• 산업경영시스템학회지
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• 제35권2호
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• pp.98-105
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• 2012

This paper describes the Bayesian approach for reliability demonstration test based on the samples from a finite population. The Bayesian approach involves the technical method about how to combine the prior distribution and the likelihood function to produce the posterior distribution. In this paper, the hypergeometric distribution is adopted as a likelihood function for a finite population. The conjugacy of the beta-binomial distribution and the hypergeometric distribution is shown and is used to make a decision about whether to accept or reject the finite population judging from a viewpoint of faulty goods. A numerical example is also given.

• Journal of the Korean Data and Information Science Society
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• 제17권3호
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• pp.743-752
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• 2006

This paper considers a Bayesian approach to replacement policy model with minimal repair. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal maintenance policy. Especially, the overall value function suggested by Jiagn and Ji(2002) is applied to obtain the optimal replacement period. The numerical examples are presented for illustrative purpose.

• 한국수자원학회논문집
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• 제49권5호
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• pp.411-422
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• 2016

우리나라는 수공구조물 설계할 때 강우빈도해석과 강우-유출 모형으로 홍수량을 산정하여 사용하고 있다. 그러나 강우자료의 확률분포 및 자료기간 등에 따른 매개변수 추정에 많은 불확실성이 존재하나 이를 고려한 해석은 이루어지지 않고 있다. 이러한 점에서 Gumbel 분포형과 확률가중 모멘트법을 기준으로 확률강우량의 신뢰구간을 평가함과 동시에 매개변수의 불확실성을 평가하는데 있어서 우수한 성능을 발휘하는 Bayesian방법을 도입하여 서울지역의 확률강우량의 불확실성을 정량적으로 평가하였다. 두 가지 방법의 비교결과 확률가중모멘트법의 신뢰구간이 Bayesian 방법의 불확실성 구간보다 전반적으로 크게 나타났다. 신뢰구간의 경우 정규분포를 따르기 때문에 좌우대칭의 형태를 갖는 반면에 Bayesian 방법의 불확실성은 Gumbel 분포로부터 유도되어, 보다 현실적인 불확실성 평가가 가능하였다. 자료의 구간 및 기간에 따른 확률강우량의 불확실성을 평가한 결과 자료에 증가에 따른 불확실성 감소를 확인할 수 있었으며, Bayesian 방법이 자료 증가에 따른 불확실성 범위 감소가 보다 뚜렷하게 나타나는 것을 확인할 수 있었다.

• Nuclear Engineering and Technology
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• 제49권2호
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• pp.434-441
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• 2017

Containment venting is one of several essential measures to protect the integrity of the final barrier of a nuclear reactor during severe accidents, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach to venting operations, from a simulation-based perspective, using an integrated severe accident code, THALES2/KICHE. The effectiveness of the containment-venting strategies needs to be verified via numerical simulations based on various settings of the venting conditions. The number of iterations, however, needs to be controlled to avoid cumbersome computational burden of integrated codes. Bayesian optimization is an efficient global optimization approach. By using a Gaussian process regression, a surrogate model of the "black-box" code is constructed. It can be updated simultaneously whenever new simulation results are acquired. With predictions via the surrogate model, upcoming locations of the most probable optimum can be revealed. The sampling procedure is adaptive. Compared with the case of pure random searches, the number of code queries is largely reduced for the optimum finding. One typical severe accident scenario of a boiling water reactor is chosen as an example. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies during severe accidents.

• 대한산업공학회지
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• 제43권2호
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• pp.147-153
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• 2017

In order to demonstrate a target reliability with a specified confidence level, a new two-stage Bayesian Reliability Demonstration Test (RDT) plans that is known to be more effective than a corresponding single-stage one is proposed and developed by Bayesian framework with beta prior distribution for Weibull life time distribution. A numerical example is provided to illustrate the proposed RDT plans and compared with other non-Bayesian and Bayesian plans. Comparative results show that the proposed Bayesian two-stage plans have some merits in terms of required and expected testing time and probability of acceptance.

• Earthquakes and Structures
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• 제8권4호
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• pp.935-956
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• 2015

Structural Health Monitoring (SHM) of steel towers has become a hot research topic. From the literature, it is impractical and impossible to develop a "general" method that can detect all kinds of damages for all types of structures. A practical method should make use of the characteristics of the type of structures and the kind of damages. This paper reports a feasibility study on the use of measured modal parameters for the detection of damaged braces of tower structures following the Bayesian probabilistic approach. A substructure-based structural model-updating scheme, which groups different parts of the target structure systematically and is specially designed for tower structures, is developed to identify the stiffness distributions of the target structure under the undamaged and possibly damaged conditions. By comparing the identified stiffness distributions, the damage locations and the corresponding damage extents can be detected. By following the Bayesian theory, the probability model of the uncertain parameters is derived. The most probable model of the steel tower can be obtained by maximizing the probability density function (PDF) of the model parameters. Experimental case studies were employed to verify the proposed method. The contributions of this paper are not only on the proposal of the substructure-based Bayesian model updating method but also on the verification of the proposed methodology through measured data from a scale model of transmission tower under laboratory conditions.

