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Multiple Linear Regression Parameters for Generating Fatigue-Based Entropy Characteristics of Magnesium Alloy

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Structural Integrity and Fatigue Failure Analysis (VCMF 2020)

Part of the book series: Structural Integrity ((STIN,volume 25))

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Abstract

This paper presents the development of a multiple linear regression based on stress ratio and applied load approach, assessed via thermodynamic entropy generation. Entropy generation as an early detection method that enables researchers to discover temperature evolution caused by dissipated plastic energy if the material experienced fatigue load. This relationship was developed through a complete entropy generation prediction using statistical approach, whereby a constant amplitude loading was applied to evaluate the fatigue life. By conducting compact tension tests, different stress ratios of 0.1, 0.4, and 0.7 were applied to the specimen. During the tests, temperature change was also observed. The highest entropy generation was 2.922 MJ m−3 K−1 when 2600 N load with a stress ratio of 0.7 was applied to the specimen. The assumptions of the models were considered through graphical residual analysis. As a result, the predicted regression model based on the applied load and stress ratio corresponded with the results of the experiment, deviating at only 4.6% from the actual experiment.

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Acknowledgements

The authors graciously acknowledge the financial support provided by Universiti Kebangsaan Malaysia (FRGS/1/2019/TK03/UKM/02/1) and Universiti Pertahanan Nasional (FRGS/1/2018/TK03/UPNM/03/1).

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Correspondence to S. Abdullah .

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Fauthan, M.A., Abdullah, S., Abdullah, M.F., Singh, S.S.K., Mohamed, I.F. (2022). Multiple Linear Regression Parameters for Generating Fatigue-Based Entropy Characteristics of Magnesium Alloy. In: Lesiuk, G., Szata, M., Blazejewski, W., Jesus, A.M.d., Correia, J.A. (eds) Structural Integrity and Fatigue Failure Analysis. VCMF 2020. Structural Integrity, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-030-91847-7_28

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  • DOI: https://doi.org/10.1007/978-3-030-91847-7_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91846-0

  • Online ISBN: 978-3-030-91847-7

  • eBook Packages: EngineeringEngineering (R0)

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