Abstract
A stub axle is a part of a vehicle constant-velocity system that transfers engine power from the transaxle to the wheels. The stub axle is subjected to fatigue failures due to cyclic loads arising from various driving conditions. The aim of this paper was to introduce a probabilistic framework for fatigue life reliability analysis that addresses uncertainties that appear in the mechanical properties. Service loads in terms of response-time history signal of a Belgian pave were replicated on a multi-axial spindle-coupled road simulator. The stress-life method was used to estimate the fatigue life of the component. A fatigue life probabilistic model of a stub axle was developed using Monte Carlo simulation where the stress range intercept and slope of the fatigue life curve were selected as random variables. Applying the goodness-of-fit analysis, lognormal was found to be the most suitable distribution for the fatigue life estimates. The fatigue life of the stub axle was found to have the highest reliability between 8000–9000 cycles. Because of uncertainties associated with the size effect and machining and manufacturing conditions, the method described in this paper can be effectively applied to determine the probability of failure for mass-produced parts.
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References
Bannantine, J. A., Comer J. J. and Handrock, J. L. (1989). Fundamentals of Metal Fatigue Analysis. Prentice Hall. New Jersey.
Booker, J. D., Raines, M. and Swift, K. G. (2001). Designing Capable and Reliable Product. Butterworth-Heinemann. New York.
Castillo, E., Lopez-Aenlle, M., Ramos, A., Fernandez-Cantelli, A., Kieselbach, R. and Esslinger, V. (2006). Specimen length effect of parameter estimation in modeling fatigue strength by Weibull distribution. Int. J. Fatigue 28,9, 1047–1058.
D’Agostino, R. B. and Stephens, M. A. (1986). Goodnessof- Fit Techniques. Marcel Dekker. New York.
Genet, G. (2006). A Statistical Approach to Multi-Input Equivalent Fatigue Loads for the Durability of Automotive Structures. Chalmers University of Technology and Goteborg University. Goteborg. Sweden.
Jun, K. J., Park, T. W., Lee, S. H., Jung, S. P. and Yoon, J. W. (2008). Prediction of fatigue life and estimation of its reliability on the parts of an air suspension system. Int. J. Automotive Technology 9,6, 741–747.
Melchers, R. E. (1999). Structural Reliability Analysis and Prediction. 2nd Edn. John Wiley & Sons. Chichester.
Pengelly, J. (2002). Monte Carlo Methods. University of Otago.
Schijve, J. (2005). Statistical distribution functions and fatigue of structures. Int. J. Fatigue 7,9, 1031–1039.
Stephens, R. I., Fatemi, A., Stephens, R. R. and Fuchs, H. O. (2001). Metal Fatigue in Engineering. 2nd Edn. Wiley Interscience. New York.
Sudret, B., Guede, Z., Hornet, P., Stephan, J. and Lemaire, M. (2003). Probabilistic assessment of fatigue life including statistical uncertainties in the SN curve. Trans. 17th Int. Conf. Structural Mechanics in Reactor Technology, Prague, Czech Republic.
Hovey, P. W., Berens, A. P. and Skinn, D. A. (1991). Risk analysis for aging aircraft. Flight Dynamic Directorate, 1, Wright Laboratory. Ohio.
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Asri, Y.M., Azrulhisham, E.A., Dzuraidah, A.W. et al. Fatigue life reliability prediction of a stub axle using Monte Carlo simulation. Int.J Automot. Technol. 12, 713–719 (2011). https://doi.org/10.1007/s12239-011-0083-z
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DOI: https://doi.org/10.1007/s12239-011-0083-z