PSI - Issue 53

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Author name / Structural Integrity Procedia 00 (2019) 000–000

João Alves et al. / Procedia Structural Integrity 53 (2024) 236–245 This is an open access article under the CC BY-NC-ND license ( https://creativecommons.org/licenses/by-nc-nd/4.0 ) Peer-review under responsibility of the scientific committee of the ESIAM23 chairpersons Keywords: Ti-6Al-4V; Additive Manufacturing; Selective Laser Melting; Life Prediction Modelos; Tomography

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1. Introduction The Ti-6Al-4V alloy, also known as TC4, is a material composed of 90% titanium, 6% aluminum, and 4% vanadium, which give it a unique combination of high fatigue strength, good creep behavior, low density, and excellent corrosion resistance, making it particularly desirable for applications demanding optimal performance under extreme conditions. Over the years, Ti-6Al-4V alloy has gained prominence in various industries such as aerospace, automotive, biomedical, and maritime due to its outstanding properties, which are far superior to many conventional materials (Froes, 2015). AM, specifically SLM, directly produces intricate, tailor-made, and highly functional components. Combined with advanced materials like the titanium alloy Ti-6Al-4V, it can revolutionize industries and push the boundaries of technological capabilities. However, adopting this new printing technology introduces novel properties and defects that can impact the fatigue behavior and, consequently, the durability of these components (Morgado et al., 2022). Considering this, it becomes crucial to comprehensively characterize the entire manufacturing process, starting from the raw materials and continuing through to the finished component. This approach is essential to understand how the mechanical behavior of Ti-6Al-4V may be influenced and, in turn, predict its performance. The main objective of this study is to develop a new model to predict the fatigue limit of Ti-6Al-4V produced by SLM. The investigation by which components fail is based on an intensive analysis of intrinsic SLM defects and their mechanical properties. It will also be performed a comparative study of the models proposed by Murakami (2002), Ueno et al. (2012), and Morgado et al. (2022).

Nomenclature area

area of the defect area ave area of the defect with a probability density of 50% area trans area of the defects, which is the transition between a small crack and a long crack area 0 critical area of defect calculated from Linear Elastic Fracture Mechanics b constant of the material calculated by the least squares method C constant of the material calculated by the least squares method h distance between internal defect and sample surface Hv Vickers Hardness N F number of cycles until failure P surf surface pressure P int internal pressure R stress ratio R s specimen fracture surfaces Y geometric factor α empirical factor dependent on the variable hardness ΔK th threshold stress intensity factor range Δσ W Fatigue thresholds for small cracks Δσ W0 Fatigue limit for smooth specimens