• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.723-728
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• 2022

This study is a method for evaluating and quantifying driver's dangerous driving behavior. The quantification method calculates various driving information in real time after starting the vehicle operation such as the time that the vehicle has been continuously driven without a break, overspeed, rapid acceleration, and overspeed driving time. These quantified risk of driving behavior values can be individually provided as a safe driving index, or can be used to objectify the evaluation of a group of drivers on roads, or vehicle groups such as cargo/bus/passenger vehicles.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.2
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• pp.129-136
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• 2020

In this study, we develop a sampling-based seismic probabilistic risk assessment (SPRA) quantification technique that can accurately consider a partially dependent condition of component seismic fragility information. Specifically, the SPRA quantification method is proposed by combining the advantages of two representative methodologies: EPRI seismic fragility and JAERI seismic fragility input-based quantification. The most important feature of the proposed method is that it performs a SPRA using a sampling technique by transforming the EPRI seismic fragility input into JAERI seismic fragility input. When the proposed sampling-based approach was applied to an example of simple system and to a SPRA problem of a nuclear power plant, it was observed that the proposed method yields approximately similar system seismic fragility and seismic risk results as those of the exact solution. Therefore, it is believed that the approach proposed in this study can be used as a useful tool for accurately assessing seismic risks, considering the partial seismic dependence among the components; the existing SPRA method cannot handle such partial dependencies.

• Nuclear Engineering and Technology
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• v.44 no.5
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• pp.471-482
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• 2012

To assess the risk of nuclear power plant operation and to determine the risk impact of digital systems, there is a need to quantitatively assess the reliability of the digital systems in a justifiable manner. The Probabilistic Risk Analysis (PRA) is a tool which can reveal shortcomings of the NPP design in general and PRA analysts have not had sufficient guiding principles in modelling particular digital components malfunctions. Currently digital I&C systems are mostly analyzed simply and conventionally in PRA, based on failure mode and effects analysis and fault tree modelling. More dynamic approaches are still in the trial stage and can be difficult to apply in full scale PRA-models. As basic events CPU failures, application software failures and common cause failures (CCF) between identical components are modelled.The primary goal is to model dependencies. However, it is not clear which failure modes or system parts CCF:s should be postulated for. A clear distinction can be made between the treatment of protection and control systems. There is a general consensus that protection systems shall be included in PRA, while control systems can be treated in a limited manner. OECD/NEA CSNI Working Group on Risk Assessment (WGRisk) has set up a task group, called DIGREL, to develop taxonomy of failure modes of digital components for the purposes of PRA. The taxonomy is aimed to be the basis of future modelling and quantification efforts. It will also help to define a structure for data collection and to review PRA studies.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.100-106
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• 2015

A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This quantification generates fault tree solutions such as minimal cut sets, minimal path sets, or binary decision diagrams (BDDs), and then, calculates top event probability and importance measures. This paper presents a new linear time algorithm to detect modules of large fault trees. It is shown through benchmark tests that the new method proposed in this study can very quickly detect the modules of a huge fault tree. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants.

• Earthquakes and Structures
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• v.22 no.1
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• pp.83-94
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• 2022

In recent years, some studies have identified and quantified factors that can increase or decrease the seismic vulnerability of buildings. These modifier factors, related to the building characteristics and condition, are taken into account in the vulnerability assessment, by means of a numerical estimation resulting from the quantification of these modifiers through vulnerability indexes. However, views have differed on the definition and the quantification of modifiers. In this study, modifier parameters and scores of the Risk-UE Level 1 method are adjusted based on the Algerian seismic code recommendations and the reviews proposed in the literature. The adjusted modifiers and scores are applied to reinforced concrete (RC) buildings in Boumerdes city, in order to assess probable seismic damage. Comparison between estimated damage and observed damage caused by the 2003 Boumerdes earthquake is done, with the objective to (i) validate the model involving influence of the modifier parameters on the seismic vulnerability, and (ii) to define the relationship between modifiers and damage. This research may help planners in improving seismic regulations and reducing vulnerability of existing buildings.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.249-250
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• 2023

The vulnerability factor analysis and risk quantification model for aging buildings presented in this study can be utilized by governmental agencies such as the Facility Safety Foundation, the Ministry of Land, Infrastructure and Transport, and various local governments. Policymakers can use this to supplement inadequacies in existing checklists, and it is expected that they can proactively prevent risks by evaluating dangers based on specific aging characteristics of buildings.

• Journal of Korean Society for Atmospheric Environment
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• v.8 no.2
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• pp.100-104
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• 1992

The research in this paper centers on a comparative risk assessment for nearby air pollution by carcinogenic metal emission from municipal solid waste incinerators. If a substance is identified as a potential human carcinogen, the carcinogenicity may be related to the chemical form of a substance and the route of exposure. This type of information with regard to carcinogenic uncertainty is incorporated into hazard quantification. In addition to the dioxin emission, the metal emission from municipal solid waste incineration is found to be a major contributor to human cancer risk via the inhalation route. The magnitude of risk by metals is about 5 times greater than that of risk by dioxins. Hexavalent form of chromium and cadmium compounds are major contributors to cancer risk from metal emission. In addition, hexavalent chromium is known to be human carcinogen while 2,3,7,8-TCDD is known to be only probable human carcinogen.

• Wind and Structures
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• v.13 no.2
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• pp.207-220
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• 2010

The 'chain reaction' effect of the interaction between wind pressure and windborne debris is likely to be a major cause of damage to residential buildings during severe wind events. The current paper (Part II) concerns the quantification of such pressure-debris interaction in an advanced vulnerability model that integrates the debris risk model developed in Part I and a component-based wind-pressure damage model. This vulnerability model may be applied to predict the cumulative wind damage during the passage of particular hurricanes, to estimate annual hurricane losses, or to conduct system reliability analysis for residential developments, with the effect of windborne debris fully considered.

• Korean Journal of Veterinary Research
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• v.47 no.2
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• pp.259-263
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• 2007

The choice of input distribution in quantitative risk assessments modeling is of great importance to get unbiased overall estimates, although it is difficult to characterize them in situations where data available are too sparse or small. The present study is particularly concerned with accommodation of uncertainties commonly encountered in the practice of modeling. The authors applied parametric and non-parametric bootstrap simulation methods which consist of re-sampling with replacement, in together with the classical Student-t statistics based on the normal distribution. The implications of these methods were demonstrated through an empirical analysis of trade volume from the amount of chicken and pork meat imported to Korea during the period of 1998-2005. The results of bootstrap method were comparable to the classical techniques, indicating that bootstrap can be an alternative approach in a specific context of trade volume. We also illustrated on what extent the bias corrected and accelerated non-parametric bootstrap method produces different estimate of interest, as compared by non-parametric bootstrap method.

• Journal of the Korean Society of Safety
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• v.8 no.2
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• pp.58-63
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• 1993

Recently, a large amount of flammable or explosive materials have been handled or stored in chemical industries. H the equipments fail or the materials release in consequence of operation errors, fire and explosion could occur to them. Thus, risk assessment using quantification of risks is very important when design of processes and modifications of installed processes are performed. The purpose of this study is to develop the program for fire and explosion index in order to quantify the expected damage of fire and explosion incidents in chemical plants, to identify equipment that would be likely to contribute to the creation or escalation of an incident, to comunicate the potential fire and explosion risk to management and to account of damage cost.