Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method / Matthias Oberreiter ... [et al.]
This research is devoted to analyze the stress state and fatigue strength of two specimens made by a newly developed high-strength aluminium alloy produced by the wire arc additive manufacturing (WAAM) process. The relationship between fatigue strength and flaw size was calculated based on the root...
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Smart Manufacturing Research Institute (SMRI)
2023
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my.uitm.ir.860122023-10-29T14:02:38Z https://ir.uitm.edu.my/id/eprint/86012/ Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method / Matthias Oberreiter ... [et al.] jaeds Oberreiter, Matthias Nik Norzainal Abidin, Nik Nur Khaleeda Stoschka, Michael Manurung, Yupiter HP Adenan, Mohd Shahriman Krishnamoorthy, Renga Rao Aluminum This research is devoted to analyze the stress state and fatigue strength of two specimens made by a newly developed high-strength aluminium alloy produced by the wire arc additive manufacturing (WAAM) process. The relationship between fatigue strength and flaw size was calculated based on the root squared area – a parameter by conventional Murakami’s equation which is a widely used analytical approach for predicting fatigue resistance in metallic materials. The research involves the metallographic preparation process on two aluminum alloy labeled HS-Al-A and HS-Al-B followed by Vickers hardness measurement. Further, the image of the observed pores was processed and dimensioned using an open-sourced software ImageJ by considering pixels and actual distance as well as by defining image threshold value for measuring pore sizes. The analytical approach is conducted in order to describe the maximum stress intensity factor Kmax at the crack front and to assess the fatigue strength σFS. As final results, specimen A has an average pore area of ≈65 µm with Kmax of 333.75 MPa∙√m and σFS of 137 MPa, while specimen B has an average pore area of ≈42 µm with Kmax of 325.13 MPa∙√m and σFS of 153 MPa. Overall, this research allows the formulation of a method for estimating fatigue strength of large defects leading to a conclusion that flaws can influence the fatigue resistance of the material so that the bigger the flaw size is, the lower σFS and the higher the Kmax. Smart Manufacturing Research Institute (SMRI) 2023-09 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/86012/1/86012.pdf Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method / Matthias Oberreiter ... [et al.]. (2023) Journal of Applied Engineering Design & Simulation (JAEDS) <https://ir.uitm.edu.my/view/publication/Journal_of_Applied_Engineering_Design_=26_Simulation_=28JAEDS=29/>, 3 (2): 1. pp. 1-14. ISSN 2805-5756 |
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Aluminum Oberreiter, Matthias Nik Norzainal Abidin, Nik Nur Khaleeda Stoschka, Michael Manurung, Yupiter HP Adenan, Mohd Shahriman Krishnamoorthy, Renga Rao Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method / Matthias Oberreiter ... [et al.] |
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This research is devoted to analyze the stress state and fatigue strength of two specimens made by a newly developed high-strength aluminium alloy produced by the wire arc additive manufacturing (WAAM) process. The relationship between fatigue strength and flaw size was calculated based on the root squared area – a parameter by conventional Murakami’s equation which is a widely used analytical approach for predicting fatigue resistance in metallic materials. The research involves the metallographic preparation process on two aluminum alloy labeled HS-Al-A and HS-Al-B followed by Vickers hardness measurement. Further, the image of the observed pores was processed and dimensioned using an open-sourced software ImageJ by considering pixels and actual distance as well as by defining image threshold value for measuring pore sizes. The analytical approach is conducted in order to describe the maximum stress intensity factor Kmax at the crack front and to assess the fatigue strength σFS. As final results, specimen A has an average pore area of ≈65 µm with Kmax of 333.75 MPa∙√m and σFS of 137 MPa, while specimen B has an average pore area of ≈42 µm with Kmax of 325.13 MPa∙√m and σFS of 153 MPa. Overall, this research allows the formulation of a method for estimating fatigue strength of large defects leading to a conclusion that flaws can influence the fatigue resistance of the material so that the bigger the flaw size is, the lower σFS and the higher the Kmax. |
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Article |
author |
Oberreiter, Matthias Nik Norzainal Abidin, Nik Nur Khaleeda Stoschka, Michael Manurung, Yupiter HP Adenan, Mohd Shahriman Krishnamoorthy, Renga Rao |
author_facet |
Oberreiter, Matthias Nik Norzainal Abidin, Nik Nur Khaleeda Stoschka, Michael Manurung, Yupiter HP Adenan, Mohd Shahriman Krishnamoorthy, Renga Rao |
author_sort |
Oberreiter, Matthias |
title |
Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method / Matthias Oberreiter ... [et al.] |
title_short |
Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method / Matthias Oberreiter ... [et al.] |
title_full |
Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method / Matthias Oberreiter ... [et al.] |
title_fullStr |
Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method / Matthias Oberreiter ... [et al.] |
title_full_unstemmed |
Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method / Matthias Oberreiter ... [et al.] |
title_sort |
analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on murakami method / matthias oberreiter ... [et al.] |
publisher |
Smart Manufacturing Research Institute (SMRI) |
publishDate |
2023 |
url |
https://ir.uitm.edu.my/id/eprint/86012/1/86012.pdf https://ir.uitm.edu.my/id/eprint/86012/ |
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1781709344345161728 |