2018
DOI: 10.1111/ffe.12799
|View full text |Cite
|
Sign up to set email alerts
|

Fatigue life prediction of additively manufactured material: Effects of surface roughness, defect size, and shape

Abstract: In this paper, the effects of process‐induced voids and surface roughness on the fatigue life of an additively manufactured material are investigated using a crack closure‐based fatigue crack growth model. Among different sources of damage under cyclic loadings, fatigue because of cracks originated from voids and surface discontinuities is the most life‐limiting failure mechanism in the parts fabricated via powder‐based metal additive manufacturing (AM). Hence, having the ability to predict the fatigue behavio… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
5

Citation Types

4
72
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
7
1

Relationship

1
7

Authors

Journals

citations
Cited by 182 publications
(76 citation statements)
references
References 37 publications
4
72
0
Order By: Relevance
“…2,8,12 When the residual stresses in an AM part are limited and the microstructure is nearly homogeneous-for instance, by postfabrication heat treatments or preheating the build plate-defect characteristics (ie, size, shape, location, and distribution) are the main factor affecting the fatigue performance. [20][21][22][23] Thus, being able to predict the fatigue resistance of AM parts from defect characteristics can address the issue of uncertainty. This can significantly decrease the time and cost for the development of new products via AM.…”
Section: Introductionmentioning
confidence: 99%
“…2,8,12 When the residual stresses in an AM part are limited and the microstructure is nearly homogeneous-for instance, by postfabrication heat treatments or preheating the build plate-defect characteristics (ie, size, shape, location, and distribution) are the main factor affecting the fatigue performance. [20][21][22][23] Thus, being able to predict the fatigue resistance of AM parts from defect characteristics can address the issue of uncertainty. This can significantly decrease the time and cost for the development of new products via AM.…”
Section: Introductionmentioning
confidence: 99%
“…It is well known that small defects, eg, scratches, cavities, and non‐metallic inclusions, can degrade the fatigue life and fatigue limit of various steels and other metallic materials depending on the shape and size. In addition, for Ni‐based superalloys, some researchers have reported the detrimental effect of small defects on the fatigue strength . For example, Yadollahi et al conducted fatigue tests of two types of AMed Alloy 718 specimens with different defect sizes, ie, specimens containing defects due to a lack of fusion ( defective build specimens ) and specimens in which such defects were reduced ( nondefective build specimens ).…”
Section: Introductionmentioning
confidence: 99%
“…There are several studies on estimating the fatigue life of AM components based on internal and external defects . Romano et al proposed a model based on internal defects to predict both low‐cycle and high‐cycle fatigue in AlSi10Mg, based on assumptions regarding defect size, geometry, and occurrence.…”
Section: Introductionmentioning
confidence: 99%
“…Romano et al proposed a model based on internal defects to predict both low‐cycle and high‐cycle fatigue in AlSi10Mg, based on assumptions regarding defect size, geometry, and occurrence. Yadollahi et al applied a similar method to describe the effect of surface texture and defect features on the fatigue life of Inconel 718. The latter article suggested using the maximum valley depth of the surface profile ( R v ) as the initial crack length for fatigue life modelling.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation