• Nuclear Engineering and Technology
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• v.36 no.1
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• pp.112-120
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• 2004

The purpose of this paper is to analyze the piping failure frequency for the main feedwater system in domestic nuclear power plants(NPPs) for the application to an in-service inspection(ISI), leak before break(LBB) concept, aging management program(AMP), and probabilistic safety analysis(PSA). First, a database was developed for piping failure events in domestic NPPs, and 23 domestic piping failure events were collected. Among the 23 events, 12 locations of wall thinning due to flow accelerated corrosion(FAC) were identified in the main feedwater system in 4 domestic WH 3-loop NPPs. Two types of the piping failure frequency such as the damage frequency and rupture frequency were considered in this study. The damage frequency was calculated from both the plant population data and damage(s) including crack, wall thinning, leak, and/or rupture, while the rupture frequency was estimated by using both the well-known Jeffreys method and a new method considering the degradation due to FAC. The results showed that the damage frequencies based on the number of the base metal piping susceptible to FAC ranged from $1.26{\times}10^{-3}/cr.yr\;to\;3.91{\times}10^{-3}/cr.yr$ for the main feedwater system of domestic WH 3-loop NPPs. The rupture frequencies obtained from the Jeffreys method for the main feedwater system were $1.01{\times}10^{-2}/cr.yr\;and\;4.54{\times}10^{-3}/cr.yr$ for the domestic WH 3-loop NPPs and all the other domestic PWR NPPs respectively, while those from the new method considering the degradation were higher than those from the Jeffreys method by about an order of one.

• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.262-271
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• 2002

This study presents a practical procedure for the Bayesian inversion of geophysical data. We have applied geostatistical techniques for the acquisition of prior model information, then the Markov Chain Monte Carlo (MCMC) method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.2
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• pp.70-78
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• 2013

Plants which are having conditions of high temperature and pressure always are exposed to danger. In order to prevent unexpected accidents, safety management that can effectively and appropriately examine facilities is required in plant operation. RBI(Risk-Based Inspection) technology in API 581 is one of standard management technique for evaluating risk on petroleum plants. There are qualitative and quantitative assessments in RBI methodology. Quantitative evaluation step is complex and required much information, so high-risk facilities in plant are selected firstly by qualitative method. Qualitative RBI is performed by choosing the answer in prepared questionnaire. However, it is difficult to believe thoroughly results from survey including ambiguous information. In this study, the procedure of qualitative RBI analysis with considering probability distribution concept were proposed by using Monte Carlo simulation method in order to increase reliability in spite of uncertain factors. In addition, qualitative risk of cooling system for LNG plant was evaluated using proposed procedure. Although 20 items of total 39 assessment items are applied to uncertain factors, risk section of high probability(89%) were verified. The detailed results were described in manuscript.

• Korean Journal of Construction Engineering and Management
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• v.1 no.1 s.1
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• pp.63-71
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• 2000

The paper considers two non-deterministic methods of analysing the risk exposure in a cost estimate The fist method(referred to as the 'conventional statistical' method) analyses cost data directly, to describe a probability distribution for total cost. The second method(referred to as the 'Monte Carlo simulation' method) interprets cost data directly, to generate a probability distribution for total costs from the descriptions of elemental cost distribution. The common practice of allowing for risk through an all-embracing contingency sum or percentage addition is challenged. Rather than excluding conventional, non-deterministic methods, they are here presented as possibly the only of effective foundation on which to risk management in cost estimating.

• Journal of Environmental Health Sciences
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• v.39 no.1
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• pp.32-42
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• 2013

Objectives: Cryptosporidium, a protozoan parasite, has been recognized as a frequent cause of waterborne disease due to its extremely strong resistance against chlorine disinfection. Although there has as yet been no report of a Cryptosporidium outbreak through drinking water in Korea, it is important to estimate the health risk of Cryptosporidium in water supply systems because of the various infection cases in human and domestic animals and frequent detection reports on their oocysts in water environments. Methods: This study evaluated the annual infection risk of Cryptosporidium in tap water using the quantitative microbial risk assessment technique. Exposure assessment was performed upon the results of a national survey on Cryptosporidium on the water sources of 97 large-scale water purification plants in Korea, water treatment efficacy, and daily unboiled tap water consumption. The estimates of the US Environmental Protection Agency on the mean likelihood of infection from ingesting one oocyst were applied for effect assessment. Results: Using probabilistic methods, mean annual infection risk of Cryptosporidiosis by the intake of tap water was estimated to fall within the range of $2.3{\times}10^{-4}$ to $1.0{\times}10^{-3}$ (median $5.7{\times}10^{-4}$). The risk in using river sources was predicted to be four times higher than with lake sources. With 0.5-log higher removal efficacy, the risk was estimated to be $1.8{\times}10^{-4}$, and could then be lowered by one-third. Conclusions: These estimations can be compared with acceptable risk and then used to determine the adequacy and priority of various drinking water quality strategies such as the establishment of new treatment technology.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.475-485
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• 2017

