• Korean Chemical Engineering Research
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• v.47 no.2
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• pp.248-257
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• 2009

In this paper, human exposure and risk of environmental pollutants were predicted using an emission assessment model and multimedia fate model. Eight environmental pollutants, acetaldehyde, acrylonitrile, aniline, benzene, carbon tetrachloride, dichloromethane, formaldehyde and vinyl chloride, were selected for the risk assessment in an urban and industrial area in Korea. The emission rate of target pollutants were estimated after considering a variety of point and non-point emission sources including geographical information. A spatially refined multimedia fate model was applied to predict the environmental concentration and fate of pollutants. Hazard data of target materials were obtained from the IRIS(Integrated Risk Information System) database. Using the modeling results with hazard data, the human risks were assessed. Modeling results demonstrate that the considerable risks were observed for several pollutants.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.53-58
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• 2021

Nuclear power plant's safety against seismic events is evaluated as risk values by probabilistic seismic safety assessment. The risk values vary by the seismic failure correlation between the structures, systems, and components (SSCs). However, most probabilistic seismic safety assessments idealized the seismic failure correlation between the SSCs as entirely dependent or independent. Such a consideration results in an inaccurate assessment result not reflecting real physical phenomenon. A nuclear power plant's seismic risk should be calculated with the appropriate seismic failure correlation coefficient between the SSCs for a reasonable outcome. An accident scenario that has an enormous impact on a nuclear power plant's seismic risk was selected. Moreover, the probabilistic seismic response analyses of a nuclear power plant were performed to derive appropriate seismic failure correlations between SSCs. Based on the analysis results, the seismic failure correlation coefficient between SSCs was derived, and the seismic fragility curve and core damage frequency of the loss of essential power event were calculated. Results were compared with the seismic fragility and core damage frequency of assuming the seismic failure correlations between SSCs were independent and entirely dependent.

• Spatial Information Research
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• v.23 no.2
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• pp.39-48
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• 2015

In this study, we evaluated flood risk by applying calculation fomula considering practical risk calculated by inundation analysis information through 2D inundation analysis, suggested a plan that provides a standardized information system. Generally, we evaluated flood risk to people and classified four degrees by using inundation depth, velocity, Debris Factor and Flood Hazard Rating relationship because current flood risk assessment method based inundation depth and area was considered to not fully reflect the actual risk to people on flood. We simulated overflow and levee break scenarios according to 500 year and 200 year floods, respectively, by using Flumen which is a 2D flood inundation model for Geumho river basin in Daegu. The result of this study could contribute to inform practical risk information to people in expected flood area. This study can be useful for the fields of disaster estimatingsuch as information analysis, evaluation, planning by offering Risk information based on standardized information system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.54
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• pp.167-177
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• 2000

The problem of system reliability is very important issue in the nuclear power plant, because the failure of its system brings about extravagant economic loss, environment destruction, and quality loss. This paper therefore proposes a normalized scoring model by the qualitative factors order to evaluate the robust reliability of nuclear power plants under uncertainty. Especially, the qualitative factors including risk, functional, human error, and quality function factors for the robust justification has been also introduced. Finally, the analytical reliability and safety assessment model developed in this paper can be used in the real nuclear power plant.

• Journal of Energy Engineering
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• v.27 no.2
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• pp.1-13
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• 2018

The proportion of natural gas-fueled power generation is expanding due to the change of domestic energy policy pursuing reduction of dust and increasing clean energy consumption. Natural gas fuels used for the combined-cycle power plants and the district-heating power plants are operated at high temperature and high pressure in the fuel supply system. Accidents due to leakage of the gas such as fire and explosion should be prevented by applying risk management techniques. In this study, risk assessment was performed on the natural gas fuel supply system of a combined power plant based on the API RP 581 RBI code. For the application of the API RBI code, lines and segments of the evaluation target system were identified. Operational data and input information were analyzed for the calculations of probability of failure and consequence of failure. The results of the risk assessment were analyzed over time from the initial installation time. In the code-based evaluation, the gas fuel supply system was mainly affected by thinning, external damage, and mechanical fatigue damage mechanisms. As the operating time passes, the risk is expected to increase due to the external damage caused by the CUI(Corrosion Under Insulation).

