• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.15-30
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• 2000

This study is to develop the applied method of reliability analysis to present risk - initial water level relationship in the small reservoir. To determine the reliability, the grasping of uncertainty sources is prerequisited and performance function is formulated. Reliability analysis method is a statistical method and the basic procedure of risk evaluation for overtopping of reservoir is as follows. 1. Define the risk criterion and performance function for the overtopping. 2. Determine the uncertainties of all the variables in the performance function. 3. Perform the risk analysis with suitable risk calculation method. Reliability analysis method such as Monte Carlo simulation(MCS) method and mean value first order second moment(MVFOSM) method are used to calculate the risk for reservoir. Finally, risk - initial water level relationship is established according to return period and it is useful for reservoir operation and safety assessment.ssment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.302-310
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• 2018

Despite the accident rate for fishing vessels accounts for 70% of all maritime accidents, few studies on such accidents have been done and most of the them mainly focus on causes and mitigation policies to reduce that accident rate. Thus, this risk analysis on sea accidents is the first to be performed for the successful and efficient implementation of accident reducing measures. In risk analysis, risk is calculated based on the combination of frequency and the consequence of an accident, and is usually expressed as a single number. However, there exists uncertainty in the risk calculation process if one uses a limited number of data for analysis. Therefore, in the study we propose a probabilistic simulation method to forecast risk not as a single number, but in a range of possible risk values. For the capability of the proposed method, using the criteria with the ALARP region, we show the possible risk values spanning across the different risk regions, whereas the single risk value calculated from the existing method lies in one of the risk regions. Therefore, a decision maker could employ appropriate risk mitigation options to handle the risks lying in different regions. For this study, we used fishing vessel accident data from 1988 to 2016.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.9-17
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• 2019

In order to deal with high uncertainty and variability in emergency medical centers, many researchers have developed various models for their operational planning and scheduling. However, most of the models just provide static plans without any risk measures as their results, and thus the users often lose the opportunity to analyze how much risk the patients have, whether the plan is still implementable or how the plan should be changed when an unexpected event happens. In this study, we construct a simulation model combined with a risk-based planning and scheduling module designed by Simio LLC. In addition to static schedules, it provides possibility of treatment delay for each patient as a risk measure, and updates the schedule to avoid the risk when it is needed. By using the simulation model, the users can experiment various scenarios in operations quickly, and also can make a decision not based on their past experience or intuition but based on scientific estimation of risks even in urgent situations. An example of such an operational decision making process is demonstrated for a real mid-size emergency medical center located in Seoul, Republic of Korea. The model is designed for temporal short-term planning especially, but it can be expanded for long-term planning also with some appropriate adjustments.

• Food Science and Biotechnology
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• v.16 no.3
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• pp.361-366
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• 2007

As the application of quantitative risk assessment (QRA) to food safety becomes widespread, it is now being questioned whether experimental results and simulated results coincide. Therefore, this paper comparatively analyzed experimental data and simulated data of the cross contamination, which needs summation of the simplest calculations in QRA, of chicken by Monte Carlo simulation and fuzzy math computation. In order to verify summation, the following basic operation was performed. For the experiment, thigh, breast, and a mixture of both parts were preserved for 24 hr at $20^{\circ}C$, and then the cell number of Salmonella spp. was measured. In order to examine the differences between experimental results and simulated results, we applied the descriptive statistics. The result was that mean value by fuzzy math computation was more similar to the experimental than that by Monte Carlo simulation, whereas other statistical descriptors by Monte Carlo simulation were more similar.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.929-934
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• 2005

The complex and dynamic job nature and the ever-changing working environment of construction projects inevitably present uncertainties to construction operations. Identification, evaluation and control of uncertainties constitute main elements of risk management and critical tasks of project management in construction. This paper is focused on application of a simplified discrete-event simulation approach in management of schedule-overrun risks, each being the combination of the occurrence probability of an uncertain interruptive factor and its potential consequence in terms of time delay. A case study observed from a concreting operation in Hong Kong is converted into a simulation model and analyzed with an in-house-developed simulation package for demonstrating how the proposed approach can be implemented to manage multiple schedule-overrun risks on construction projects.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.139-147
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• 2023

