Fatigue (S-N) data exhibit relatively large scatter. For design purposes, an S-N curve that characterizes fatigue strength is required. This curve should lie on the lower, or safe, side of the data. A method based on a modification of the Owen tolerance interval is proposed. The method is general and can be applied to nonlinear heteroscedastic data having runouts.

Issue Section:
Technical Papers
Topics:
Design, Fatigue strength, Electromagnetic scattering, Fatigue
1.
ASTM Committee E-9 on Fatigue, 1963, A Guide for Fatigue Testing and Statistical Analysis of Fatigue Data, Vol. STP 91-A, American Society for Testing and Materials, Philadelphia.
2.
ASTM, 1981, Statistical Analysis of Fatigue Data, R. E. Little and J. C. Eckvall, eds., Vol. STP 744, American Society for Testing and Materials, Philadelphia.
3.
ASTM Committee E-9 on Fatigue, 1991, Standard Practice for Statistical Analysis of Linear or Linearized Stress-Life (S-N) and Strain-Life (t-N) Fatigue Data, ASTM Standard E739-91, American Society for Testing and Materials, Philadelphia.
4.
Hinkle
A. J.
, and
Emptage
M. R.
,
1991
, “
Analysis of Fatigue Life Data Using the Box-Cox Transformation
,”
Fatigue Fract. Eng. Mat. Struc.
, Vol.
14
, pp.
591
–
600
.
5.
Johnson, L. G., 1964, The Statistical Treatment of Fatigue Experiments, Elsevier, New York.
6.
Langer
B. F.
,
1962
, “
Design of Pressure Vessels for Low Cycle Fatigue
,”
ASME Journal of Basic Engineering
, Vol.
84
, pp.
389
–
402
.
7.
Little, R. E., and Jebe, E. H., 1975, Statistical Design of Fatigue Experiments, Applied Science, London.
8.
Miller, R. G., 1981, Simultaneous Statistical Inference, 2nd ed., Springer-Verlag, New York.
9.
Montgomery, D. C, and Runger, G. C., 1994, Applied Statistics and Probability for Engineers, Wiley, New York.
10.
Natrella, M. G., 1963, Experimental Statistics, NBS Handbook 91, U.S. Govt. Printing Office, Washington, D.C.
11.
Nelson, W., 1982, Applied Life Data Analysis, Wiley, New York.
12.
Owen
D. B.
,
1968
, “
A Survey of Properties and Applications of the Noncentral r-Distribution
,”
Technometrics
, Vol.
10
, pp.
445
–
472
.
13.
Neter, J., Wasserman, W., and Kutner, M. H., 1990, Applied Linear Statistical Models, Richard D. Irwin, Inc., Homewood, IL.
14.
Schmee
J.
, and
Hahn
G. J.
,
1979
, “
A Simple Method for Regression Analysis with Censored Data
,”
Technometrics
, Vol.
21
, pp.
417
–
432
.
15.
Shen, C. L., 1994, “Statistical Analysis of Fatigue Data,” Ph.D. dissertation, The University of Arizona, Tucson.
16.
Shen, C. L., Wirsching, P. H., and Cashman, G. T., 1994, “An Advanced Comprehensive Model for the Statistical Analysis of S-N Fatigue Data,” ASME JOURNAL OF ENGINEERING MATERIALS AND TECHNOLOGY (submitted).
17.
SAE Fatigue Design and Evaluation Technical Committee, 1988, Fatigue Design Handbook, Society of Automotive Engineers, Warrendale, Pa.
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