A Study on<i>P</i>-<i>S</i>-<i>N</i>Curve for Rotating Bending Fatigue Test for Bearing Steel
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Bibliographic record
Abstract
Abstract A study on the fatigue behavior of bearing steel by using rotating bending fatigue test rigs is carried out for bearing steel (JIS SUJ2 = AISI 52100) heat-treated to HRC58-62. Several P-S-N curves and fatigue life distributions, such as Weibull and log-normal, have been used for the discussion. As a result, the best fit for a life distribution of six lots each with a sample size of around 30 specimens, at stress levels from 0.94 GPa to 1.27 GPa, is obtained by the three-parameter Weibull distribution, followed by the lognormal distribution as second, and the two-parameter Weibull distribution as the third. The observation of the broken section of the test piece reveals that the initiation point of the failure is associated almost always with subsurface non-metallic inclusions. The fatigue limit could not be observed in the experimental results. It is also proposed that the relationship between the statistical life distributions of the test series and the P-S-N curve can be expressed by the same model as the life formula by introducing a rating stress such as bearing rating load in the three-parameter Weibull and log-normal distribution used. KEY WORDS: Bearing SteelFatigue TestFatigue LimitNon-Metallic InclusionsLinear BearingLog-Normal Distribution P-S-N CurveRotating BendingRating LoadRating StressStatistical AnalysisWeibull Distribution ACKNOWLEDGEMENT The author would like to thank Mr. K. Hiraoka and Mr. M. Nagao (Sanyo Tokushu Seiko Co. Ltd.) for their discussion and cooperation and Ms. A. Ando (graduated school student, now at NSK Co., Ltd.) for her earnest cooperation in the P-S-N test for this paper. The author would also like to extend his thanks to Dr. C. S. Sharma of THK Co., Ltd., for his discussions on this topic in completing this paper. This study is sponsored by the "High-Tech Research Center" Project for Private Universities: matching fund subsidy from MEXT (Ministry of Education, Culture, Sports, Science, and Technology), 2002–2006 under the leadership of Prof. S. Shimizu. We would also like to extend our thanks to related members of Meiji University for their kind cooperation. Presented at the STLE Annual Meeting in Calgary, Alberta, Canada May 7-11, 2006 Review led by Mike Hoeprich
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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