• Smart Structures and Systems
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• 제26권6호
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• pp.735-751
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• 2020

Identification of structure parameters is crucial in Structural Health Monitoring (SHM) context for activities such as model validation, damage assessment and signal processing of structure response. In this paper, guided waves generated by piezoelectric transducers are used for in-situ and non-destructive structural parameter estimation based on Bayesian approach. As Bayesian approach needs iterative process, which is computationally expensive, this paper proposes a method in which an analytical model is selected and developed in order to decrease computational time and complexity of modeling. An experimental set-up is implemented to estimate three target elastic and geometrical parameters: Young's modulus, Poisson ratio and thickness of aluminum and steel plates. Experimental and simulated data are combined in a Bayesian framework for parameter identification. A significant accuracy is achieved regarding estimation of target parameters with maximum error of 8, 11 and 17 percent respectively. Moreover, the limitation of analytical model concerning boundary reflections is addressed and managed experimentally. Pulse excitation is selected as it can excite the structure in a wide frequency range contrary to conventional tone burst excitation. The results show that the proposed non-destructive method can be used in service for estimation of material and geometrical properties of structure in industrial applications.

• 지질공학
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• 제22권1호
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• pp.15-25
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• 2012

지반정수의 통계적 불확실성을 설계에 반영함으로써 합리적인 설계를 하기위한 확률론적 설계법이 국내외에서 설계기준으로 채택되고 있는 추세이다. 본 연구에서는 지반 확률변수의 불확실성을 정량화 하기위한 기법과 획득한 자료의 수에 따라 불확실성을 최소화함으로써 설계의 경제성을 기할 수 있는 기법들을 분석하였다. 국내의 특정 현장에서 채취되고 실험된 토질정수를 불확실성 정량화를 위한 몇 가지 기법들에 적용하고 비교하였다. 그 결과 3-sigma기법은 자료를 이용하여 산정된 표준편차에 비하여 모두 낮게 평가되어 확률론적으로 경제적인 설계가 가능하나 샘플 수를 고려하지 않은 Bayesian 기법을 이용하여 사전정보와 조합한 경우 일부의 변수는 3-sigma기법이 작게 산정되어 불안전한 설계의 우려가 있었다. 반면, 샘플 수를 고려하여 Bayesian 분석한 경우는 상대적으로 가장 낮은 분산을 보였다. 샘플 수가 증가할수록 확률밀도함수의 분산이 현저히 감소하였고 25개 이상인 경우 전체적으로 일정수준에 수렴하였다. 특히, 단위중량과 같이 변동성이 작은 확률변수의 경우 상대적으로 적은 샘플 수에서도 사후정보에서 신뢰도 높은 값을 추정할 수 있었다.

• 한국정보과학회논문지:데이타베이스
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• 제37권6호
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• pp.285-291
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• 2010

본 연구에서는 나이브 베이시안 학습의 환경에서 속성의 가중치를 계산하는 새로운 방식을 제안한다. 기존 방법들이 속성에 가중치를 부여하는 방식인데 반하여 본 연구에서는 한걸음 더 나아가 속성의 값에 가중치를 부여하는 새로운 방식을 연구하였다. 이러한 속성값의 가중치를 계산하기 위하여 Kullback-Leibler 함수를 이용하여 가중치를 계산하는 방식을 제안하였고 이러한 가중치들의 특성을 분석하였다. 제안된 알고리즘은 다수의 데이터를 이용하여 속성 가중치 방식과 비교하였고 대부분의 경우에 더 좋은 성능을 제공함을 알 수 있었다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.59-65
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• 2005

We propose five Bayesian methods to estimate the cell expectation in an incomplete multi-way categorical table with nonignorable nonresponse mechanism. We study 3 Bayesian methods which were previously applied to one-way categorical tables. We extend them to multi-way tables and, in addition, develop 2 new Bayesian methods for multi-way categorical tables. These five methods are distinguished by different priors on the cell probabilities: two of them have the priors determined only by information of respondents; one has a constant prior; and the remaining two have priors reflecting the difference in the response mechanisms between respondent and non-respondent. We also compare the five Bayesian methods using a categorical data for a prospective study of pregnant women.