• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.257-266
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• 2007

It is known that Agresti-Coull approach is an effective tool for the construction of confidence intervals for various problems related to binomial proportions. However, the Agrest-Coull approach often produces a conservative confidence interval. In this note, confidence intervals based on a Bayesian approach are proposed for a linear function of independent binomial proportions. It is shown that the Bayesian confidence interval slightly outperforms the confidence interval based on Agresti-Coull approach in average sense.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.4
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• pp.191-199
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• 2013

It is estimated and analyzed that the design wave height and the confidence interval (hereafter CI) according to the return period using the fourteen-year wave data obtained at Pusan New Port. The functions used in the extreme value analysis are the Gumbel function, the Weibull function, and the Kernel function. The CI of the estimated wave heights was predicted using one of the Monte-Carlo simulation methods, the Bootstrap method. The analysis results of the estimated CI of the design wave height indicate that over 150 years of data is necessary in order to satisfy an approximately ${\pm}$10% CI. Also, estimating the number of practically possible data to be around 25~50, the allowable error was found to be approximately ${\pm}$16~22% for Type I PDF and ${\pm}$18~24% for Type III PDF. Whereas, the Kernel distribution method, a typical non-parametric method, shows that the CI of the method is below 40% in comparison with the CI of the other methods and the estimated design wave height is 1.2~1.6 m lower than that of the other methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.163-168
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• 2011

Robust optimization or reliability-based design optimization are some of the methodologies that are employed to take into account the uncertainties of a system at the design stage. For applying such methodologies to solve industrial problems, accurate and efficient methods for estimating statistical moments and failure probability are required, and further, the results of sensitivity analysis, which is needed for searching direction during the optimization process, should also be accurate. The aim of this study is to employ the function approximation moment method into the sensitivity analysis formulation, which is expressed as an integral form, to verify the accuracy of the sensitivity results, and to solve a typical problem of reliability-based design optimization. These results are compared with those of other moment methods, and the feasibility of the function approximation moment method is verified. The sensitivity analysis formula with integral form is the efficient formulation for evaluating sensitivity because any additional function calculation is not needed provided the failure probability or statistical moments are calculated.

• Journal of Korean Society of Steel Construction
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• v.14 no.2
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• pp.365-373
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• 2002

In this paper, the system reliability concept was presented to predict the lifespan of bridges. Lifetime distribution functions (survivor functions) were used to model real bridges to predict their remaining life. Using the system reliability concept and lifetime distribution functions (survivor functions), a program called LIFETIME was developed. The survivor functions give the reliability of component at time t. The program was applied to an existing Colorado state highway bridge to predict the failure probability of the time-dependent system. The bridge was modeled as a system, with failure probability computed using time-dependent deteriorating models.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.13 no.1
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• pp.9-17
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• 2001

A probability of failure of armor units on rubbJe-mound breakwater are evaluated by using the direct method for reliability analysis, which is represented as a function of safety factor that has been extensively used in practical design. The reliability function is fonnulated based on Hudson formula suggested for designing the stable size of armor units on rubble-mound breakwater. Several kinds of stability coefficient are applied separately to calculate the probability of failure with respect to the type of armor units, breaking/nonbreaking and the correlation coefficients between random variables. [n addition, the sensitivity analyses are carried out to investigate quantitatively into the effects of each random variable in the reliability function on the probability of failure.

• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.315-320
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• 2000

본 연구에서는 수리 가능한 시스템에서 고장 강도와 수리 효과에 대한 모수 추정 문제를 다룬다. 시스템이 노후화로 인한 고장이 발생할 경우 최소수리가 행해지고 계획된 예방정비에서는 비례적 수명 감소가 이루어지는 수명 데이터에 대해서 고장 강도 함수의 모수와 정비의 수리효과를 추정하기 위해서 최대 우도 함수 방법을 이용한다. 또한 유전자 알고리즘을 이용해서 우도 함수를 최대화시키는 절차를 개발하고 수치 예제를 나타낸다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.15 no.2
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• pp.86-96
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• 2003

A fracture or breakage of the concrete armor units in the primary cover layer of breakwaters is studied by using the reliability analysis which may be defined as the structural stability. The reliability function can be derived as a function of the angle of rotation that represents the rocking of armor units quantitatively. The relative influences of all of random variables related to the material and geometric properties on the fracture of armor units is analyzed in detail. In addition, the probability of failure for the fracture of individual armor unit can be evaluated as a function of the incident wave height. Finally, Bernoulli random process and the allowable fracture ratio may be introduced together in this paper, by which the probability of failure of a breakwater due to the fracture of armer units can be obtained straightforwardly. It is found that the probability of failure of a breakwater due to the fracture of armor units may be varied with the several allowable fracture ratios. Therefore, it should be necessary to consider the structural stability as well as the hydraulic stability for the design of breakwaters with multi-leg slender concrete armor units of large size under wave action in deep water.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.685-694
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• 1998

임상실험이나 신뢰성공학 분야에서 임의 중단자료를 이용한 비모수적 신뢰도 추정량으로 Kaplan-Meier 추정량과 Nelson형 추정량이 많이 사용되고 있다. 그러나 Nelson형 추정량은 평균제곱오차의 관점에서 Kaplan-Meier 추정량보다 추정능력이 우수한 반면 편의는 신뢰도가 감소함에 따라 양의 방향으로 점증하는 소표본 특성을 갖는다. Nelson형 추정량의 이러한 특성 때문에 신뢰도의 함수로 표현되는 잔여수명 분위수함수 등의 추정시에는 평균제곱오차의 관점에서 Kaplan-Meier 추정량보다 추정능력이 떨어짐을 볼 수 있다. 이러한 점을 고려하여 이 두 추정량을 가중평균으로 통합한 새로운 비모수적 신뢰도 추정량을 제안하고 추정량의 특성을 비교 분석하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1691-1695
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• 2010

본 연구에서 AFDA(Approximate Full Distribution Approach)를 사용하여 하수관의 불능확률을 정량적으로 산정할 수 있는 신뢰성 모형이 개발되었다. 여러 도시의 연 최대강우강도(Yearly Maximum Rainfall Intensity)를 이용하여 그 확률분포함수를 분석하였고 우수관(Storm sewer)의 불능확률 산정을 위한 신뢰성 모형에 적용하였다. 연 최대강우강도 자료의 분석결과 우리나라 중부지방의 여러 중소도시에 대한 연 최대강우강도의 확률분포함수는 Gumbel분포와 일치하는 것으로 나타났다. 신뢰성 모형은 불능확률의 신뢰함수를 구하기 위해 하중(Load)을 규정하는 식은 합리식이 사용되었고 용량(Capacity)를 규정하는 식은 Darcy-Weisbach공식과 Manning의 공식이 사용되었다. 이렇게 개발된 신뢰성 모형을 실제 우수관에 적용하여 불능확률을 산정하는 신뢰성 해석을 수행하였다. Y자형 우수관망에서 2개의 관으로 유입하는 각각의 유량이 그 관의 허용유량을 초과할 경우를 불능확률로 가정하였고, 나머지 관의 경우는 두 개의 관으로부터 유입하는 유량과 그 세 번째 관의 매설지역의 우수유입량의 합이 그 관의 허용유량을 초과할 경우를 불능상태(state of system failure)로 간주하여 불능확률을 정량적으로 산정하였다. Darcy-Weisbach공식과 Manning의 공식을 사용한 신뢰성 해석결과를 비교하였으며 우수관 직경의 변화에 따른 불능확률을 산정하였다. 특정한 수치(설계직경)이하일 경우 불능확률이 급격히 증가하는 것으로 나타났다. 따라서 실제 우수관의 유효직경이 설계직경에 항상 가깝도록 불순물을 제거하는 것이 최선의 관리 방법이며 불능확률을 줄이는 최선의 방법일 것이다. 본 연구에서 개발된 신뢰성 모형은 우수관의 운용, 관리, 감독은 물론 설계에 활용이 가능 할 것이다.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.1-10
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• 2023

The nuclear power plant(NPP)'s Instrumentation and Control(I&C) system periodically conducts integrity checks for the maintenance of self-diagnostic function during normal operation. Additionally, it performs functionality and performance checks during planned preventive maintenance periods. However, there is a need for technological development to diagnose failures and prevent accidents in advance. In this paper, we studied methods for estimating the reliability function by utilizing environmental data and self-diagnostic data of the I&C equipment. To obtain failure data, we assumed probability distributions for component features of the I&C equipment and generated virtual failure data. Using this failure data, we estimated the reliability function using representative artificial intelligence(AI) models used in survival analysis(DeepSurve, DeepHit). And we also estimated the reliability function through the Cox regression model of the traditional semi-parametric method. We confirmed the feasibility through the residual lifetime calculations based on environmental and diagnostic data.