• Journal of the Korean Institute of Gas
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• v.16 no.1
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• pp.39-45
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• 2012

While the natural gas supply industry has continuously been growing, its potential hazard has also risen since the natural gas facilities essentially require installations that carry highly flammable and pressurized gas close to the populated areas, posing a serious consequence of significant property damage as well as human casualties in the event of accident. Therefore Quantitative Risk Assessment (QAR) has been recognized as a appropriate method to reduce the risk as far as possible, considering the reality of unachievable zero-risk. However, it is hard to perform effective QRA on hundreds of gas facilities because of insufficient number of expert and long-term analysis. In this paper, we suggest a conceptual QRA system framework to support more efficient risk analysis in gas supply facilities. In this system, the experts make questionnaires and internal calculation formula needed in accident frequency/consequence analysis of the facility through pre-analysis on the point of analysis, called incident point, and general users locate the point on the map and input the value required by the questionnaire to obtain the risk. Ultimately, this is suggested based on the idea that the specialization is available in QRA analysis process and the validity of the system is verified through actual system construction and application.

• Journal of Environmental Health Sciences
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• v.41 no.2
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• pp.102-115
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• 2015

Objectives: A learning organization was designed and implemented on the basis of the selection criteria and essential elements of knowledge translation theory. Methods: The learning organization was designed on the basis of biosafety harmonization criteria and risk management strategy and was implemented as the learning organization for biosafety management by the National Institute of Health, Korea Centers for Disease Control & Prevention. The effect of knowledge translation in the research institutions by evidence-based policy was verified. Results: The result of applying the knowledge translation theory involving all stakeholders showed a positive reaction in establishing and implementing biosafety management strategy and embodied risk assessment criteria and evoked sympathy with the necessity of learning and using of expert knowledge about risk assessment and risk management. All stakeholders initiated voluntarily action toward new human-network construction and communication between similar organizations. The learning organization's capability expanded the base of knowledge translation. Conclusion: These results showed that a learning organization could enhance the autonomous safety management system by diffusion of knowledge translation.

• The Journal of Industrial Distribution & Business
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• v.13 no.10
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• pp.1-8
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• 2022

Purpose: Support vector machines (SVMs) ensemble has been proposed to improve classification performance of Credit risk recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. To deal with this problem, this paper designs a support vector machines (SVMs) ensemble method based on fuzzy integral, which aggregates the outputs of separate component SVMs with importance of each component SVM. Research design, data, and methodology: This paper designs a personal credit risk evaluation index system including 16 indicators and discusses a support vector machines (SVMs) ensemble method based on fuzzy integral for designing a credit risk assessment system to discriminate good creditors from bad ones. This paper randomly selects 1500 sample data of personal loan customers of a commercial bank in China 2015-2020 for simulation experiments. Results: By comparing the experimental result SVMs ensemble with the single SVM, the neural network ensemble, the proposed method outperforms the single SVM, and neural network ensemble in terms of classification accuracy. Conclusions: The results show that the method proposed in this paper has higher classification accuracy than other classification methods, which confirms the feasibility and effectiveness of this method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.329-341
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• 2021

This study derives the risk-Influence factors for subway structures, the basis for the transition from the current subway disaster recovery-oriented maintenance system to a preemptive disaster management system, to reduce risk factors for existing subway structures. To apply reasonable risk assessment techniques, risk influence factors for subway underground structures using statistical information(spatial information) and risk influence factors according to frequency of accidents were selected to derive the risk factors. The significant risk factors were verified through ground subsidence (SI: Subsidence Impact)-based correlation analysis. This process confirmed that the subsidence of the ground was a risk influence factor for the subway structure. The main result of this study is that derive the risk factors to improve the risk factors of subway structures due to the rapid increase in disaster risk factors. The derived risk factors that were expected to affect the depression around subway stations and track structures did not show a noticeable correlation, but the cause of this may be that there is no physical connection between them, but on the other hand, the accumulated data may not accurately record the surrounding depression. Accordingly, in order to evaluate the risk of depression around the station and track, more intensive observation and data accumulation around the structure are required.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.129-136
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• 2023

In this paper, we describe a rule-based risk classification algorithm to perform Risk-based Inspection (RBI) on imported goods at customs. The RBI system is a method to automatically select which cargos have to be inspected and manage potential risks in boarder. In this study, we designed a rule-based risk classification algorithm for RBI solutions and implemented them using the Svelte web application framework. The risk classification algorithm proposed in this paper uses different indicative risk factors such as HS code, country of origin, importer's reliability, trade relationships, and logistics routes to classify cargos into Green, Yellow, and Red channels. To achieve this, we assigned risk categories to each risk factor and randomly generated risk scores within a specific range for each risk category. This system is expected to contribute to the increased efficiency of customs operations and protect public safety by minimizing the risk of imported hazardous materials.