• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.172-178
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• 2014

In terms of an accident management, the cases causing severe core damage need to be analyzed and arranged systematically for an easy access to the results since the Three Mile Island (TMI) accident. The objectives of this paper are to explain how to identify the plant response and cope with its vulnerabilities using the probabilistic safety assessment (PSA) quantified results and severe accident database SARDB(Severe Accident Risk Data Bank) based on sequences analysis results. Although PSA has been performed for the Korean Standard Power Plants (KSNPs), and that it considered the necessary sequences for an assessment of the containment integrity. The developed Database (DB) system includes a graphical display for a plant and equipment status, previous research results by a knowledge-based technique, and the expected plant behaviour. The plant model used in this paper is oriented to the cases of loss of coolant accident (LOCA) is be used as a training simulator for a severe accident management.

• Journal of the Korean Society of Safety
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• v.27 no.5
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• pp.224-228
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• 2012

According to the results of Probabilistic Safety Assessment(PSA) for a Nuclear Power Plant(NPP), an Emergency Power Supply(EPS) system has been considered as one of the most important safety system. Especially, the interests in the reliability of the EPS system have been increased after the severe accidents of Fukushima Daiichi. Firstly, we performed the risk assessment and the importance analysis of the EPS system based on the PSA models of the reference plant, which is the Korean standard NPP type. Considering a portable Diesel Generator(DG) system as the reliability reinforcement of the EPS system, we modified the PSA models and performed the risk impact assessment and the importance analysis. Although the reliability of the potable DG could be about 20% of the reliability of the alternative AC DG, we identified that Core Damage Frequency(CDF) was decreased by at least 4.6%. In addition, the risk impacts due to the unavailability of the EPS system on CDF were decreased.

• Earthquakes and Structures
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• v.14 no.5
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• pp.437-447
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• 2018

Computational cost is one of the major obstacles for detailed risk analysis of structures. This paper puts forward a methodology for efficient probabilistic seismic loss assessment of structures using the Endurance Time (ET) analysis and the first-order reliability method (FORM). The ET analysis efficiently yields the structural responses for a continuous range of intensities through a single response-history analysis. Taking advantage of this property of ET, FORM is employed to estimate the annual rate of exceedance for the loss components. The proposed approach is an amalgamation of two analysis approaches, ET and FORM, that significantly lower the computational costs. This makes it possible to evaluate the seismic risk of complex systems. The probability distribution of losses due to the structural and non-structural damage as well as injuries and fatalities of a prototype structure are estimated using the proposed methodology. This methodology is an alternative to the prevalent risk analysis framework of the total probability theorem. Hence, the risk estimates of the proposed approach are compared with those from the total probability theorem as a benchmark. The results indicate a satisfactory agreement between the two methods while a significantly lower computational demand for the proposed approach.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.1
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• pp.63-70
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• 2017

Release of hazardous and flammable gas is a significant contributor to risk. The ignition of flammable gas clouds can lead to explosion accidents in the offshore installations. A gas detector, which is one of active protect systems, brings the module into a safe state through emergency shut down processes and reduces the damage by eliminating the dangerous releases. It is critical to understand the gas release, the wind field, and the complex geometry of installations to determine gas detector placement. In this paper, the Gas detector Location Index (GLI) which is a novel index for optimal detector location determination to efficiently prevent explosion accident using probabilistic approach.

• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.126-135
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• 2000

Probabilistic Safety Assessment (PSA) is an engineering analysis method to identify possible contributors to the risk from a nuclear power plant and now it has become a standard tool in safety evaluation of nuclear power plants. PSA consists of three phases named as Level 1, 2 and 3. Level 2 PSA, mainly focused in this paper, uses a step-wise approach. At first, plant damage states (PDSs) are defined from the Level 1 PSA results and they are quantified. Containment event tree (CET) is then constructed considering the physico-chemical phenomena in the containment. The quantification of CET can be assisted by a decomposition event tree (DET). Finally, source terms are quantitatively characterized by the containment failure mode. As the main benefit of PSA is to provide insights into plant design, performance and environmental impacts, including the identification of the dominant risk contributors and the comparison of options for reducing risk, this technique is expected to be applied to the industrial safety area.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.192-192
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• 2008

