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Research Papers

Prediction of Remaining Fatigue Cycles in Composite Materials Under Uncertainty

[+] Author and Article Information
Saeed Shiri

Department of Mechanical Engineering,
Sahand University of Technology,
Tabriz 51335, Iran
e-mail: sshiri1392@gmail.com

Mohammad Pourgol-Mohammad

Department of Mechanical Engineering,
Sahand University of Technology,
Tabriz 51335, Iran
e-mail: pourgol-mohamadm2@asme.org

Mojtaba Yazdani

Department of Mechanical Engineering,
Sahand University of Technology,
Tabriz 51335, Iran
e-mail: m.yazdani.sut@gmail.com

1Corresponding author.

Manuscript received March 5, 2015; final manuscript received June 12, 2015; published online November 20, 2015. Assoc. Editor: Chimba Mkandawire.

ASME J. Risk Uncertainty Part B 2(1), 011001 (Nov 20, 2015) (6 pages) Paper No: RISK-15-1040; doi: 10.1115/1.4031037 History: Received March 05, 2015; Accepted July 07, 2015

In this paper, a stiffness-based model is initially assessed for fatigue damage simulation of composite materials. The model is evaluated with three sets of experimental data. A residual strength model is coupled to the choice model and a modified model is developed. Numerical results show that the modified model leads to a noticeable improvement of accuracy in fatigue life prediction of composites under two-stage loadings. In the second step of the research, an uncertainty analysis is conducted to evaluate the reliability of the achieved results. The fatigue life and strength are assumed as random variables and uncertainty analysis is done by the Monte Carlo (MC) approach. Reliability variations of predicted residual fatigue lives are studied as well. The results demonstrate that the fatigue life dispersion noticeably decreases the reliability of predicted remaining fatigue cycles.

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References

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Figures

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Fig. 1

Sketch of fatigue damage development [1]

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Fig. 2

Damage evolution curves of various composites under different loadings: (a) [±45]7 laminates, (b) [0/90]7 laminates, and (c) [0/±60] laminates

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Fig. 3

Weibull distribution to the histogram of predicted residual fatigue lives for E-glass/epoxy laminates [20]: (a) Low-high loading sequence and (b) high-low loading sequence

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Fig. 4

Weibull distribution to the histogram of predicted residual fatigue lives for carbon/epoxy laminates [21]: (a) Low-high loading sequence and (b) high-low loading sequence

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Fig. 5

Reliability variation of predicted residual fatigue lives for E-glass/epoxy laminates [20]: (a) σ1=241, σ2=289, n1=49,950 and (b) σ1=386, σ2=337, n1=100

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Fig. 6

Reliability variation of predicted residual fatigue lives for E-glass/epoxy laminates [21]: (a) σ1=315, σ2=340, n1=86,300 and (b) σ1=340, σ2=315, n1=1350

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