• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.201-217
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• 2015

In this paper, we report computational testing result to examine the validity of firm's bankruptcy risk estimation through quantification of supply chain risk. Supply chain risk in this study refers to upstream supply risk and downstream demand risk, To assess the firm's risk affected by supply chain risk, we adopt unit of analysis as industry level. since supply and demand relationships of the firm could be generalized by the industry input-output table and the availability of various valid economic indicators which are chronologically calculated. The research model to estimate firm's risk level is the linear regression model to assess the industry bankruptcy risk estimation of the focal firm's industry with the independent variables which could quantitatively reflect demand and supply risk of the industry. The publicly announced macro economic indicators are selected as the candidate independent variables and validated through empirical testing. To validate our approach, in this paper, we confined our research scope to steel industry sector and its related industry sectors, and implemented the research model. The empirical testing results provide useful insights to further refine the research model as the valid forecasting mechanism to capture firm's future risk estimation more accurately by adopting supply chain industry risk aspect, in conjunction with firm's financial and other managerial factors.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.665-676
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• 2017

Purpose: The purpose of this paper proposes an effective and systematic methods of risk management in product development project. Methods: This paper first discusses what risk factors be considered during product development period and then presented a model for preventive risk management. For that, this paper proposes how to evaluate the risk factors and risk events, and how to select prevention action for managing risk factors effectively. For this process, this paper uses well-known quality tools such as House of Quality (HOQ) and Failure Mode and Effects Criticality Analysis (FMECA) methods. Results: There is an inherent need for the development of robust risk management framework in order for product development projects to be successful. The identification and quantification of risk factors, risk events, and prevention actions can have significant effects on the success of a product development projects. Project managers can implement the proposed model to improve project success. Conclusion: The findings showed that this method would be effective for project managements in dealing with risk management issues in product development projects. This method presented would be an one of good guidelines for practitioners in the industry.

• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.292-309
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• 1987

A large dry PWR containment response analysis for postulated severe accidents was performed as part of the Zion Risk Rebaselining study for input to the U.S. NRC's "Reactor Risk Reference Document," NUREG-1150. The Methodologies used in the present work were developed as part of the Severe Accident Risk Reduction Program (SARRP) at Sandia National Laboratory specifically for the Surry Plant, but they were extrapolated to Zion. Major steps of the quantification of risk from a nuclear power plant are first outlined. Then, the methodologies of containment response analysis for severe accidents used for Zion are described in detail: major features of the containment event tree (CET) analysis codes and CET quantification procedures are summarized. In addition, plant specific features important to containment response analysis are presented along with the containment loading and performance issues included in the present uncertainty analysis. Finally, a brief summary of the results of deterministic and statistical containment event tree analysis is presented to provide a perspective on the large dry PWR containment response for postulated severe accidents.accidents.

• Journal of Environmental Impact Assessment
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• v.2 no.2
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• pp.59-71
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• 1993

Evaluation methods are employed in environmental impact assessment to choose between different project site, to determine the required measures to compensate impact and to decide whether the environmental impacts are more important than the social or economic effects of a project. The main obstacles that restrict use of quantitative evaluation method are a Lack of knowledge about the environmental effects (e.g. if impacts on wildlife or landscape amenities are predicted) and the relative importance of economic and social issues compared with nature conservation stability of ecosystem or landscape beauty. In Germany, the most common method for site planning is the "ecological risk analysis". It is a kind of multi-criteria-decision-method based on quantitative and qualitative description and ordinal ranking. The various kinds of "ecological balancing methods" that are more recently developed (within the last decade) to quantify the required amount for compensatory measures instead often use cardinal figures to express the value of ecosystems, the intensity of impacts, the need for additional measures to compensate for long recuperative periods when restoring ecosystems and so on. There are still only a view attempts to quantify decisions between environmental and socio-economic issues. Multicriteria-analysis as well as cost-benifit-analysis was used. Some new approaches which are still in a preliminary status are based on contingent valuation and on calculations for compensatory payments (instead of compensatory measures).

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.644-654
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• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1372-1386
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• 2018

Despite recent advances in multi-hazard analysis, the complexity and inherent nature of such problems make quantification of the landslide effect in a probabilistic safety assessment (PSA) of NPPs challenging. Therefore, in this paper, a practical approach was presented for performing an earthquake-induced landslide PSA for NPPs subject to seismic hazard. To demonstrate the effectiveness of the proposed approach, it was applied to Korean typical NPP in Korea as a numerical example. The assessment result revealed the quantitative probabilistic effects of peripheral slope failure and subsequent run-out effect on the risk of core damage frequency (CDF) of a NPP during the earthquake event. Parametric studies were conducted to demonstrate how parameters for slope, and physical relation between the slope and NPP, changed the CDF risk of the NPP. Finally, based on these results, the effective strategies were suggested to mitigate the CDF risk to the NPP resulting from the vulnerabilities inherent in adjacent slopes. The proposed approach can be expected to provide an effective framework for performing the earthquake-induced landslide PSA and decision support to increase NPP safety.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1132-1139
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• 2006

Railway risk is evaluated by a method of linking event trees and fault trees as the general PSA(Probabilistic Safety Assessment) model for the risk assessment of complex systems. Accident scenarios causing undesirable events are modeled by event trees comprised of several accident sequences. Each branch located in the accident progression of the event tree is modeled by an fault tree or can be represented by some value too simply. We usually evaluate the frequency of the whole sequence by adding them after calculating the frequency of each sequence at a time. However, since there are quite a number of event trees and fault trees in the railway risk assessment model, the number of sequence to evaluate increases and preparation for the risk assessment costs much time all the more. Also, it may induce errors when analysts perform the work of quantification. Therefore, the systematic maintenance and control of event trees and fault trees will be essential for the railway risk assessment. In this paper we introduce an integrated assessment method using one-top model and develop a risk assessment tool for the maintenance and control of the railway risk model.

• Nuclear Engineering and Technology
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• v.46 no.4
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• pp.481-488
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• 2014

An analysis of the uncertainty quantification related to LBLOCA using the Monte-Carlo calculation has been performed and compared with the tolerance level determined by the Wilks' formula. The uncertainty range and distribution of each input parameter associated with the LOCA phenomena were determined based on previous PIRT results and documentation during the BEMUSE project. Calulations were conducted on 3,500 cases within a 2-week CPU time on a 14-PC cluster system. The Monte-Carlo exercise shows that the 95% upper limit PCT value can be obtained well, with a 95% confidence level using the Wilks' formula, although we have to endure a 5% risk of PCT under-prediction. The results also show that the statistical fluctuation of the limit value using Wilks' first-order is as large as the uncertainty value itself. It is therefore desirable to increase the order of the Wilks' formula to be higher than the second-order to estimate the reliable safety margin of the design features. It is also shown that, with its ever increasing computational capability, the Monte-Carlo method is accessible for a nuclear power plant safety analysis within a realistic time frame.

• The Korean Journal of Food And Nutrition
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• v.35 no.6
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• pp.543-551
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• 2022

There has been increased interest in lignans due to their potential effect in reducing the risk of developing several diseases. To evaluate lignan contents, sensitive and accurate methods should be developed for their quantification in food. The present study aimed to validate a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the quantification of 5 lignans: lariciresinol (Lar), matairesinol (Mat), pinoresinol (Pin), secoisolariciresinol (Seco), and syringaresinol (Syr). The validation included selectivity, linearity, recovery, accuracy, and precision. The method was proved to be specific, with a linear response (R²≥0.99). The limits of detection were 0.040~0.765 ㎍/100 g and the limits of quantification were 0.114~1.532 ㎍/100 g. Recoveries were 90.588~109.053% for black sesame powder. Relative standard deviations of repeatability and reproducibility were below 5%. Total lignan contents of roasted coffee bean, oat, and blacksoy bean were 105.702 ㎍/100 g, 78.965 ㎍/100 g, and 165.521 ㎍/100 g, respectively. These results showed that LC-MS/MS analysis would be effective in producing acceptable sensitivity, accuracy, and precision in five lignan analyses.

• 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.