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Accession number:
20141617576239
Title:
S-N Curve Modeling for Finite Life Range under the Assumption of Linearly Changing Scatter
Authors:
Yingjie, Zhou1 ; Xuezhi, Tang2
Author affiliation:
1Schaeffler Holding (China) Co., Ltd., China
2Schaeffler Trading (Shanghai) Co., Ltd., China
Corresponding author:
Yingjie, Z. (zhouyji@schaeffler.com)
Source title:
SAE International Journal of Materials and Manufacturing
Abbreviated source title:
SAE Int. J. Mater. Manuf.
Volume:
7
Issue:
2
Issue date:
April 2014
Publication year:
2014
Pages:
454-464
Language:
English
ISSN:
19463979
E-ISSN:
19463987
Document type:
Journal article (JA)
Publisher:
SAE International
Abstract:
Fatigue test data in finite life region are normally analyzed separately for each stress level because of varying scatters, while another method assuming equal scatters on all levels and thus unifying all data into one model is also welcome for its efficient usage of data. Combining the idea of the two methods, a new method that assumes linear change of scatter according to stress levels is developed in this paper. The algorithm derives from maximum likelihood estimation and general Newton's method. Monte Carlo method is used for theoretical validation and the new method is proved to be correct with the estimations. Finally a set of test data which shows a tendency of trapezoidal data distribution is analyzed and an S-N curve for finite life range is created. The new method has its advantage in certain situations so it's meaningful to add it to the alternatives of fatigue data analysis methods. Copyright © 2014 SAE International.
Number of references:
14
Main heading:
Maximum likelihood estimation
Controlled terms:
Fatigue testing - Monte Carlo methods - Newton-Raphson method
Uncontrolled terms:
Data distribution - Fatigue data - Newton's methods - S-N curve - Stress levels - Test data - Theoretical validations
Classification code:
422.2 Strength of Building Materials : Test Methods - 921.6 Numerical Methods - 922 Statistical Methods - 922.2 Mathematical Statistics
DOI:
10.4271/2014-01-0970
Database:
Compendex
Compilation and indexing terms, © 2015 Elsevier Inc |
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