• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.201-201
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• 2003

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.692-701
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• 2019

Recently, instrumentation and control (I&C) systems in nuclear power plants have undergone digitalization. Owing to the unique characteristics of digital I&C systems, the reliability analysis of digital systems has become an important element of probabilistic safety assessment (PSA). In a reliability analysis of digital systems, fault-tolerant techniques and their effectiveness must be considered. A fault injection experiment was performed on a safety-critical digital I&C system developed for nuclear power plants to evaluate the effectiveness of fault-tolerant techniques implemented in the target system. A software-implemented fault injection in which faults were injected into the memory area was used based on the assumption that all faults in the target system will be reflected in the faults in the memory. To reduce the number of required fault injection experiments, the memory assigned to the target software was analyzed. In addition, to observe the effect of the fault detection coverage of fault-tolerant techniques, a PSA model was developed. The analysis of the experimental result also can be used to identify weak points of fault-tolerant techniques for capability improvement of fault-tolerant techniques

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.22-27
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• 1990

Since an eigenvalue problem in structural analysis has been recognized as an important process for the assessment of structural strength, it is usually to be carried out the eigenvalue analysis or buckling analysis of structures when the compression behabiour of the member is dorminant. In general, various variables involved in the eigenvalue problem have also shown their variability. So it is natural to apply the probabilistic analysis into such problem. Since the limit state equation for the eigenvalue analysis or buckling reliability analysis is expressed implicitly in terms of random variables involved, the probabilistic finite element method is combined with the conventional reliability method such as MVFOSM and AFOSM for the determination of probability of failure due to buckling. The accuracy of the results obtained by this method is compared with results from the Monte Carlo simulations. Importance sampling method is specially chosen for overcomming the difficulty in a large simulation number needed for appropriate accurate result. From the results of the case study, it is found that the method developed here has shown good performance for the calculation of probability of buckling failure and could be used for checking the safety of the calculation of probability of buckling failure and could be used for checking the safely of frame structure which might be collapsed by either yielding or buckling.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.349-359
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• 2017

During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models.

• Journal of the Korean Society of Safety
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• v.34 no.3
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• pp.102-110
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• 2019

This paper describes the work and results of the preliminary Probabilistic Safety Assessment (PSA) for a research reactor in the design phase. This preliminary PSA was undertaken to assess the level of safety for the design of a research reactor and to evaluate whether it is probabilistically safe to operate and reliable to use. The scope of the PSA described here is a Level 1 PSA which addresses the risks associated with core damage. After reviewing the documents and its conceptual design, eight typical initiating events are selected regarding internal events during the normal operation of the reactor. Simple fault tree models for the PSA are developed instead of the detailed model at this conceptual design stage. A total of 32 core damage accident sequences for an internal event analysis were identified and quantified using the AIMS-PSA. LOCA-I has a dominant contribution to the total CDF by a single initiating event. The CDF from the internal events of a research reactor is estimated to be 7.38E-07/year. The CDF for the representative initiating events is less than 1.0E-6/year even though conservative assumptions are used in reliability data. The conceptual design of the research reactor is designed to be sufficiently safe from the viewpoint of safety.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.981-988
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• 2023

A seismic event caused an accident at the Fukushima Nuclear Power Plant, which further resulted in simultaneous accidents at several units. Consequently, this incident has aroused great interest in the safety of nuclear power plants worldwide. A reasonable safety evaluation of such an external event should appropriately consider the correlation between SSCs (structures, systems, and components) and the probability of failure. However, a probabilistic safety assessment in current nuclear industries is performed conservatively, assuming that the failure correlation between SSCs is independent or completely dependent. This is an extreme assumption; a reasonable risk can be calculated, or risk-based decision-making can be conducted only when the appropriate failure correlation between SSCs is considered. Thus, this study analyzed the effect of the failure correlation of SSCs on the safety of the system to realize rational safety assessment and decision-making. Consequently, the impact on the system differs according to the size of the failure probability of the SSCs and the AND and OR conditions.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2221-2229
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• 2020

