Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2024 , Vol. 58 >Issue 3: 400 - 410

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2022.312

Materials Science and Engineering

A Fatigue Life Prediction Method for Fiber-Reinforced Composite Laminates

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  • School of Mechanical Engineering, Xinjiang University, Urumqi 830017, China

Received date: 2022-08-15

  Revised date: 2022-09-28

  Accepted date: 2022-10-24

  Online published: 2024-03-28

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Abstract

To address the fatigue life prediction problem of fiber-reinforced composite laminates, a method for predicting fatigue life was proposed by closely combining theory and simulation, unidirectional board and multi-directional laminate. Based on the fatigue test data of several sets of carbon fiber/resin-based T300/QY8911 unidirectional plates under cyclic stress, the fatigue life model and damage function of unidirectional plates were established by using the GM(1, 1) model of the gray system. Compared with the traditional least squares method fitting, this method improves the prediction accuracy. Stress analysis, failure analysis and material degradation of laminates were performed by finite element methods. The results of the failure analysis were combined with the established fatigue life model and damage function of the unidirectional laminate to calculate the fatigue life and damage of the multidirectional laminate. A comparison of the experimental data and those of other prediction methods indicates the prediction method established reduces the relative error of fatigue life prediction and the results predicted is in good agreement with the experimental results.

Key words： carbon fiber composites; gray system; finite element analysis; multi-directional laminates; fatigue life

Cite this article

XU Rongxia, GAO Jianxiong, ZHU Pengnian, WU Zhifeng . A Fatigue Life Prediction Method for Fiber-Reinforced Composite Laminates[J]. Journal of Shanghai Jiaotong University, 2024 , 58(3) : 400 -410 . DOI: 10.16183/j.cnki.jsjtu.2022.312

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