• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.2
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• pp.179-194
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• 2020

A Bayesian approach was introduced to improve the belief of prior distributions of input parameters for the probabilistic safety assessment of radioactive waste repository. A GoldSim-based module was developed using the Markov chain Monte Carlo algorithm and implemented through GSTSPA (GoldSim Total System Performance Assessment), a GoldSim template for generic/site-specific safety assessment of the radioactive repository system. In this study, sequential Bayesian updating of prior distributions was comprehensively explained and used as a basis to conduct a reliable safety assessment of the repository. The prior distribution to three sequential posterior distributions for several selected parameters associated with nuclide transport in the fractured rock medium was updated with assumed likelihood functions. The process was demonstrated through a probabilistic safety assessment of the conceptual repository for illustrative purposes. Through this study, it was shown that insufficient observed data could enhance the belief of prior distributions for input parameter values commonly available, which are usually uncertain. This is particularly applicable for nuclide behavior in and around the repository system, which typically exhibited a long time span and wide modeling domain.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.275-276
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• 2009

This paper provides a new approach for predicting the corrosion resistivity of reinforced concrete structures exposed to carbonation. In this method, the prediction can be updated successively by a Bayesian theory when additional data are available. The stochastic properties of model parameters are explicitly taken into account into the model. To simplify the procedure of the model, the probability of the durability limit is determined from the samples obtained from the Latin hypercube sampling technique. The new method may be very useful in designing important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.2
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• pp.139-146
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• 2013

This study is to update of vibration power generating model and to analyze electromotive force on subway. Analysis of electromotive force using power generation depending on classification of locations which are ballast bed and concrete bed. As the section between Seocho and Bangbae in the line 2 subway was changed from ballast bed to concrete bed, it could be analyzed at same condition, train, section. Induced electromotive force equation by Faraday's law was updated using Bayesian regression and correlation analysis with calculate value and experiment value. Using the updated model, it could get 40mV per one power generation in ballast bed, and it also could get 4mV per one power generation in concrete bed. If the updated model apply to subway or any train, it will be more effective to get electric power. In addition to that, it will be good to reduce greenhouse gas and to build a green traffic network.

• Journal of the Korea Concrete Institute
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• v.20 no.1
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• pp.77-88
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• 2008

This paper provides a new approach for predicting the corrosion resistivity of reinforced concrete structures exposed to chloride attack. In this method, the prediction can be updated successively by a Bayesian theory when additional data are available. The stochastic properties of model parameters are explicitly taken into account into the model. To simplify the procedure of the model, the probability of the durability limit is determined from the samples obtained from the Latin hypercube sampling technique. The new method may be very useful in designing important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored.