• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.232-237
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• 2001

The evaluation of specimen thickness effect of fatigue crack growth life by the simulation of probabilistic fatigue crack growth is presented. In this paper, the material resistance to fatigue crack growth is treated as a spatial stochastic process, which varies randomly on the crack surface. Using the previous experimental data, the non-Gaussian(eventually Weibull, in this report) random fields simulation method is applied. This method is useful to estimate the probability distribution of fatigue crack growth life and the variability due to specimen thickness by simulating material resistance to fatigue crack growth along a crack path.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.192-200
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• 1994

The methodology of a simple probabilistic fatigue crack under random loading is proposed. Using the crack closure concept, the crack opening stress is assumed to be constant during random loading. The loading history was analyzed to determine the probability density functions, probability distribution functions and other related parameters for the probabilistic fatigue crack growth analysis. Fatigue crack growth using the exisiting available data was predicted by the proposed probabilistic analysis and compared with experimental data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.923-929
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• 2003

In this paper, an analysis of fatigue crack growth behavior from a statistical point of view has been carried out. Fatigue crack growth tests were conducted on sixteen pre-cracked compact tension (CT) specimens of the pressure vessel (SPV50) steel in controlled identical load and environmental conditions. The assessment of the statistical distribution of fatigue crack growth experimental data obtained from SPV50 steel was studied and also the correlation of the parameter C and m in the Paris-Erdogan law was discussed. The probability distribution function of fatigue crack growth life seems to follow the 3-parameter Weibull. The fatigue crack growth rate seems to follow the 3-parameter Weibull and the log-normal distribution. The coefficient of variation (COV) of fatigue crack growth life was observed to decrease as the crack grows. Fatigue crack growth rate data shows a normal distribution for both m and logC. A strong negative linear correlation exists between the coefficient C and the exponent m.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.304-313
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• 2021

Nickel base Alloy X-750, which is used as fastener parts in light-water reactor (LWR), has experienced many failures by environmentally assisted cracking (EAC). In order to improve the reliability of passive components for nuclear power plants (NPP's), it is necessary to study the failure mechanism and to predict crack growth behavior by developing a probabilistic failure model. In this study, The Bayesian inference was employed to reduce the uncertainties contained in EAC modeling parameters that have been established from experiments with Alloy X-750. Corrosion fatigue crack growth rate model (FCGR) was developed by fitting into Paris' Law of measured data from the several fatigue tests conducted either in constant load or constant ΔK mode. These parameters characterizing the corrosion fatigue crack growth behavior of X-750 were successfully updated to reduce the uncertainty in the model by using the Bayesian inference method. It is demonstrated that probabilistic failure models for passive components can be developed by updating a laboratory model with field-inspection data, when crack growth rates (CGRs) are low and multiple inspections can be made prior to the component failure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.4
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• pp.375-381
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• 2011

The primary aim of this study is to investigate the probabilistic characteristics of the fatigue parameters that describe the fatigue crack growth behavior in magnesium alloy. Statistical fatigue crack propagation experiments have been performed on rolled AZ31 magnesium alloy CT specimens with different specimen thickness, load ratio, and maximum load at ambient temperature in a laboratory. Using the statistical fatigue data obtained from these experiments, the goodness-of-fit of the probability distribution of the fatigue behavior parameters is evaluated in this study by performing statistical analyses. The crack growth rate coefficient is a fatigue parameter having a very large COV(Coefficient of Variation), but the variation of a crack growth rate exponent is not substantial. It is considered that a crack growth rate exponent can be a material constant. It is also found that the best fit probability distribution of the parameters such as the crack growth rate coefficient and crack growth rate exponent for a magnesium alloy is a three-parameter Weibull distribution, and two-parameter Weibull distribution is a good distribution only for the crack growth rate coefficient.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.271-279
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• 2018