After the Fukushima Daiichi nuclear power plant (NPP) accident, level 3 probabilistic safety assessment (PSA) has emerged as an important task in order to assess the risk level of the multi-unit NPPs in a single nuclear site. Accurate calculation of the radionuclide concentrations and exposure doses to the public is required if a nuclear site has multi-unit NPPs and large number of people live near NPPs. So, there has been a great need to develop a new method or procedure for the fast and accurate offsite consequence calculation for the multi-unit NPP accident analysis. Since the multi-unit level 3 PSA is being currently performed assuming that all the NPPs are located at the same position such as a center of mass (COM) or base NPP position, radionuclide concentrations or exposure doses near NPPs can be drastically distorted depending on the locations, multi-unit NPP alignment, and the wind direction. In order to overcome this disadvantage of the COM method, the idea of a new multiple location (ML) method was proposed and implemented into a new tool MURCC (multi-unit radiological consequence calculator). Furthermore, the MURCC code was further improved for the multi-unit level 3 PSA that has the arbitrary number of multi-unit NPPs. The objectives of this study are to (1) qualitatively and quantitatively compare COM and ML methods, and (2) demonstrate the strength and efficiency of the ML method. The strength of the ML method was demonstrated by the applications to the multi-unit long-term station blackout (LTSBO) accidents at the four-unit Vogtle NPPs. Thus, it is strongly recommended that this ML method be employed for the offsite consequence analysis of the multi-unit NPP accidents.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.5
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• pp.319-325
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• 2021

The 2011 East Japan Earthquake caused accidents at a number of nuclear power plants in Fukushima, highlighting the need for a study on the seismic safety of multiple NPP (Nuclear Power Plant) units. In the case of nuclear power plants built on a site that shows a similar seismic response, there is at least a correlation between the seismic damage of structures, systems, and components (SSCs) of nuclear power plants. In this study, a probabilistic seismic safety assessment was performed for the loss of essential power events of twin units. To derive an appropriate seismic damage correlation coefficient, a probabilistic seismic response analysis was performed. Using the external event mensuration system program, we analyzed the seismic fragility and seismic risk by composing a failure tree of multiple loss of essential power events. Additionally, a comparative analysis was performed considering the seismic damage correlation between SSCs as completely independent and completely dependent.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1871-1880
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• 2020

Round robin analyses for vessel failure probabilities due to PTS events are proposed for plant-specific analyses of all types of reactors developed in Korea. Four organizations, that are responsible for regulation, operation, research and design of the nuclear power plant in Korea, participated in the round robin analysis. The vessel failure probabilities from the probabilistic fracture mechanics analyses are calculated to assure the structural integrity of the reactor pressure vessel during transients that are expected to initiate PTS events. The failure probabilities due to various parameters are compared with each other. All results are obtained based on several assumptions about material properties, flaw distribution data, and transient data such as pressure, temperature, and heat transfer coefficient. The realistic input data can be used to obtain more realistic failure probabilities. The various results presented in this study will be helpful not only for benchmark calculations, result comparisons, and verification of PFM codes developed but also as a contribution to knowledge management for the future generation.

• Journal of the Korean Geotechnical Society
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• v.32 no.11
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• pp.31-42
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• 2016

Usually the seismic stability analysis of slope uses the pseudostatic analysis considering the inertial force by the earthquake as a static load. Geostructures such as slope include the uncertainty of soil properties. Therefore, it is necessary to consider probabilistic method for stability analysis. In this study, the probabilistic stability analysis of slope considering the uncertainty of soil properties has been performed. The fragility curve that represents the probability of exceeding limit state of slope as a function of the ground motion has been established. The Monte Carlo Simulation (MCS) has been implemented to perform the probabilistic stability analysis of slope with pseudostatic analysis. A procedure to develop the fragility curve by the pseudostatic horizontal acceleration has been presented by calculating the probability of failure based on the Artificial Neural Network (ANN) based response surface technique that reduces the required time of MCS. The results showed that the proposed method can get the fragility curve that is similar to the direct MCS-based fragility curve, and can be efficiently used to reduce the analysis time.