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Finite Element Based Durability Assessment of a Free Piston Linear Engine Component

M. M. Rahman1, A. K. Ariffin1, S. Abdullah1, N. Jamaludin1

1 Computational and Experimental Mechanics Group, Department of Mechanical and Materials Engineering, Universiti Kebangsaan Malaysia. 43600 UKM, Bangi, Selangor DE, Malaysia. Phone:+6(03)89216012; Fax: +6(03)89216040 E-mail: mustafiz@eng.ukm.my

Structural Durability & Health Monitoring 2007, 3(1), 1-14. https://doi.org/10.3970/sdhm.2007.003.001

Abstract

A modern computational approach based on finite element analysis for durability assessment in a two-stroke free piston linear engine component using the variable amplitude loadings is presented. This paper describes the finite element analysis techniques to predict the fatigue life and identify the critical locations of the component. The effect of mean stress on the fatigue life is also investigated. The finite element modeling and analysis has been performed using a computer-aided design and a finite element analysis software package, and the fatigue life prediction was carried out using finite element based fatigue life prediction codes. The fatigue crack initiation approach was utilizing to assess the durability of the component of the free piston linear engine. The acquired results utilizing the crack initiation approach indicate that when the loading sequences is predominantly tensile in nature (such as SAETRN loading), the SWT and the Morrow models give shorter life than that obtained using the Coffin-Manson model. However, the Coffin-Manson method gives conservative prediction when the time histories are predominantly compressive (SAESUS loading), and zero mean stress loadings (SAEBKT loading). The results are capable of showing the contour plots of the fatigue life histogram and damage histogram at the most critical location.

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Cite This Article

Rahman, M. M., Ariffin, A. K., Abdullah, S., Jamaludin, N. (2007). Finite Element Based Durability Assessment of a Free Piston Linear Engine Component. Structural Durability & Health Monitoring, 3(1), 1–14.



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