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多孔性对增材制造钛部件疲劳裂纹萌生的影响。

The Influence of Porosity on Fatigue Crack Initiation in Additively Manufactured Titanium Components.

机构信息

Department of Materials Science and Engineering, University of Sheffield, Sheffield, S1 3JD, UK.

School of Materials, University of Manchester, Manchester, M13 9PL, UK.

出版信息

Sci Rep. 2017 Aug 4;7(1):7308. doi: 10.1038/s41598-017-06504-5.

DOI:10.1038/s41598-017-06504-5
PMID:28779073
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5544733/
Abstract

Without post-manufacture HIPing the fatigue life of electron beam melting (EBM) additively manufactured parts is currently dominated by the presence of porosity, exhibiting large amounts of scatter. Here we have shown that the size and location of these defects is crucial in determining the fatigue life of EBM Ti-6Al-4V samples. X-ray computed tomography has been used to characterise all the pores in fatigue samples prior to testing and to follow the initiation and growth of fatigue cracks. This shows that the initiation stage comprises a large fraction of life (>70%). In these samples the initiating defect was often some way from being the largest (merely within the top 35% of large defects). Using various ranking strategies including a range of parameters, we found that when the proximity to the surface and the pore aspect ratio were included the actual initiating defect was within the top 3% of defects ranked most harmful. This lays the basis for considering how the deposition parameters can be optimised to ensure that the distribution of pores is tailored to the distribution of applied stresses in additively manufactured parts to maximise the fatigue life for a given loading cycle.

摘要

如果不对电子束熔化 (EBM) 增材制造零件进行制造后热等静压处理,其疲劳寿命目前主要受孔隙率的影响,表现出大量的分散性。在这里,我们已经表明,这些缺陷的大小和位置对于确定 EBM Ti-6Al-4V 样品的疲劳寿命至关重要。X 射线计算机断层扫描已用于在测试前对疲劳样品中的所有孔隙进行特征描述,并跟踪疲劳裂纹的萌生和扩展。这表明萌生阶段占寿命的很大一部分(>70%)。在这些样品中,萌生缺陷通常离最大缺陷有一定距离(仅在前 35%的大缺陷中)。使用各种排名策略,包括一系列参数,我们发现,当考虑到表面接近度和孔隙纵横比时,实际的萌生缺陷位于排名前 3%的最有害缺陷之列。这为考虑如何优化沉积参数奠定了基础,以确保孔隙的分布根据增材制造零件中应用的应力分布进行调整,从而在给定的加载循环中使疲劳寿命最大化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/449a2b34f5e5/41598_2017_6504_Fig10_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/9b5e243570f1/41598_2017_6504_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/449a2b34f5e5/41598_2017_6504_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/2206f4a81a18/41598_2017_6504_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/06562f3ab9c4/41598_2017_6504_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/4c4f8e3b93c1/41598_2017_6504_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/4db952c7d698/41598_2017_6504_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/10961af8f319/41598_2017_6504_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/75d81e104fdd/41598_2017_6504_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/bf91778f1fd8/41598_2017_6504_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/a1e7e9663f33/41598_2017_6504_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/9b5e243570f1/41598_2017_6504_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f52/5544733/449a2b34f5e5/41598_2017_6504_Fig10_HTML.jpg

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