Weibull Statistical Analysis of Krouse Type Bending Fatigue of Nuclear Materials
Abstract
A bending fatigue mini-specimen (Krouse-type) was used to study the fatigue properties of nuclear materials. The objective of this paper is to study fatigue for Grade 91 ferritic-martensitic steel using a mini-specimen (Krouse-type) suitable for reactor irradiation studies. These mini-specimens are similar in design (but smaller) to those described in the ASTM B593 standard. The mini specimen was machined by waterjet and tested as-received. The bending fatigue machine was modified to test the mini-specimen with a specially designed adapter. The cycle bending fatigue behavior of Grade 91 was studied under constant deflection. The S-N curve was created and mean fatigue life was analyzed using mean fatigue life. In this study, the Weibull function was predicted probably for high stress to low stress at 563, 310 and 265 MPa. The commercial software Minitab 17 was used to calculate the distribution of fatigue life under different stress levels. We have used 2 and 3- parameters Weibull analysis to introduce the probability of failure. The plots indicated that the 3- parameter Weibull distribution fits the data well.
Recommended Citation
A. S. Haidyrah et al., "Weibull Statistical Analysis of Krouse Type Bending Fatigue of Nuclear Materials," Journal of Nuclear Materials, vol. 470, pp. 244 - 250, Elsevier, Mar 2016.
The definitive version is available at https://doi.org/10.1016/j.jnucmat.2015.12.016
Department(s)
Materials Science and Engineering
Second Department
Nuclear Engineering and Radiation Science
Keywords and Phrases
Fatigue of Materials; Fatigue Testing; Ferritic Steel; Martensitic Steel; Radioactive Materials; Bending Fatigue; Bending Fatigue Tests; Krouse; Mean Life; MINITAB; S-N Curve; Weibull Distribution; Bending Fatigue Mini Specimen; Bending Fatigue Test; Krouse; Mean Life; Minitab 17; S-N Curve; Weibull Distribution
International Standard Serial Number (ISSN)
0022-3115
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2016 Elsevier, All rights reserved.
Publication Date
01 Mar 2016