A Fatigue Life Prediction Method for Fiber-Reinforced Composite Laminates

doi:10.16183/j.cnki.jsjtu.2022.312

Abstract

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

CLC Number:

TB332

XU Rongxia, GAO Jianxiong, ZHU Pengnian, WU Zhifeng. A Fatigue Life Prediction Method for Fiber-Reinforced Composite Laminates[J]. Journal of Shanghai Jiao Tong University, 2024, 58(3): 400-410.

Figures/Tables 15

Tab.1

Tab.2

Precision comparison of different methods for fitting q-N function of [0]16 uni-directional plates

参数类型	拟合方法	函数表达式	相对误差/%
双参数	最小二乘法	q=-0.035ln N+1.189	63.16
	本文方法	q= $- 0.024 6 l n N + 1.094, 0.8 ≤ q < 1 - 0.078 8 l n N + 1.731, q < 0.8$	6.82
三参数	最小二乘法	q=(1.778×10^-5ln N+2.132)^-6.597	97.838
	本文方法	q= $- 0.024 6 l n N + 1.094, 0.8 ≤ q < 1 (- 0.074 9 l n N + 1.701) 1.090, q < 0.8$	6.684

Tab.2

Fig.1

Tab.3

Tab.4

Fig.2

Tab.5

Tab.6

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Tab.7

Tab.8

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q	N
0.90	2.50×10³
0.85	2.40×10⁴
0.80	1.43×10⁵
0.77	1.96×10⁵
0.70	4.57×10⁵

q	N
0.90	1.01×10³
0.80	3.48×10³
0.70	1.59×10⁵
0.60	>10⁶

q	N
0.85	229
0.80	398
0.70	3 350
0.60	2.48×10⁴
0.50	1.78×10⁵
0.40	>10⁶

不同预测方法	疲劳寿命	相对误差/%
文献[23]	236 757	1.612 4
文献[24]	236 768	1.617 2
文献[25]	2.32×10⁵	0.429 2
文献[26]	2.684×10⁵	15.193 1
本文方法	2.331 06×10⁵	0.004 5

不同预测方法	疲劳寿命	相对误差/%
文献[23]	130 800	81.233 9
文献[24]	130 950	81.212 3
文献[25]	2.03×10⁵	70.875 2
文献[26]	9.736×10⁴	86.031 6
本文方法	3.666 1×10⁵	47.401 7