Grey Relational Grade Analysis between Vickers Hardness and Fatigue Crack Growth Data of 2024-T351 Aluminum Alloy

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Abstract:

Compact tension specimens cut from 2024-T351 aluminum-alloy plate were used for Vickers hardness tests under low-force scale and then for fatigue crack growth tests under sinusoidal loads, and the scattered data sets obtained including Vickers hardness, initiation cycle and specimen life, exponent m and intercept C of Paris-Erdogan law were collected as a factor set with five factor series for analysis of grey relational grade. Nominal value method was adopted for the preprocess referred to as grey relational generation to obtained new factor series, and then Hsia’s method was used to calculate the grey relational grades among new factor series. The analyzed result named global grey relational grade in matrix form with dimension of shows three main findings: (1) Vickers hardness has the largest influence on specimen life, and vice versa. (2) Vickers hardness, specimen life, and m have a large influence on each other. (3) C has the least influence on any other factors, and vice versa.

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Advanced Materials Research (Volumes 476-478)

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2435-2439

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February 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] W.D. Callister, JR.: Materials Science and Engineering an Introduction, John Wiley & Sons, New York (2003).

Google Scholar

[2] D.A. Virkler, B.M. Hillberry and P.K. Goel: The Statistic Nature of Fatigue Crack Propagation, ASME Journal of Engineering Materials and Technology, Vol. 101, (1979), pp.148-153.

DOI: 10.1115/1.3443666

Google Scholar

[3] H. Ghonem and S. Dore: Experimental Study of the Constant Probability Crack Growth Curves under Constant Amplitude Loading, Engineering Fracture Mechanics, Vol. 27 (1987), pp.1-27.

DOI: 10.1016/0013-7944(87)90002-6

Google Scholar

[4] J.L. Bogdanoff and F. Kozin: Probabilistic Models of Cumulative Damage, John Wiley & Sons, New York (1985).

Google Scholar

[5] Y.K. Lin and J.N. Yang: A Stochastic Theory of Fatigue Crack Propagation, AIAA Journal, Vol. 23 (1985), pp.117-124.

Google Scholar

[6] J.N. Yang and S.D. Manning: Stochastic Crack Growth Analysis Methodologies for Metallic Structures, Engineering Fracture Mechanics, Vol. 37 (1990), pp.1105-1124.

DOI: 10.1016/0013-7944(90)90032-c

Google Scholar

[7] W.F. Wu, and C.C. Ni: Probabilistic Models of Fatigue Crack Propagation and Their Experimental Verification, Probabilistic Engineering Mechanics Vol.19 (2004), pp.247-257.

DOI: 10.1016/j.probengmech.2004.02.008

Google Scholar

[8] W.F. Wu and C.C. Ni,: Statistical Aspects of Some Fatigue Crack Growth Data, Engineering Fracture Mechanics, Vol. 74 (2007), pp.2952-2963.

DOI: 10.1016/j.engfracmech.2006.08.019

Google Scholar

[9] J.L. Deng: Grey System-Theory and Applications, Gau-Lih Book Company, Taiwan (2003).

Google Scholar

[10] C.C. Wong, C.C. Chen and H.R. Lai: Grey System-Basic Methods and Applications, Gau-Lih Book Company, Taiwan (2001).

Google Scholar

[11] ASTM E647-91: Standard Test Method for Measurement of Fatigue Crack Growth Rates, American Society for Testing and Materials, Vol.03.01 (1991), pp.679-706.

Google Scholar