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Fatigue Characterization Under Effective Strain Damage Model on Various Road Load Conditions

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Abstract

The aim of this paper is to characterize the fatigue under various random strain loads that consider the effects of cycle sequence conditions. Due to the frequent exposure of fatigue damage to a leaf spring, the fatigue life calculation needs to consider a load cycle sequence effect. A finite element analysis is performed to determine the critical region on the leaf spring. In addition, the strain loads were experimentally captured under three different road load conditions, i.e., rural, campus, and highway, in order to obtain the strain load behavior under random data. The fatigue life predicted using an established strain-life model was 3.63 × 103 to 4.19 × 107 cycles/block, and the effective strain damage model was 1.04 × 105 to 1.75 × 106 cycles/block. The correlation fatigue life data show the data are within the 1:2 and 2:1 boundary condition with a high R2 value in a range of 0.9994–0.9998. It shows fatigue life data are highly correlated because they reflect the effects of cycle sequence. Hence, the effective strain damage model that considers the cycle sequence effect can provide an accurate fatigue life prediction compared to the traditional strain-life model under various road loads.

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Acknowledgments

The authors would like to express their gratitude to Universiti Kebangsaan Malaysia (Research funding: FRGS-1-2019-TK03-UKM-02-1 and DCP-2019-015 for supporting this research.

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Correspondence to S. S. K. Singh.

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This article is an invited paper selected from presentations at the 6th Symposium on Damage Mechanism in Materials and Structures (SDMMS 2022), held August 16–17, 2022 in Kuantan, Malaysia. The manuscript has been expanded from the original presentation. The special issue was organized by Nasrul Azuan Alang, Norhaida Ab Razak, and Aizat Alias, Universiti Malaysia Pahang.

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Abdullah, L., Singh, S.S.K., Abdullah, S. et al. Fatigue Characterization Under Effective Strain Damage Model on Various Road Load Conditions. J Fail. Anal. and Preven. 23, 529–539 (2023). https://doi.org/10.1007/s11668-023-01604-z

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  • DOI: https://doi.org/10.1007/s11668-023-01604-z

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