Icm11 Paper in Proceeding

Topics: Tensile strength, Elasticity, Fatigue Pages: 10 (2986 words) Published: May 13, 2013
Available online at www.sciencedirect.com Available online at www.sciencedirect.com

Procedia Engineering 10 (2011) 1232–1237 Procedia Engineering 00 (2011) 000–000

Procedia Engineering


Statistic characteristics of fatigue properties in magnesium alloy S. Mohda,c, *, Y. Otsukab, Y. Miyashitab, Y. Mutohb

Department of Materials Science, Nagaoka University of Technology, 1603-1 Kamitomioka, Nagaoka 940-2188, Japan b Department of System Safety, Nagaoka Universty of Technology, 1603-1 Kamitomioka, Nagaoka 940-2188, Japan c Department of Aeronautical Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia

Abstract The knowledge of statistic characteristics in mechanical properties is important for designers in order to assess the reliability of structures. Scatter characteristics of fatigue limit, fatigue life and tensile strength for magnesium alloy were investigated in this study. At least 20 specimens were tested to obtain the scatter data of fatigue limit, fatigue life and tensile strength, respectively. The probability distributions of fatigue limit, fatigue life and tensile strength were evaluated by using Normal distribution and Weibull distribution function. The values of the Weibull modulus, m were 159, 10, 175 for fatigue limit, fatigue life and tensile strength, respectively. Therefore, it can be concluded that scatter of fatigue limit is small and almost coincides with that of tensile strength, while scatter of fatigue life is significantly large compared to those of fatigue limit and tensile strength. The large scatter of fatigue life will be due to crack nucleation and small crack growth processes, which strongly depend on local microstructure near the crack nucleation region.

© 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of ICM11 Keywords: Scatter characteristics; fatigue limit; fatigue life; Normal distribution; Weibull distribution

1. Introduction Statistical properties of fatigue behavior have been recognized as one of the important information required for reliable design of machines and structures that experience variable loads during operation. Many research works have been conducted to evaluate the fundamental statistical behavior of fatigue and

* Corresponding author. Tel.: +8-125-847-9735; fax: +8-125-847-9770. E-mail address: sofian@uthm.edu.my.

1877–7058 © 2011 Published by Elsevier Ltd. doi:10.1016/j.proeng.2011.04.205


S. Mohd et al. / Procedia Engineering 10 (2011) 1232–1237 S. Mohd et al./ Procedia Engineering 00 (2011) 000–000


tensile properties, which have resulted in the development of various statistical approaches to laboratory data. Studies on scatter in fatigue life have received great attention by many researchers. For example, J. Schijve [1] evaluated the fatigue life data using three distribution functions i.e. log(N) Normal distribution, 3-parameter Weibull distribution and 3-parameter log(N-No) distribution. M.T. Todinov [2,3], P.J. Lazt and B.M. Hillberry [4] and J.Z. Yi et al. [5,6] were developed various probabilistic models for predicting fatigue life based on the probability distribution of either defect size or inclusion size. S. Nishijima [7] investigated statistical fatigue properties of steels for machine structural application. He reported that fatigue strength of the materials followed a normal distribution, as did their Vickers hardness. The fatigue strength variation represented by coefficient of variation, COV, increased with an increase in hardness. However, there have been no reports on statistical characteristics of fatigue limit. In the present study, scatter behavior of fatigue limit and tensile strength of extruded AZ61 magnesium alloy was investigated. Difference of scatter behavior between fatigue limit and fatigue life, which was referred from the previous work [8], was discussed. The scatter indexes represented...

References: [1] Schijve J. Int J Fatigue 2005;27(9):1031-9. [2] Todinov MT. Mater Sci Engng A 1988;255(1-2):117–23. [3] Todinov MT. Computers and Structures 2001;79(3):313-8. [4] Laz PJ, Hillberry BM. Int J Fatigue 1998;20(4):263-70. [5] Yi JZ, Lee PD, Lindley TC, Fukui T. Mater Sci Engng A 2006;432(1-2):59-68. [6] Yi JZ, Gao YX, Lee PD, Flower HM, Lindley TC. Metall. Mater. Trans. A 2003;34(9):1879-90. [7] Nishijima S. Statistical analysis of fatigue data, ASTM STP 744, In: Little RE, Ekvall JC, Eds..American Society for Testing and Materials;1981, p.75-88. [8] S. Mohd, Y. Mutoh, Y. Otsuka, Y. Miyashita. In: Proc. of 47th JSME General Congress Hokuriku Shinetsu Branch;2010,p.159-60. [9] JIS Z2273. General rules for fatigue testing of metals. 1978 [10] ASTM E466-76. Standard recommended practice for constant axial fatigue tests of metallic materials, 1977;10:536-540 [11] Bomas H, Mayr P, Schleicher M. Mater Sci Engng A 1997;234-236:393-6. [12] Zheng X, Wei J. Int J Fatigue 2005;27(6):601-609. [13] Schijve J. Fatigue of Structures and Materials. 2nd ed.: Springer;2008, p.14-32.
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