This paper develops a conversion function and method transforming from daily peak load curve used $LOLE_D$ [days/year] to hourly load curve used $LOLE_H$[hours/year]and describes relationship between $LOLE_D$ [days/year] and $LOLE_H$ [hours/year]. The indices can not only be transformed just arithmetically but also have different characteristics physically because of using their different load curves. The conversion function is formulated as variables of capacity and forced outage rate of generator, hourly load daily load factor and daily peak load yearly load factor, etc. Therefore, the conversion function (${\gamma}={\varphi}$(.)) can not be simple. In this study, therefore, the function is formulated as linear times of separated two functions. One is an exponential formed conversion function of daily load factor. Another is formulated with an exponential typed conversion function of daily peak load yearly load factor. Futhermore, this paper presents algorithm and flow chart for transforming from $LOLE_D$[days/year] to $LOLE_H$[hours/year]. The proposed conversion function is applied to sample system and actual KPS(Korea Power System) in 2015. The exponent coefficients of the conversion functions are assessed using proposed method. Finally, assessment errors using conversion function for case studies of sample system and actual system are evaluated to certify the firstly proposed method.

• Journal of the Korean Society of Safety
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• v.35 no.5
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• pp.30-38
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• 2020

In order to construct a dam, the diversion facility such as cofferdam and a diversion tunnel should be installed in advance. And size of a cofferdam depends on type of a main dam. According to the Korea Dam Design Standard, if the main dam is a concrete dam, design flood of the cofferdam is 1~2 years flood frequency. This means that overflow of the cofferdam occurs one time for 1 or 2 years, therefore, stability of the cofferdam should be secured against any overflow problem. In this study, failure probability analysis for the concrete cofferdam is performed considering the overflow. First of all, limit state function of the concrete cofferdam is defined for overturning, sliding and base pressure, and upstream water levels are set as El. 501 m, El. 503 m, El. 505 m, El. 507 m. Also, after literature investigation research, probabilistic characteristics of various random variables are determined, the failure probability of the concrete cofferdam is calculated using the Monte Carlo Simulation. As a result of the analysis, when the upstream water level rises, it means overflow, the failure probability increases rapidly. In particular, the failure probability is largest in case of flood loading condition. It is considered that the high upstream water level causes increase of the upstream water pressure and the uplift pressure on the foundation. In addition, among the overturning, the sliding and the base pressure, the overturing is the major cause for the cofferdam failure considering the overflow.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.1-8
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• 2016

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.111-119
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• 2016

Rebound hammer test, SonReb method and concrete core test are most useful testing methods for estimate the concrete compressive strength of deteriorated concrete structures. But the accuracy of the NDE results on the existing structures could be reduced by the effects of the uncertainty of nondestructive test methods, material effects by aging and carbonation, and mechanical damage by drilling of core. In this study, empirical procedure for verifying the in-situ compressive strength of concrete is suggested through the probabilistic analysis on the 268 data of rebound and ultra-pulse velocity and core strengths obtained from 106 bridges. To enhance the accuracy of predicted concrete strength, the coefficients of core strength, and surface hardness caused by ageing or carbonation was adopted. From the results, the proposed equation by KISTEC and the estimation procedures proposed by authors is reliable than previously suggested equation and correction coefficient.

• Journal of the Korean Institute of Gas
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• v.21 no.3
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• pp.61-69
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• 2017

The commercial development of unconventional gas is pursued in North America because it is more feasible owing to the technology required to improve productivity. Shale reservoir have low permeability and gas production can be carried out through cracks generated by hydraulic fracturing. The decline rate during the initial production period is high, but very low latter on, there are significant variations from the initial production behavior. Therefore, in the prediction of the production rate using deterministic decline curve analysis(DCA), it is not possible to consider the uncertainty in the production behavior. In this study, production rate of the Eagle Ford shale is predicted by Arps Hyperbolic and Modified SEPD. To minimize the uncertainty in predicting the Estimated Ultimate Recovery(EUR), Monte Carlo simulation is used to multi-wells analysis. Also, kernel density function is applied to determine probability distribution of decline curve factors without any assumption.