Probabilistic mechanical properties of LZ50 axle steel for railway vehicles

ZHAO Yong-xiang; HUANG Yu-zhong; GAO Qing

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ZHAO Yong-xiang, HUANG Yu-zhong, GAO Qing. Probabilistic mechanical properties of LZ50 axle steel for railway vehicles[J]. Journal of Traffic and Transportation Engineering, 2003, 3(2): 11-17.

Citation:

ZHAO Yong-xiang, HUANG Yu-zhong, GAO Qing. Probabilistic mechanical properties of LZ50 axle steel for railway vehicles[J]. Journal of Traffic and Transportation Engineering, 2003, 3(2): 11-17.

ZHAO Yong-xiang, HUANG Yu-zhong, GAO Qing. Probabilistic mechanical properties of LZ50 axle steel for railway vehicles[J]. Journal of Traffic and Transportation Engineering, 2003, 3(2): 11-17.

Citation:

ZHAO Yong-xiang, HUANG Yu-zhong, GAO Qing. Probabilistic mechanical properties of LZ50 axle steel for railway vehicles[J]. Journal of Traffic and Transportation Engineering, 2003, 3(2): 11-17.

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Probabilistic mechanical properties of LZ50 axle steel for railway vehicles

1.
Institute of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
2.
Department of Applied Mechanics and Engineering, Southwest Jiaotong University, Chengdu 610031, China

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Author Bio:
ZHAO Yong-xiang (1963-), male, PhD, professor, 86-28-87602465, yxzhao@home.swjtu.edu.cn
Received Date: 2002-11-03
Publish Date: 2003-06-25

Abstract

Abstract

Experimental study on the probabilistic mechanical properties was performed on the LZ50 axle steel for railway vehicles.The unified approach for determining appropriate statistical models of the limited fatigue reliability data was developed to analyze the present test data.The six commonly used distributions, namely three parameter Weibull, two parameter Weibull, normal, lognormal, extreme maximum value, and extreme minimum value, were compared in fits of the data from the three considerations of goodness-of-fit, consistency of failure mechanism and safety in tail region predictions.From the viewpoint of safety, the extreme minimum value distribution was selected as an optimal model of the data.A method based on this distribution was proposed for the estimation of mechanical properties under given reliability and confidence levels.The method has been well used for the estimation of probabilistic parameters of the mechanical properties of the present material.
- railway vehicle,
- axle,
- LZ50 steel,
- mechanical properties,
- reliability,
- lognormal distribution

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References(20)

References

[1]	FreudenthalA M. Safety of structure[J]. Trans. ASCE, 1947, 112: 125—128.
[2]	FreudenthalA M. Physical and statistical aspects of fatigue[J]. Adv. Appl. Mech., 1956, 4: 116—156.
[3]	KecociogluD. Reliability analysis of mechanical componentsand systems[J]. Nucl. Eng. Des., 1972, 19: 259—290.
[4]	HaugenE B. Probabilistic Mechanical Design[M]. NewYork: JohnWiley andSons, 1980.
[5]	Proven J W. Probability Fracture Mechanics and Reliability [M]. Dordrecht: Martnus Nijhoff Publishers, 1987.
[6]	TB/T 1335-1996, 铁道车辆强度设计及试验鉴定规范[S].
[7]	XIAO Ji-mei. Som e comparison between steels50 and40 usedfor railroad axles[J]. Transactions onMaterials, 2000, 14(6): 7—8. (inChinese).
[8]	ZHONG Qun-peng. The views on carbon steel40 and50 forthe vehicle shaft[J]. Transactions onMaterials, 2000, 14(6): 9—10. (inChinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CLDB200006005.htm
[9]	MencikJ. Reliability assessment with small amount of experi-mental data[R]. InStructuralSafety andReliability: ICOSSAR'01.187—194.
[10]	ZHAO Yong-xiang. Short fatigue crack behavior and reliability analysis in low cycle fatigue[D]. Chengdu: Southwest Jiaotong University, 1998. (in Chinese)
[11]	Tanaka T, Sakai T, Iwaya T. Distribution characteristics of fatigue lives and fatigue strengths of ferrous metals by the analysis of P-N data in the JSMEdata base on fatigue strength of metallic materials[A]. In Statistical Research on Fatigue and Fracture[C]. London: Elsevier Applied Science Publishers, 1987.125-157.
[12]	Baldwin JD, Thacker JG. Astrain -based fatigue reliability analysis method[J]. ASME Journal of Mechanical Design, 1995, 117: 229-234.
[13]	The Committee on Fatigue and Fracture Reliability of the Co-mmittee on Structural Safety and Reliability of the Structural Division. Fatigue reliability: introduction[J]. J. Struct. Div. Proc. ASCE, 1982, 108(ST1): 3-23.
[14]	ZHAO Yong-xiang, SUN Ya-fang, GAO Qing. Unified linear regression method for the analysis of seven commonly used statistical distributions[J]. J. Mech. Strength, 2001, 23(1): 102-106. (in Chinese). doi: 10.3321/j.issn:1001-9669.2001.01.028
[15]	Zhao Y X, Gao Q, Wang J N. An approach for determining an appropriate assumed distribution of fatigue life under limited data[J]. Reliab. Eng. Sys. Saf., 2000, 67(1): 1-7. doi: 10.1016/S0951-8320(99)00039-3
[16]	Zhao Y X, Gao Q, Sun X F. A statistical investigation of the fatigue lives of Q235 steel-welded joints[J]. Fatigue Fract. Eng. Mater. Struct., 1998, 21: 781-790.
[17]	Zhao YX, Wang JN, Gao Q. Random cyclic stress-strain resp- onses of a stainless steel pipe-weld metal I-a statistical investigation[J]. Nucl. Eng. Des., 2000, 199: 303-314.
[18]	Zhao YX, Wang JN, Gao Q. Statistical evolution of small fatigue crack in 1Cr18Ni9Ti weld metal[J]. Theor. Appl. Fract. Mech., 1999, 32: 55-64.
[19]	Zhao Y X. Size evolution of the surface short fatigue cracks of 1Cr18Ni9Ti pipe-weld metal with a local viewpoint[J]. Mater. Sci. Eng. A, 2003, 344: 229-239.
[20]	ZHAO Yongxiang, WANG Jinnuo, GAO Qing. Unified approach for determining an appropriate assumed distribution of limited fatigue reliability data[J]. Journal of China Mech. Eng., 2001, 12(12): 1 343-1 347. (in Chinese) doi: 10.3321/j.issn:1004-132X.2001.12.005