Fatigue performance is often a key aspect when dealing with existing steel structures such as steel bridges or offshore constructions. This issue proves to be more critical as these structures are usually located in aggressive environments and are thus exposed to progressive degradation. Indeed, disruptive phenomena such as corrosion can severely worsen the fatigue performance of the steel components. Currently, the normative standards do not provide a codified procedure for the fatigue checks of steel structures subjected to ongoing corrosion. Within this framework, in this paper a simplified approach for the life-cycle assessment of corroded steel structures is proposed. For this purpose, the concept of "critical corrosion degree" is introduced, allowing the expression of corrosion fatigue checks in a more direct "demand vs. capacity" form with respect to the currently available methods. A first validation of such methodology is reported for the corrosion fatigue tests drawn from the literature. The predicted levels of critical corrosion are in good agreement with the values of artificially induced corrosion (i.e., 4, 8, and 12% of mass loss, respectively), with a maximum relative error of ≈9.3% for the most corroded specimen. Finally, parametrical analyses are performed, highlighting the influence of the model parameters on the corrosion fatigue performance of the steel elements.
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http://dx.doi.org/10.3390/ma15062210 | DOI Listing |
J Mech Behav Biomed Mater
December 2024
School and Hospital of Stomatology, China Medical University, Shenyang, 110001, Liaoning, China.
The medical devices are subjected to dynamic loads and surrounding physiological condition of the bodily fluids, which will impact the degradation behavior of magnesium (Mg) alloy implants. In this work, the corrosion fatigue (CF) and corrosion behaviors of Mg-xGa (x = 1, 1.5, and 2 wt%) alloys in Hank's balanced salt solutions (HBSS) with 1 g/L and 3 g/L glucose are thoroughly studied.
View Article and Find Full Text PDFMaterials (Basel)
December 2024
Hunan Tieyuan Civil Engineering Testing Co., Ltd., Changsha 410075, China.
Materials (Basel)
December 2024
School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
High-entropy alloys (HEAs) have drawn substantial attention on account of their outstanding properties. Additive manufacturing (AM), which has emerged as a successful approach for fabricating metallic materials, allows for the production of complex components based on three-dimensional (3D) computer-aided design (CAD) models. This paper reviews the advancements in the AM of HEAs, encompassing a variety of AM techniques, including selective laser melting (SLM), selective laser sintering (SLS), selective electron beam melting (SEBM), directed energy deposition (DED), binder jetting (BJT), direct ink writing (DIW), and additive friction stir deposition (AFSD).
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November 2024
Institute for Machine Tools, University of Stuttgart, Keplerstraße 7, 70174 Stuttgart, Germany.
The single-phase titanium ß-alloy Ti10V2Fe3Al (Ti-1023) has been widely used in the aerospace industry due to its unique mechanical properties, which include high fatigue strength and fracture toughness, as well as high corrosion resistance. On the other hand, these unique properties significantly hinder the cutting processes of this material, especially those characterized by a closed machining process area, such as drilling. This paper is devoted to the study of the short hole drilling process of the above-mentioned titanium alloy using direct measurements and numerical modeling.
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November 2024
Engineering Faculty, Mondragon Unibertsitatea, Loramendi 4, 20500 Arrasate-Mondragon, Spain.
Broaching is a key manufacturing process that directly influences the surface integrity of critical components, impacting their functional performance in sectors such as aeronautics, automotive, and energy. Such components are subjected to severe conditions, including high thermomechanical loads, fatigue, and corrosion. For this reason, the development of predictive models is essential for determining the optimal tool design and machining conditions to ensure proper in-service performance.
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