• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.4
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• pp.790-805
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• 1988

Static strength and fatigue life scattering of glass fiber reinforced epoxy composite materials has been studied. Normal, lognormal, two-parameter and three-parameter Weibull distribution functions are used for strength and one-stress fatigue life distribution. The value of mean fatigue life is analysed using mean fatigue life, mean log fatigue life and expected value of 2 and 3-parameter Weibull distribution functions. Modification on non-statistical cumulative damage models is made in order to interpret the result of two-stress level fatigue life scattering. The comparison results show that 3-parameter Weibull distribution has better predictions in static strength and one-stress level fatigue life distributions. However, no advantage of 3-parameter Weibll distribution is found over 2-parameter Weibull distribution in two-stress level fatigue life predictions. It is found that two-stress level fatigue life prediction by the expanded equal rank assumption is close to the experimental data.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.11a
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• pp.119-123
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• 2000

The characteristics of fatigue life distribution for Carbon/epoxy composite laminates was investigated under tension-tension loading(R=0.1). The statistical nature of the fatigue life of the composite materials was analyzed by Weibull, normal, lognormal distributions As a result, it was observed that the correlation between the experimental results and the theoretical predictions for the fatigue life is good. The distribution of the static ultimate strength has the characteristic of lognormal distribution and distribution of the fatigue life has characteristics of the weibull distribution.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1281-1287
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• 2000

The studies of probability distribution of the fatigue crack growth life have been somewhat reported. But the study on the probability distribution of the fatigue crack growth life considering the crack coalescence for three dimensional surface fatigue crack has apparently not been reported to date. In this study, the computer program has been developed to predict the probability distribution of the fatigue crack growth life considering the crack coalescence. The effects of parameters for the distribution of the fatigue crack propagation life were evaluated by using the program.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.8
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• pp.707-719
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• 2009

The variables relating to the fatigue behavior have uncertainty and are random. The fatigue crack propagation is, thus, stochastic in nature. In this study, fatigue experiments are performed on the specimen of the magnesium alloy AZ31. The data of the fatigue life are scattered even in the same experimental condition. It is necessary to determine the probability distribution of the fatigue crack propagation life for the reliability analysis as well as the design and maintenance of structural components. Therefore the statistics and the probability distribution for the fatigue crack propagation life are investigated and the best fit probability distribution of that is proposed in this paper.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.594-599
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• 2011

In this paper, the effect of the boundary conditions on the reliability and the cumulative distribution characteristics of the fatigue failure life is analyzed in a magnesium alloy AZ31. The boundary conditions are specimen thickness, stress ratio, and maximum fatigue load. The statistical data of the fatigue failure life are obtained by fatigue crack propagation tests under the detail conditions for each boundary condition. The 3-parameter Weibull distribution is used to analyze a statistical characteristics of the fatigue failure life in magnesium alloy AZ31. It is found that the statistical fatigue failure life is long in the case of a thicker specimen, a larger stress ratio, and a smaller maximum fatigue load. Under the opposite cases, the reliability on the fatigue failure life is rapidly dropped.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.68
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• pp.1-7
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• 2001

A probabilistic model for fatigue life of a structural component is derived when the component is in a variable-amplitude loading environment. The physical mechanism which governs fatigue failure is used to model the fatigue life. Especially, the judgement of rotational symmetry in the-stress-intensity-factors results in the probability distribution for fatigue life. The probability distribution is related to the familiar truncated Gaussian distribution, which has a single parameter with a direct physical meaning.

• Journal of Power System Engineering
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• v.20 no.3
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• pp.29-35
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• 2016

Because of the severe service environment of the large marine vessel, the fatigue strength and its evaluation play an important role in design and maintenance of marine crankshaft. The aim of this work is to investigate the probability distribution of fatigue lives in crank throw forged steel and to develop the methodology for estimation of the probabilistic design fatigue strength. Detailed studies were performed on the constant amplitude axial loading fatigue test. The experiments were controlled by stress ratio of -1 and 15Hz frequency for each stress level. The considerable variability of fatigue life was observed in each stress level under rigidly controlled constant fatigue testing conditions. The fatigue life of crank throw forged steel was well followed the log-normal and Weibull distribution. In addition, it can be used for the estimation of probabilistic design fatigue strength by using the proposed methodology.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2353-2360
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• 2000

Statistical fatigue properties of metallic materials are increasingly required for reliability design purpose. In this study, static and fatigue tests were conducted and the normal, log-normal, two -parameter Weibull distributions at the 5% significance level are compared using the Kolmogorov-Smirnov goodness-of-fit test. Parameter estimation were compared with experimental results using the maximum likelihood method and least square method. It is found that two-parameter Weibull distribution and maximum likelihood method provide a good fit for static and fatigue life data. Therefore, it is applicable to the static and fatigue life analysis of the spheroidal graphite cast iron. The P-S-N curves were evaluated using log-normal distribution, which showed fatigue life behavior very well.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.6
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• pp.804-811
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• 2010

The fatigue crack propagation is stochastic in nature, because the variables affecting the fatigue behavior are random and have uncertainty. Therefore, the fatigue life prediction is critical for the design and the maintenance of many structural components. In this study, fatigue experiments are conducted on the specimens of magnesium alloy AZ31 under various conditions such as thickness of specimen, the load ratio and the loading condition. The probability distribution fit to the fatigue failure life are investigated through a probability plot paper by these conditions. The probabilities of failure at various conditions are also estimated. The fatigue design life is predicted by using the Weibull distribution.

• Structural Engineering and Mechanics
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• v.37 no.4
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• pp.427-442
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• 2011

In fatigue life design of mechanical components, uncertainties arising from materials and manufacturing processes should be taken into account for ensuring reliability. A common practice is to apply a safety factor in conjunction with a physics model for evaluating the lifecycle, which most likely relies on the designer's experience. Due to conservative design, predictions are often in disagreement with field observations, which makes it difficult to schedule maintenance. In this paper, the Bayesian technique, which incorporates the field failure data into prior knowledge, is used to obtain a more dependable prediction of fatigue life. The effects of prior knowledge, noise in data, and bias in measurements on the distribution of fatigue life are discussed in detail. By assuming a distribution type of fatigue life, its parameters are identified first, followed by estimating the distribution of fatigue life, which represents the degree of belief of the fatigue life conditional to the observed data. As more data are provided, the values will be updated to reduce the credible interval. The results can be used in various needs such as a risk analysis, reliability based design optimization, maintenance scheduling, or validation of reliability analysis codes. In order to obtain the posterior distribution, the Markov Chain Monte Carlo technique is employed, which is a modern statistical computational method which effectively draws the samples of the given distribution. Field data of turbine components are exploited to illustrate our approach, which counts as a regular inspection of the number of failed blades in a turbine disk.