Purpose: Probabilistic safety analysis was performed to enhance the safety and reliability of nuclear power plants because traditional deterministic approach has limitations in predicting the risk of failure by crack growth. The study introduces a probabilistic approach to establish a basis for probabilistic safety assessment of passive components. Methods: For probabilistic modeling of fatigue crack growth rate (FCGR), various FCGR tests were performed either under constant load amplitude or constant ${\Delta}K$ conditions by using heat treated X-750 at low temperature with adequate cathodic polarization. Bayesian inference was employed to update uncertainties of the FCGR model using additional information obtained from constant ${\Delta}K$ tests. Results: Four steps of Bayesian parameter updating were performed using constant ${\Delta}K$ test results. The standard deviation of the final posterior distribution was decreased by a factor of 10 comparing with that of the prior distribution. Conclusion: The method for developing a probabilistic crack growth model has been designed and demonstrated, in the paper. Alloy X-750 has been used for corrosion fatigue crack growth experiments and modeling. The uncertainties of parameters in the FCGR model were successfully reduced using the Bayesian inference whenever the updating was performed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.1
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• pp.63-69
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• 2015

The primary aim of this paper is to evaluate the probabilistic fatigue crack propagation models using the residual of a random variable and to present the probabilistic model fit for the probabilistic fatigue crack growth behavior in Mg-Al-Zn alloys under maximum load conditions. The models used in this study were prepared by applying a random variable to empirical fatigue crack propagation models such as the Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was verified that the good models for describing the stochastic variation of the fatigue crack propagation behavior in Mg-Al-Zn alloys under maximum load conditions were the 'probabilistic Paris-Erdogan model' and 'probabilistic Walker model'. The influence of the maximum load conditions on the stochastic variation of fatigue crack growth is also considered.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.05a
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• pp.104-109
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• 2002

In this paper, a statistical analysis of fatigue crack growth behavior under constant amplitude loads has been carried out. Fatigue crack growth tests were conducted on sixteen pre-cracked compact tension (CT) specimens of the pressure vessel (SPV50) steel in controlled identical load and environmental conditions. The assessment of the statistical distribution of fatigue crack growth experimental data obtained from SPV50 steel was studied and also the correlation of the parameter C and m in the Paris-Erdogan law was discussed. The probability distribution function of fatigue crack growth life seems to follow the 3-parameter Weibull. The fatigue crack growth rate seems to follow the 3-parameter Weibull and the log-normal distribution. The coefficient of variation (COV) of fatigue crack growth life was observed to decrease as the crack grows. A strong negative linear correlation exists between the coefficient C and the exponent m in Paris model. Fatigue crack growth rate data shows a normal distribution for both m and logC.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.6
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• pp.1448-1454
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• 1994

Data which gathered and used in the field of fatigue and fracture mechanics have a lot of uncertainties. In this case, those uncertainties will make scatter band in evaluation of fatigue life and fracture toughness. Thus, the probabilistic analysis of these data will be needed. For determining the fatigue life in mixed mode, using crack direction law and fatigue crack growth law, the problem is studied as a constrained life minimization. Stress intensity factor(SIF) is computed by approximate solution table(Ewalds/Wanhill 1984) and 0th order PFEM. The variance of fatigue life and SIF are computed by differentiation of tabulated approximate solution and 1st order PFEM. And these are used for criterion of design values, principal parameter determination and modelling. The problem of center cracked plate is solved for checking the PFEM model which is influenced by various parameters like as initial crack length, final crack length, two fatigue parameters in Paris Equation and applied stress.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.130-138
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• 1996

In general, the scattler is observed in fatigue test data due to the nonhomogeneity of a material. Consequently. It is necessary to use the statistical method to describe the fatigue crack growth process precisely. Bogdanoff and Kozin suggested and developed the B-model which is the probabilistic models of cumulative damage using the Markov process in order to describe the damage process. But the B-model uses only constant probability ratior(r), so it is not consistent with the actual damage process. In this study, the r-decreasing model using a monotonic decreasing function is introduced to improve the B-model. To verify the model, thest data of fatigue crack growth of A12024-T351 and A17075-T651 are used. Compared with the empirical distribution of test data, the distribution from the r-decreasing model is satisfactory and damage process is well described from the probabilistic and physical viewpoint.