As the lifetime of nuclear power plants (NPPs) reaches design life, the probability for fatal accidents increases. Most of accidents are known to be caused by degradation of mechanical components. Pressure tubes are the most important components in CANDU reactor. They are subjected to various aging mechanisms such as delayed hydride cracking (DHC), irradiation and corrosion, etc. Therefore, the integrity of pressure tube is key concern in CANDU reactor. Up to recently, conventional deterministic approaches have been utilized to evaluate the integrity of components. However, there are many uncertainties to prevent a rational evaluation. The objective of this paper is to assess the failure probability of pressure tube in CANDU. To do this, probability fracture mechanics (PFM) analysis based on the Genetic Algorithm (GA) is performed. For the verification of the analysis, a comparison of the PFM analysis using a commercial code and mathematical method is carried out.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.6
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• pp.488-494
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• 2014

Rocket Plumes can cause serious damage to launch vehicles and adjacent structures. This paper describes the impact of an adjacent structure by a rocket plume. Each parameter related with dynamic behavior of a missile is modeled with probabilistic distributions of variables. Flyout analyses of initial behavior of a vertically launched missile are performed using Monte-Carlo simulation and flow-motion analyses were conducted by using CFD. In this way, when a missile is fired by a ship, the impact of an adjacent structure by a rocket plume was analyzed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.6
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• pp.2559-2565
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• 2013

Material of boat hull has been used mainly with FRP composite materials until now. FRP boat hull manufacturing began to be restricted after the 2000's under international regulation on ocean environment safety. Shipyard on a small scale has manufactured polyethylene canoe and kayak hulls. Polyethylene has the melting point lower than the existing hull materials. Thermal stress occurs on outer hull surface when the polyethylene boat hull is exposed to sunlight. If it happens everyday, boat hull undergoes fatigue damage due to thermal fatigue. Therefore, this study presents the statistical fatigue life estimation on the HDPE boat hull subject to repeated thermal stress under three point bending condition.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.259-264
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• 2005

This paper presents a vital area identification (VAI) method based on the current fault tree analysis (FTA) and probabilistic safety assessment (PSA) techniques for the physical protection of nuclear power plants. A structured framework of a top event prevention set analysis (TEPA) application to the VAI of nuclear power plants is also delineated. One of the important processes for physical protection in a nuclear power plant is VAI that is a process for identifying areas containing nuclear materials, structures, systems or components (SSCs) to be protected from sabotage, which could directly or indirectly lead to core damage and unacceptable radiological consequences. A software VIP (Vital area Identification Package based on the PSA method) is being developed by KAERI for the VAI of nuclear power plants. Furthermore, the KAERI fault tree solver FTREX (Fault Tree Reliability Evaluation eXpert) is specialized for the VIP to generate the candidates of the vital areas. FTREX can generate numerous MCSs for a huge fault tree with the lowest truncation limit and all possible prevention sets.

• Structural Engineering and Mechanics
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• v.72 no.1
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• pp.31-41
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• 2019

Structural integrity assessment of piping components is of paramount important for remaining life prediction, residual strength evaluation and for in-service inspection planning. For accurate prediction of these, a reliable fracture parameter is essential. One of the fracture parameters is stress intensity factor (SIF), which is generally preferred for high strength materials, can be evaluated by using linear elastic fracture mechanics principles. To employ available analytical and numerical procedures for fracture analysis of piping components, it takes considerable amount of time and effort. In view of this, an alternative approach to analytical and finite element analysis, a model based on relevance vector machine (RVM) is developed to predict SIF of part through crack of a piping component under fatigue loading. RVM is based on probabilistic approach and regression and it is established based on Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Model for SIF prediction is developed by using MATLAB software wherein 70% of the data has been used for the development of RVM model and rest of the data is used for validation. The predicted SIF is found to be in good agreement with the corresponding analytical solution, and can be used for damage tolerant analysis of structural components.