A probabilistic SCG model for transverse cracking in CFRP cross-ply laminates under cyclic loading

Keiji Ogi, Shinji Ogihara, Shigeki Yashiro

研究成果: ジャーナルへの寄稿記事

2 引用 (Scopus)

抄録

This paper presents a probabilistic fatigue model for transverse cracking in CFRP cross-ply laminates. First, a delayed fracture model for a crack in a brittle material subjected to cyclic loading was established on the basis of the slow crack growth (SCG) concept in conjunction with the Weibull's probabilistic failure model. Second, the above probabilistic delayed fracture model was applied to transverse cracking in cross-ply laminates during cyclic loading. The stress distribution and the length of the unit element were calculated with the aid of a shear lag analysis. The transverse crack density was expressed as a function of maximum stress, stress ratio and number of cycles using the parameters associated with the Paris equation and the Weibull distribution in addition to the mechanical properties. Unknown parameters were determined from experiment data for three kinds of cross-ply laminates to reproduce the transverse crack density against the number of cycles. The parametric studies using the obtained parameters revealed the effects of the Weibull modulus, crack propagation exponent and stress ratio on evolution of transverse cracking under fatigue loading.

元の言語英語
ページ(範囲)1-17
ページ数17
ジャーナルAdvanced Composite Materials
19
発行部数1
DOI
出版物ステータス出版済み - 1 1 2010
外部発表Yes

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Carbon fiber reinforced plastics
Laminates
Crack propagation
Cracks
Fatigue of materials
Weibull distribution
Brittleness
Stress concentration
Mechanical properties
carbon fiber reinforced plastic
Experiments

All Science Journal Classification (ASJC) codes

  • Ceramics and Composites
  • Mechanics of Materials
  • Mechanical Engineering

これを引用

A probabilistic SCG model for transverse cracking in CFRP cross-ply laminates under cyclic loading. / Ogi, Keiji; Ogihara, Shinji; Yashiro, Shigeki.

:: Advanced Composite Materials, 巻 19, 番号 1, 01.01.2010, p. 1-17.

研究成果: ジャーナルへの寄稿記事

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