As heavy precipitation rates have increased due to climate change, the risk of landslides has also become greater. Studies in the field of disaster risk assessment predominantly focus on evaluating intrinsic importance represented by the use or role of facilities. This work, however, focused on evaluating risks according to the external conditions of facilities, which were presented via debris flow simulation. A random walk model (RWM) was partially improved and used for the debris flow simulation. The existing RWM algorithm contained the problem of the simulation results being overly concentrated on the maximum slope line. To improve the model, the center cell height was adjusted and the inertia application method was modified. Facility information was collected from a digital topographic map layer. The risk level of each object was evaluated by combining the simulation result and the digital topographic map layer. A risk assessment technique suitable for the polygon and polyline layers was applied, respectively. Finally, by combining the evaluated risk with the attribute table of the layer, a system was prepared that could create a list of objects expected to be damaged, derive various statistics, and express the risk of each facility on a map. In short, we used an easy-to-understand simulation algorithm and proposed a technique to express detailed risk information on a map. This work will aid in the user-friendly development of a debris flow risk assessment system.

• Child Health Nursing Research
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• v.21 no.2
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• pp.98-106
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• 2015

Purpose: This study was done to develop and evaluate an algorithm-based simulation scenario for emergency measures for high-risk newborns presenting with apnea. Methods: A one shot case study design was used to evaluate the algorithm-based simulation scenario. Effects of the developed simulation scenario were evaluated using the Simulation Effectiveness Tool (SET) and the Lasater Clinical Judgement Rubric (LCJR). From March to November 137 senior nursing students completed the simulation using this scenario. Results: The eight-frame simulation scenario was developed based on the Neonatal Resuscitation Program (NRP) and the nursing clinical judgment process. After use of the scenario, overall scores for SET and LCJR were 21.0 out of 26.0 and 32.4 out of 44.0 respectively. There were no significant differences in scores according to general characteristics. Positive correlation coefficients were identified among overall and subcategories of SET and LCJR. In addition, students provided positive feedback on the simulation experience. Conclusion: Considering that nursing students have limited access to high-risk newborns during their clinical experience and that newborns presenting apnea are common in the neonatal intensive care unit, the simulation scenario developed in this study is expected to provide nursing students with more opportunities to practice emergency measures for high-risk newborns.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.9-16
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• 2016

The project schedule risk in the engineering and facility construction industry is increasingly considered as important management factor because the risks in terms of schedule or deadline may significantly affect the project cost. Especially, the project-based operating companies attempt to find the best estimate of the project completion time for use at their proposals, and therefore, usually have much interest in accurate estimation of the duration of the projects. In general, the management of projects schedule risk is achieved by modeling project schedule with PERT/CPM techniques, and then performing risk assessment with simulation such as Monte-Carlo simulation method. However, since these approaches require the accumulated executional data, which are not usually available in project-based operating company, and, further, they cannot reflect various schedule constraints, which usually are met during the project execution, the project managers have difficulty in preparing for the project risks in advance of their occurrence in the project execution. As these constraints may affect time and cost which role as the crucial evaluation factors to the quality of the project result, they must be identified and described in advance of their occurrence in the project management. This paper proposes a Bayesian Net based methodology for estimating project schedule risk by identifying and enforcing the project risks and its response plan which may occur in storage tank engineering and construction project environment. First, we translated the schedule network with the project risks and its response plan into Bayesian Net. Second, we analyzed the integrated Bayesian Net and suggested an estimate of project schedule risk with simulation approach. Finally, we applied our approach to a storage tank construction project to validate its feasibility.

• 한국방재학회:학술대회논문집
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• 2009.02b
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• pp.13-24
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• 2009

This paper introduces various kinds of applications of the scenario-based seismic risk assessment in Taiwan. Seismic scenario simulation (SSS) is a GIS-based technique to assess distribution of ground shaking intensity, soil liquefaction probability, building damages and associated casualties, interruption of lifeline systems, economic losses, etc. given source parameters of an earthquake. The SSS may integrate with rapid earthquake information release system to obtain valuable information and to assist in decision-making processes to dispatch rescue and medical resources efficiently. The SSS may also integrate with probabilistic seismic hazard analysis to evaluate various kinds of risk estimates, such as average annual loss and probable maximum loss in one event, in a probabilistic sense and to help proposing feasible countermeasures.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.136-144
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• 2013

An extensive real world in-depth crash accident data is needed to make a precise occupant injury risk prediction at crash accidents which might be a critical information from the scene of the accident in ACNS(Automatic Crash Notification System). However it is rather unfortunate that there is no such a domestic database unlike other leading countries. Therefore we propose a numerical method, i.e., crash simulation using a sled model to make a virtual database that can substitute car crash database in real world. The proposing crash injury risk prediction is validated against a limited domestic crash accident data.