• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.199-207
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• 2001

The failure rate functions between successive failures are of concatenated form. We allow the parameters of failure rate function change after a certain failure and its fixing. We confine out attention to a model wherein the interfailure times are described by its failure rate function. We suggest an adaptive failure rate function with a change-point under the assumption that interfailure times are record value statistics from a Weibull distribution. The proposed model will be applied through a practical example of software failure data.

• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.445-461
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• 1994

This paper deals with the problem of obtaining some Bayes estimators and Bayesian credible regions of a reliability function for the Rayleigh distribution. Using several priors for a reliability function some Bayes estimators and Bayes credible sets are proposed and studied under squared error loss and Harris loss. Also the performances and behaviors of the proposed Bayes estimators are examined via Monte Carlo simulations and some numericla examples are given.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.672-676
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• 2002

In this paper, a reliability-based design optimization method, which enables the determination of optimum design that incorporate confidence range for structures, is studied. Response surface method and Monte Carlo simulation are utilized to determine limit state function. The proposed method is applied to the I-type steel structure for reliability based optimal design.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.11 no.3
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• pp.165-172
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• 1999

A probability density function of reliability function is derived in this paper, by which the stability of armor units on the rubble-mound breakwater can be studied on the probabilistic approach. To obtain the distribution, each random variable of the reliability function is assumed to follow Gaussian distribution. The distribution function of reliability function is in agreement with the histogram simulated by the Monte-Carlo method. In addition, the failure probability of armor units on the rubble-mound breakwater evaluated by the derived probability density function is shown to have the same order of magnitude as those calculated by FMA and AFDA of moment method. In particular, it is important to note that random variables of the reliability function may be considered to be statistically independent in the reliability analysis of armor units on the rubble-mound breakwater. Therefore, the present approach may be straightforwardly applicable to all of the cases that any random variables in the reliability function are controlled by other distribution functions as well as normal distribution.

• International Journal of Reliability and Applications
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• v.13 no.2
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• pp.81-90
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• 2012

Engineering systems are usually repairable. The reliability of a repairable system can be represented by failure intensity function. A type of shape of failure intensity function is called a failure pattern. Reliability-Centred Maintenance (RCM) presents six typical failure patterns but its definition is unclear. It is an open issue how to recognize the failure pattern of repairable systems. This paper first discusses the problems of RCM with the notion of failure pattern; then presents the method for failure pattern recognition; and finally proposes a flexible failure intensity function model. The appropriateness of the model is illustrated by a real-world example.

• Wind and Structures
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• v.27 no.3
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• pp.149-161
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• 2018

A reliability analysis method is proposed in this paper based on the maximum entropy (MaxEnt) principle in which constraints are specified in terms of the fractional moments instead of integer moments. Then a multiplicative dimensional reduction method (M-DRM) is introduced to compute the fractional moments. The method is applicable for both explicit and implicit limit state functions of complex structures. After two examples illustrate the accuracy and efficiency of this method in comparison to the Monte Carlo simulation (MCS), the method is used to analyze the flutter reliability of suspension bridge. The results show that the empirical formula method in which the limit state function is explicitly represented as a function of variables is only a too conservative estimate for flutter reliability analysis but is not accurate adequately. So it is not suitable for reliability analysis of bridge flutter. The actual flutter reliability analysis should be conducted based on a finite element method in which limit state function is implicitly represented as a function of variables. The proposed M-DRM provide an alternate and efficient way to analyze a much more complicated flutter reliability of long span suspension bridge.

• Structural Engineering and Mechanics
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• v.62 no.2
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• pp.125-138
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• 2017

Reliability-based design optimization (RBDO) is a powerful tool for design optimization when considering probabilistic characteristics of design variables. However, it is often computationally intensive because of the coupling of reliability analysis and cost minimization. In this study, the concept of reliability mapping function is defined based on the relationship between the reliability index obtained by using the mean value first order reliability method and the failure probability obtained by using an improved response surface method. Double-loop involved in the classical RBDO can be converted into single-loop by using the reliability mapping function. Since the computational effort of the mean value first order reliability method is minimal, RBDO by using reliability mapping functions should be highly efficient. Engineering examples are given to demonstrate the efficiency and accuracy of the proposed method. Numerical results indicated that the proposed method has the similar accuracy as Monte Carlo simulation, and it can obviously reduce the computational effort.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.50-54
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• 2010

In this study, reliability-based design optimizations of airfoils were performed. PARSEC function was used to consider the uncertainty of the aerodynamic shape for the reliability-based shape optimization of airfoils. Among aerodynamic performance. The accuracy of the reliability analysis was compared with other method and it was found that the moment method predicts the probability accurately. Deterministic and reliability-based optimizations were performed for shape of the RAE2822 airfoil and it was demonstrated that reliability-based optimizations the aerodynamic performances under uncertainties of the shape of the airfoil.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.59-62
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• 2001

Reliability engineering is regarded as the major and important roll for all industry. And advanced manufacturing systems with high speed and intelligent have been developing for the betterment of machining ability. In this study, we have systemized evaluation of reliability for machinery system. We proposed the reliability assessment and design review method using analyzing critical units of high speed and intelligent machine system. In addition, we have not only designed and developed test bed system for acquiring reliability data, but also apply QFD technique for satisfying quality function which is provided in design phase. From this study, we will expect to guide and introduce the reliability engineering in developing and processing phase of high quality product.

• Journal of Korean Physical Therapy Science
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• v.4 no.1
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• pp.265-289
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• 1997

The purpose of this studied was to examine the reliability analysis of the GMFM in children with C.P. The subject of this study were 40 C. P patient who had been hospitalized Department of Sam-Yook Rehabilitation Hospital. Subjects were 28 boys and girls, aged 6 to 8 years. Reliability of each dimension of the GMFM were analyzed using Cronbach coefficients and to examine the intra-rater reliability were using Pearson correlation coefficients. The result of reliability analysis of the GMFM revealed higher reliability values. The reliability of the total dimension score was 95. Test-retest revealed intra-rater correlation coefficients from .71 to .98. The study presents that GMFM is useful in assessment of function of children with C. P by the quantitative description of the function.