely affect the resistance to static and fatigue loadings of AMed components. Among the possible failure mechanisms, the failure promoted by static loadings when cracks are present is one of the most important failure conditions, in particular for the as-built parts, which might have reduced fracture toughness and ductility compared to the wrought alloy counterpart. In this work, we present a comprehensive approach to the static assessment of AlSi10Mg parts manufactured by Laser Powder Bed Fusion. Two benchmark fracture geometries were designed to investigate the typical AM geometrical features: i) thin walls in tension and ii) notched components in bending. Finite Element analyses of the benchmark specimens showed that an approach based on elastic-plastic fracture mechanics parameters is needed to correctly predict the experimental failures, despite the quasi-brittle behaviour shown by the AlSi10Mg alloy. In view of these results, this paper explores the applicability of the Failure Assessment Diagram (FAD), a tool used for conventional ductile materials, to static assessment of AMed parts. The results show that the assessment approach based on the FAD makes it possible to properly predict the experimental failures of the benchmark specimens.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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页数:20
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