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Surface and defect sensitive modelling of life in powder bed fusion produced Ti-6Al-4V
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Material Science.ORCID iD: 0000-0003-3828-2149
GKN Aerospace Sweden AB.
GKN Aerospace Sweden AB.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Material Science.ORCID iD: 0000-0001-5921-1935
2023 (English)Manuscript (preprint) (Other academic)
Abstract [en]

In this study a fatigue life model was developed and used to predict the fatigue life of electron beam powder bed fusion  Ti-6Al-4V specimens produced through powder bed fusion. To focus on the impact of surface quality, fatigue testing was carried out in four point bending fatigue on as-built, machined and chemically milled specimens. X-ray computed combined with extreme value statistics provided information about the distribution of internal defects near the surface and white light interferometry was used for surface roughness mesurements. Together the two methods provided input to a crack propagation fatigue life model. It was found that local information from high resolution XCT scans can improve model accuracy in capturing the effect of surface treatments. Together with surface roughness effects this information can be used to accurately capture general trends in fatigue behavior.

Place, publisher, year, edition, pages
2023.
Keywords [en]
Extreme Value Statistics, Defects, Fracture Mechanics
National Category
Other Materials Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-96280OAI: oai:DiVA.org:ltu-96280DiVA, id: diva2:1747756
Projects
SUDDEN
Funder
Vinnova, 2017-04846Available from: 2023-03-30 Created: 2023-03-30 Last updated: 2023-10-14
In thesis
1. Defects and Surfaces and their Impact on Fatigue Behaviour of Powder Bed Fused Ti-6Al-4V: Characteristics and Modelling
Open this publication in new window or tab >>Defects and Surfaces and their Impact on Fatigue Behaviour of Powder Bed Fused Ti-6Al-4V: Characteristics and Modelling
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Additive manufacturing (AM), of metals is gaining popularity as an alternative to conventional manufacturing techniques such as casting and forging. Metal-AM allows for the production of complex part geometries with reduced material waste and shorter lead times. The aerospace industry has been quick to adopt this technology; however, the fatigue performance of  metal-AM is a critical consideration for ensuring safety.

One of the challenges of AM metal is limited knowledge in its ability to withstand various loading conditions, from static loads to complex multiaxial thermo-mechanical fatigue loads. Defects in AM materials, such as rough surfaces, pores, and lack-of-fusion between build layers, act as local stress concentrators and crack initiation sites in the material. Some defects can be reduced through careful build process optimization and post-processing treatments, but it is generally not considered possible to eliminate all defects. Therefore, it is necessary to estimate the fatigue performance of AM-produced critical components containing defects.

The aim of the thesis is to investigate the relationship between defect characteristics and fatigue behaviour in AM-produced metal. The AM-material studied is electron beam powder bed fusion (EB-PBF) produced Ti-6Al-4V. Defect distributions, both on the surface and further inside the material, are statistically analysed and a simple fracture mechanical model for predicting fatigue life is developed. Post-production treatments, such as machining, chemical surface treatments and hot isostatic pressing (HIP), are also examined to determine their impact on defects and fatigue behaviour.

The thesis consists of six scientific papers. In the first three papers (1-3), fatigue behaviour and material characteristics are studied using mechanical testing and materials characterisation techniques such as optical microscopy, scanning electron microscopy, interferometry, and X-ray computed tomography (XCT). Internal defects are documented using XCT and compared with fatigue crack initiations (paper 1). Surface roughness and morphology of post-production treated EB-PBF material are analysed using interferometry and microscopy, and its connection to the surface near distribution of internal defects is examined (paper 2). Material that has been surface treated and subjected to Hot Isostatic Pressing (HIP) was tested in four-point bending fatigue followed by a fractographic study (paper 3).

The final three papers (4-6) of the thesis aim to take the material characteristics investigated in the first three papers as input for a crack-propagation-based fracture mechanics model to predict fatigue life using statistical analysis of the observed surface quality and defect distribution. These papers include modelling based on information about internal defects, as studied in the first paper, applied in a tension-compression cyclic load case (paper 4);  an exploration of surface morphology and four-point fatigue testing combined with surface adjacent XCT to use as input for a surface-sensitive fatigue life model (paper 5); and an estimation of the impact of surface machining depth on the material's fatigue behaviour using the experience gained from all previous work (paper 6).

It was found that the severity of the impact of a defect on the fatigue behaviour of the material largely depends on its characteristics and position relative to the surface. Production and post-processing of the material also play a role in the severity of this impact. The thesis also concludes that probabilistic statistical analysis can be used to accurately predict the life of the studied material under the conditions tested for.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2023
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords
Defects, Additive Manufacturing, Ti-6Al-4V, Probabilistic Modelling, Fatigue, Extreme Value Statistics
National Category
Metallurgy and Metallic Materials
Research subject
Engineering Materials
Identifiers
urn:nbn:se:ltu:diva-96282 (URN)978-91-8048-289-9 (ISBN)978-91-8048-290-5 (ISBN)
Public defence
2023-05-26, E632, Luleå tekniska universitet, Luleå, 08:30 (English)
Opponent
Supervisors
Projects
SUDDEN
Funder
Vinnova, 2017-04846
Available from: 2023-03-31 Created: 2023-03-31 Last updated: 2023-09-05Bibliographically approved

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