• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.505-514
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• 2000

A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduced mixture failure model of Rayleigh and Erlang(2) pattern. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Gibbs steps are proposed to perform the Bayesian inference of such models. For model determination, we explored sum of relative error criterion that selects the best model. A numerical example with simulated data set is given.

• Computational Structural Engineering
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• v.11 no.4
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• pp.219-227
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• 1998

실제 구조물에 있어 확률, 통계 및 이론으로 구해진 랜덤성을 갖는 객관적 불확실성뿐만 아니라 설계자의 경험이나 공학적 판단에 의해 주관적으로 평가되는 인간오차나 시공중의 과오 또는 구조설계에 미치는 사회적, 정치적 및 경제적 요청 등의 퍼지성을 갖는 주관적 불확실성이 존재하기 때문에 현실적으로 랜덤성과 퍼지성을 동시에 고려한 실뢰성평가 즉, 안전성평가에 대한 퍼지이론의 도입이 필수 불가결하다. 따라서 본 연구에서는 기존 구조물의 객관적·주관적 불확실성을 동시에 고려한 신뢰성해석방법으로 베이즈의 의사결정이론에 퍼지이론을 병합한 퍼지-베이즈 신뢰성해석 알고리즘을 개발하여 건축구조물의 신뢰성평가 및 안전성평가에 적용하여 분석하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.929-938
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• 2009

This paper presents a novel control methodology for communication network based nonlinear systems with time delay nature. We construct a nominal nonlinear control law for representing a linear model and a reset control system which is aimed for corrective control strategy to compensate system error due to uncertain time delay through wireless communication network. Next, online neural control approach is proposed for overcoming nonstationary statistical nature in the network topology. Additionally, DBN (Dynamic Bayesian Network) technique is accomplished for modeling of its dynamics in terms of casuality, which is then utilized for estimating prediction of system output. We evaluate superiority and reliability of the proposed control approach through numerical simulation example in which a nonlinear inverted pendulum model is employed as a networked control system.

• Journal of Aerospace System Engineering
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• v.8 no.4
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• pp.7-17
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• 2014

Objective of this paper is to introduce a new technology known as prognostics and health management (PHM) which enables a real-time life prediction for safety critical systems under extreme loading conditions. In the PHM, Bayesian framework is employed to account for uncertainties and probabilities arising in the overall process including condition monitoring, fault severity estimation and failure predictions. Three applications - aircraft fuselage crack, gearbox spall and battery capacity degradation are taken to illustrate the approach, in which the life is predicted and validated by end-of-life results. The PHM technology may allow new maintenance strategy that achieves higher degree of safety while reducing the cost in effective manner.

• Journal of Korean Society for Quality Management
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• v.42 no.2
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• pp.199-208
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• 2014

Purpose: This paper explains how to obtain the Bayes estimates of the whole launch vehicle and of a vehicle stage, respectively, for a newly developed expendable launch vehicle. Methods: We determine the parameters of the beta prior distribution using the upper bound of the 60% Clopper-Pearson confidence interval of failure probability which is calculated from previous launch data considering the experience of the developer. Results: Probability that a launch vehicle developed from an inexperienced developer succeeds in the first launch is obtained by about one third, which is much smaller than that estimated from the previous research. Conclusion: The proposed approach provides a more conservative estimate than the previous noninformative prior, which is more reasonable especially for the initial reliability of a new vehicle which is developed by an inexperienced developer.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1080-1082
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• 2003

To develop a reliability analysis program applied to the diagnosis for air operated valve's integrity. we collected, analyzed AOV failure data from foreign and domestic nuclear power plants, and classified whole subjects of this program into several groups according to type and size. We established a theoretical basis using Lognormal Distribution and Bayesian Theory to develop analysis methodology. The result of this program was applied to the calculation of operational unavailability of AOV, and the effect of AOV's failure. Also this program can be applied to the development of diagnostic technique considering AOV environment (temperature, pressure), and setting-up maintenance cycle.

• Journal of the Korea institute for structural maintenance and inspection
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• v.2 no.3
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• pp.223-234
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• 1998

In this study, an attempt is made to apply the concept of fuzzy-bayesian theory to the integrity assessment of structure system, and uncertainty states are represented in terms of fuzzy sets which define several linguistic variables such as "very good", "good", "average", "poor", "very poor", etc. Especially, the concept of fuzzy conditional probability aids to derive a new reliability analysis which includes the subjective assessment of engineers without introducing any additional correction factors. The fuzzy concept are also used as reliability indexes for the condition assessment based on the proposed models, the proposed fuzzy theory-based approach with the results of PEM and AFOSM are applied to retaining wall.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3913-3923
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• 2023

Todays, medium energy resolution detectors are preferably used in radioisotope identification devices(RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(²⁴¹Am, ⁵⁷Co, ¹³⁷Cs, ⁵⁴Mn, ⁶⁰Co), and then applied to five standard nuclear materials(0.32-4.51% at.²³⁵U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5-74.4% for ²³⁸U and 4.7-10.5% for ²³⁵U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify ²³⁵U and ²³⁸U isotopes in LEU or natural U-Th samples if a medium energy resolution detector is was in the measurements.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.181-186
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• 2003

There are many uncertainties in structural failures or structures, so probabilistic failure cause assessment should be performed in order to consider the uncertainties. However, in many cases of forensic engineering, the failure cause assessments are performed by deterministic approach though number of uncertainties are existed in the failures or structures. Thus, deterministic approach may have possibility for leading to unreasonable and unrealistic failure cause assessment due to ignorance of the uncertainties. Therefore, probabilistic approach is needed to complement the shortcoming of deterministic approach and to perform the more reasonable and realistic failure cause assessment. In this study, reliability-based failure cause assessment (reliability based forensic engineering) is performed, which can incorporate uncertainties in failures and structures. For more practical application, the modified ETA technique is proposed, which automatically generates the defected structural model, performs structural analysis and reliability analysis, and calculates the failure probabilities of the failure events and the occurrence probabilities of the failure scenarios. Also, for more precise reliability analysis, uncertainties are estimated more reasonably by using bayesian approach based on the experimental laboratory testing data in forensic report.

• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.241-248
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• 1997

This paper presents the development procedure and application of the generic component reliability data base considering the dependency among dependent generic compendia in NPPs (Nuclear Power Plants) PSA (Probabilistic Safety Assessment) under construction or without operating history. We use MPRDP (Multi-Purpose Reliability Data Processor) code developed in KAERI (Korea Atomic Energy Research Institute) based on a PEB (Parametric Empirical Bayesian) procedure to estimate the reliability. The employed model in this study accounts for the relative credibility as well as the dependency among generic estimates. Numerical examples and the part of summarized reliability data table are provided as the application.