Quantitative evaluation for influence of complex surface texture on fatigue limit reliability from mesocharacteristics (2nd report, method to predict fatigue limit reliability and its application to axisymmetric surface roughness)

Yuuta Aono, Hiroshi Noguchi, Hiroshi Hidaka, Takashi Hattori

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In this paper, a method to predict the fatigue limit reliability of specimens with various surface roughness is proposed. First, the mechanical profile for fatigue limit is proposed. This is obtained from the ineffective crack length. Then the equivalent notch depth is proposed to treat a rough surface as a smooth surface with a notch. Next, a method to predict the fatigue limit reliability is discussed. As the surface roughness is expressed with the spectrum analysis, computational simulation is used to produce surface profiles. And stress analysis described in the first report is carried out for each specimen. Then a fatigue limit of an arbitrary metal specimen with an arbitrary small notch can be estimated. Moreover, rotating bending fatigue tests of 0.1% carbon steel with a complex surface are carried out. Then the experimental fatigue limit data is compared with the present estimated values. As results, the validity of the present meso-analysis is examined.

Original languageEnglish
Pages (from-to)1186-1194
Number of pages9
JournalNippon Kikai Gakkai Ronbunshu, A Hen/Transactions of the Japan Society of Mechanical Engineers, Part A
Volume69
Issue number8
DOIs
Publication statusPublished - Aug 2003

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

Fingerprint

Dive into the research topics of 'Quantitative evaluation for influence of complex surface texture on fatigue limit reliability from mesocharacteristics (2nd report, method to predict fatigue limit reliability and its application to axisymmetric surface roughness)'. Together they form a unique fingerprint.

Cite this