On a Decision Method of the S-N Curve Based on Fatigue Strength Distribution.
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- HANAKI Satoshi
- Dept. of Mech. Eng., Himeji Inst. of Tech.
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- IWAO Yasuhiro
- Himeji Inst. of Tech.
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- YAMASHITA Masato
- Dept. of Mech. Eng., Himeji Inst. of Tech.
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- UCHIDA Hitoshi
- Dept. of Mech. Eng., Himeji Inst. of Tech.
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- ZAKO Masaru
- Dept. of Manufacturing Sci., Osaka Univ.
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- KURASHIKI Tetsusei
- Dept. of Manufacturing Sci., Osaka Univ.
Bibliographic Information
- Other Title
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- 疲労強度分布に注目したS‐N線図の統計的決定法に関する研究
- ヒロウ キョウド ブンプ ニ チュウモク シタ S Nセンズ ノ トウケイテキ ケッテイホウ ニ カンスル ケンキュウ
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Abstract
Since the experimental results of fatigue test show large scatter, the S-N curve should be determined after the evaluation of them. In the previous paper, we have proposed a decision method for the S-N curve based on the fatigue strength distribution. In the proposed method, we have applied bilinear regression model for the data in the stress level around the fatigue limit. However, the S-N curves for some materials don't show obvious knee point. In this case, curved regression models such as hyperbola regression model are available. In this paper, we improve the proposed method to be applicable for such types of materials. In the developed method, 8 types of regression models, which are proposed by the committees on fatigue and reliability engineering in JSMS, are available, In addition, we can also decide the best-fitted model using the correlation for the plots of normalized fatigue strength on the probability paper, which are used for the evaluation of the fatigue strength distribution The proposed method has been applied to the fatigue test data for some materials. As a result, it is recognized that the reasonable S-N curves are obtained.
Journal
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- Journal of the Society of Materials Science, Japan
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Journal of the Society of Materials Science, Japan 52 (1), 23-27, 2003
The Society of Materials Science, Japan
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Details 詳細情報について
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- CRID
- 1390001205391453824
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- NII Article ID
- 110002301993
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- NII Book ID
- AN00096175
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- ISSN
- 18807488
- 05145163
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- NDL BIB ID
- 6433384
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed