• 한국시뮬레이션학회논문지
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• 제20권4호
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• pp.127-138
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• 2011

장시간 저장 후 짧은 시간 동안 운용되는 특성을 갖는 보증 유도탄은 지속적인 신뢰도 저하를 개선하기 위해 주기적인 검사정책을 사용한다. 본 연구에서는 유도탄의 저장 신뢰도 유지를 위해 주기적 검사 개념을 기초로 검사장비의 불완전성에 따라 유도탄 구성품을 정비계단에 맞추어 분류하고, 검사 시 발생하는 손상확률과 정비과정의 불완전성에 의해 손상되는 확률을 고려하여 최적의 검사주기 산출과정을 제시한 기존 연구를 검토한다. 또한 검토된 기존 연구를 바탕으로 주기검사 과정에서 유도탄이 손상되는 확률과 유도탄의 운용 형태 및 정비 형태를 고려한 제약사항을 포함하는 시뮬레이션 모델을 설정하고, 시뮬레이션 전용 패키지를 활용하여 분석함으로써 실제 운용 환경에서 최적의 보증유도탄 검사주기, 주기검사소, 정비창을 설정함으로써 유사 유도탄체계에서 활용이 가능한 시뮬레이션모델을 제안한다.

• 대한기계학회논문집A
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• 제30권8호
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• pp.941-948
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• 2006

In this study, the new method for reliability estimation is proposed using kriging metamodel. Kriging metamodel can be determined by appropriate sampling range and sampling numbers because there are no random errors in the Design and Analysis of Computer Experiments(DACE) model. The first kriging metamodel is made based on widely ranged sampling points. The Advanced First Order Reliability Method(AFORM) is applied to the first kriging metamodel to estimate the reliability approximately. Then, the second kriging metamodel is constructed using additional sampling points with updated sampling range. The Monte-Carlo Simulation(MCS) is applied to the second kriging metamodel to evaluate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.

• 대한기계학회논문집A
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• 제30권9호
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• pp.1116-1123
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• 2006

In this study, the effective method for reliability estimation is proposed using tow-staged kriging metamodel and genetic algorithm. Kriging metamodel can be determined by appropriate sampling range and the number of sampling points. The first kriging metamodel is made based on the proposed sampling points. The advanced f'=rst order reliability method is applied to the first kriging metamodel to determine the reliability and most probable failure point(MPFP) approximately. Then, the second kriging metamodel is constructed using additional sampling points near the MPFP. These points are selected using genetic algorithm that have the maximum mean squared error. The Monte-Carlo simulation is applied to the second kriging metamodel to estimate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.

• 대한기계학회논문집
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• 제18권9호
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• pp.2257-2264
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• 1994

A method to evaluate the position performance for a stochastically defined planar robot manipulator is presented. Performance is defined as the operational reliability based upon the positional errors of the manipulator tip. An analytical method is developed and applied to a two-link robot manipulator through forward kinematics. This study includes uncertainties in the link length, pin center location and radial clearance. By virtue of the effective link length model, only the nominal manipulator model and statistical information on the uncertainties are required. The results from the analytical method is compared to those from the Monte Carlo simulation.

• 전기학회논문지
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• 제66권12호
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• pp.1712-1720
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• 2017

In South Korea, minimum reserve rate, which is to satisfy reliability standard, has been determined by simulation result using WASP. But, it is still controversial whether the level of minimum reserve rate is adequate. Thus, in this study, various analyses of minimum reserve rate are being conducted. WASP uses the probabilistic simulation technique to evaluate whether reliability standard is satisfied. In this process, forced outage rate and maintenance periods of each generator play important roles. Especially, the long-term plan can be varied depending on how maintenance periods deal with. In order to model maintenance periods in the probabilistic simulation technique, WASP uses derating method. However, broad analyses have to be conducted because there are various ways including derating method to model maintenance periods which result in different results. Therefore, in this paper, 3 different maintenance outage rate modeling methods are applied to arbitrarily modeled system based on the basic plan for long-term electricity supply and demand of South Korea. Results show impact of each modeling method on minimum reserve rate.

• 한국기계가공학회지
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• 제19권12호
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• pp.70-79
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• 2020

This paper describes a comparative study of characteristics of probabilistic design using various reliability analysis methods in the structure design of an automatic salt collector. The thickness sizing variables of the main structural member were considered to be random variables, including the uncertainty of corrosion, which would be an inevitable hazard in the work environment of the automatic salt collector. Probabilistic performance functions were selected from the strength performances of the automatic salt collector structure. First-order reliability method, second-order reliability method, mean value reliability method, and adaptive importance sampling method were applied during the reliability analyses. The probabilistic design performances such as reliability probability and numerical costs based on the reliability analysis methods were compared to the Monte Carlo simulation results. The adaptive importance sampling method showed the most rational results for the probabilistic structure design of the automatic salt collector.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.452-455
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• 1999

Genetic algorithm is well known as the efficient algorithm which can solve a difficult problem. Network design considering reliability is NP-hard problem with cost, distance, and volume. Therefore genetic algorithm is considered as a good method for this problem. This paper suggests the reliable network which can be constructed with minimum cost using genetic algorithm and the rank method based on reliability for improving the performance. This method shows more excellent than existing method and confirms the result through simulation.

• International Journal of Reliability and Applications
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• 제14권1호
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• pp.27-39
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• 2013

In this article, a new model based on the Rayleigh distribution is introduced. This model is useful and practical in physics, reliability, and life testing. The statistical and reliability properties of this model are presented, including moments, the hazard rate, the reversed hazard rate, and mean residual life functions, among others. In addition, it is shown that the distributions of the new model are ordered regarding the strongest likelihood ratio ordering. Four estimating methods, namely, method of moment, maximum likelihood method, Bayes estimation, and uniformly minimum variance unbiased, are used to estimate the parameters of this model. Simulation is used to calculate the estimates and to study their properties. Finally, the appropriateness of this model for real data sets is shown by using the chi-square goodness of fit test and the Kolmogorov-Smirnov statistic.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권1호
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• pp.45-61
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• 2010

In the communication channel, the received signal is affected by many factors that can cause errors. These effects mean that received signal strength (RSS) based methods incur more errors in measuring distance and consequently result in low precision in the location detection process. As one of the approaches to overcome these problems, we propose using direction calibration to improve the performance of the RSS-based method for distance measurement, and sequentially a weighted least squares (WLS) method using reliability factors in conjunction with a conventional RSS weighting matrix is proposed to solve an over-determined localization process. The proposed scheme focuses on the features of the RSS method to improve the performance, and these effects are proved by the simulation results.

• Structural Engineering and Mechanics
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• 제22권6호
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• pp.665-683
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• 2006

The strength behaviors of Fiber Reinforced Plastics (FRP) Composites can be greatly influenced by the properties of constitutive materials, the laminate structures, and load conditions etc, accompanied by many uncertainty factors. So the reliability study on FRP is an important subject of research. Many achievements have been made in reliability studies based on the probability theory, but little has been done on the roles played by fuzzy variables. In this paper, a fuzzy reliability model for FRP laminates is established first, in which the loads are considered as random variables and the strengths as fuzzy variables. Then a numerical model is developed to assess the fuzzy reliability. The Monte Carlo simulation method is utilized to compute the reliability of laminas under the maximum stress criterion. In the second part of this paper, a generalized fuzzy reliability model (GFRM) is proposed. By virtue of the fact that there may exist a series of states between the failure state and the function state, a fuzzy assumption for the structure state together with the probabilistic assumption for strength parameters is adopted to construct the GFRM of composite materials. By defining a generalized limit state function, the problem is converted to the conventional reliability formula that enables the first-order reliability method (FORM) applicable in calculating the reliability index. Several examples are worked out to show the validity of the models and the efficiency of the methods proposed in this paper. The parameter sensitivity analysis shows that some of the mean values of the strength parameters have great influence on the laminated composites' reliability. The differences resulting from the application of different failure criteria and different fuzzy assumptions are also discussed. It is concluded that the GFRM is feasible to use, and can provide an effective and synthetic method to evaluate the reliability of a system with different types of uncertainty factors.