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Bayesian 추계학적 신뢰도 기법을 이용한 소양강댐 퇴사용량 감소의 불확실성 분석

Identification of Uncertainty on the Reduction of Dead Storage in Soyang Dam Using Bayesian Stochastic Reliability Analysis

  • 이철응 (강원대학교 공과대학 토목공학과) ;
  • 김상욱 (강원대학교 공과대학 토목공학과)
  • Lee, Cheol-Eung (Department of Civil Engineering, Kangwon National University) ;
  • Kim, Sang Ug (Department of Civil Engineering, Kangwon National University)
  • 투고 : 2012.10.15
  • 심사 : 2012.11.26
  • 발행 : 2013.03.31

초록

저수지 내 퇴적과정으로 의한 저수용량 감소에 대한 효율적 관리의 중요성에도 불구하고, 불확실성을 포함하는 확률론적 관점의 신뢰도 분석이론을 활용한 저수용량 감소에 관한 연구는 많지 않다. 본 연구에서는 신뢰도 분석모형의 하나인 추계학적 감마 과정(stochastic gamma process)을 이용하고 개발된 모형을 소양강댐에서 적용하여 향후 발생될 수 있는 저수용량의 감소를 불확실성 측면에서 분석하였다. 특히 불확실성을 분석하기 위하여 정보적 사전분포(informative prior distribution)를 이용한 Bayesian MCMC 기법을 사용하여 추계학적 감마 과정의 모수(parameter)를 추정하였다. 구축된 정보적 사전분포를 적용한 결과사전분포의 불확실성에 비해 사후분포의 불확실성이 상당히 감소되어져 정보적 사전분포의 효과를 확인할 수 있었으며, 소양강댐 퇴사용량의 기대수명은(expected life time)은 5%유의수준에서 119.3년부터 183.5년의 불확실성을 나타내는 것으로 분석되었다. 이와 같은 연구는 저수용량의 감소에 관한 불확실성 측면의 정보를 신뢰도 분석결과와 함께 제공할 수 있으므로, 향후 퇴적과정으로 인한 저수지의 유지관리계획을 수립함에 있어 댐관리자 등에게 효과적으로 활용될 수 있을 것으로 판단된다.

Despite of the importance on the maintenance of a reservoir storage, relatively few studies have addressed the stochastic reliability analysis including uncertainty on the decrease of the reservoir storage by the sedimentation. Therefore, the stochastic gamma process under the reliability framework is developed and applied to estimate the reduction of the Soyang Dam reservoir storage in this paper. Especially, in the estimation of parameters of the stochastic gamma process, the Bayesian MCMC scheme using informative prior distribution is used to incorporate a wide variety of information related with the sedimentation. The results show that the selected informative prior distribution is reasonable because the uncertainty of the posterior distribution is reduced considerably compared to that of the prior distribution. Also, the range of the expected life time of the dead storage in Soyang Dam reservoir including uncertainty is estimated from 119.3 years to 183.5 years at 5% significance level. Finally, it is suggested that the improvement of the assessment strategy in this study can provide the valuable information to the decision makers who are in charge of the maintenance of a reservoir.

키워드

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