Numerical investigation of production-related characteristics regarding their influence on the fatigue strength of additively manufactured components

• Autorzy: Zeißig Michaela , Jablonski Frank

Identyfikatory

DOI

10.2478/ama-2023-0033

• Języki publikacji: EN

Abstrakty

EN

In order to further enhance the application of additive manufacturing (AM) processes, such as the laser powder bed fusion (L-PBF) process, reliable material data are required. However, the resulting specimen properties are significantly influenced by the process parameters and may also vary depending on the material used. Therefore, the prediction of the final properties is difficult. In the following, the effect of residual stresses on the fatigue strength of 316L steel, a commonly used steel in AM, is investigated using a Weibull distribution. The underlying residual stress distributions as a result of the building process are approximated for two building directions using finite element (FE) models. These imply significantly different distributions of tensile and compressive residual stresses within the component. Apart from the residual stresses, the impact of the mean stress sensitivity is discussed as this also influences the predicted fatigue strength values.

Słowa kluczowe

EN

additive manufacturing; fatigue strength; Weibull distribution; FEM

• Wydawca: Oficyna Wydawnicza Politechniki Białostockiej
• Czasopismo: Acta Mechanica et Automatica
• Rocznik: 2023
• Tom: Vol. 17, no. 2
• Strony: 288--291
• Opis fizyczny: Bibliogr. 23 poz., rys., tab., wykr.

Twórcy

autor

Zeißig Michaela

• Faculty of Production Engineering, Bremen Institute for Mechanical Engineering (bime), University of Bremen, Am Biologischen Garten 2, 28359 Bremen, Germany

• https://orcid.org/0009-0001-8249-9495

autor

Jablonski Frank

• Faculty 5, City University of Applied Sciences Bremen, Neustadtswall 30, 28199 Bremen, Germany

• https://orcid.org/0000-0002-9670-0540

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).