• Journal of Aerospace System Engineering
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• v.15 no.4
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• pp.64-74
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• 2021

Unmanned Aircraft Systems (UAS) are rapidly emerging not only as a key military power, such as surveillance and reconnaissance for military purposes but also as a new air transportation means in the form of Urban Air Mobility (UAM). Currently, airworthiness certification is carried out focused on the verification of technical standards for flight safety suitability of aircraft design in accordance with the Military Aircraft Flight Safety Certification Act and does not employ the model for operational risk assessment for mission areas and airspace. In this study, in order to evaluate the risk of the mission area from the perspective of the UAS operator, a risk assessment simulation has been conducted by applying the Specific Operations Risk Assessment (SORA) model to the operating environment of the Korean military UAS. Also, the validity of the SORA model has been verified through the analysis of simulation results, and a new application plan for airworthiness certification of the military unmanned aerial system has been presented.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.83-93
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• 2020

Bivariate measure of risk and error(BMORE) plot is originally designed to depict bivariate output data and related statistics obtained from a stochastic simulation such as sample mean, median, outliers, and a boundary of a certain percentile of simulation data. When compared to the static numbers, the plot has a big advantage in visualization that enables scholars and practitioners to understand the potential variability and risk in the simulation data. In this study, beyond just the construction of the plot to depict the variability of a certain system, we add a chance constraint to the plot and apply it for decision making such as checking the feasibility of systems, comparing performances of the systems on statistical background, and also analyzing the sensitivity of the problem parameters. In order to demonstrate an application of the plot, we employ an inventory management problem as an example. However, the techniques and algorithms suggested in this paper can be applied to any other problems comparing systems on bivariate performance measures with simulation/experiment results.

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.203-214
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• 2000

Health risk assessment is applied to streamlining LCA(Life Cycle Assessment) using Monte carlo simulation for probabilistic/stochastic exposure and risk distribution analysis caused by data variability and uncertainty. A case study was carried out to find benefits of this application. BTC(Benzene, Trichloroethylene, Carbon tetrachloride mixture alias) personal exposure cases were assumed as production worker(in workplace), manager(in office) and business man(outdoor). These cases were different from occupational retention time and exposure concentration for BTC consumption pattern. The result of cancer risk in these 3 scenario cases were estimated as $1.72E-4{\pm}1.2E+0$(production worker; case A), $9.62E-5{\pm}1.44E-5$(manger; case B), $6.90E-5{\pm}1.16E+0$(business man; case C), respectively. Portions of over acceptable risk 1.00E-4(assumed standard) were 99.85%, 38.89% and 0.61%, respectively. Estimated BTC risk was log-normal pattern, but some of distributions did not have any formal patterns. Except first impact factor(BTC emission quantity), sensitivity analysis showed that main effective factor was retention time in their occupational exposure sites. This case study is a good example to cover that LCA with probabilistic risk analysis tool can supply various significant information such as statistical distribution including personal/environmental exposure level, daily time activity pattern and individual susceptibility. Further research is needed for investigating real data of these input variables and personal exposure concentration and application of this study methodology.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.10a
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• pp.180-181
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.

• Journal of Navigation and Port Research
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• v.34 no.10
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• pp.727-733
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.

• Korean System Dynamics Review
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• v.16 no.3
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• pp.5-29
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• 2015

The importance of the concept of safety culture has increased in the security of high-risk facility after Chernobyl accident in 1986. This paper elaborated the concept of safety culture and its main factors by Causal Loop Diagram. Due to the decline of safety culture, the occurrence of incidents and accidents require more and more corrective actions to the members of high-risk facilities and thereby increasing their workloads. Employees who must complete the task within the given time have to have time pressures and don't comply with the rules and procedures. Also, a schedule pressure is a big stress for employees, causing mistakes in precision work. In order to improve these problems, CLD of the safety culture in this paper suggests hiring more workers, re-allocation of given workloads and strengthen the learning, communication capabilities and safety leadership. In addition, the two real accident cases were analyzed to test the feasibility of the System Dynamic simulation model through the process of structuring the fault trees on the stationary black out accident in Kori unit 1 in South Korea and Kleen Energy power station explosion in US. The simulation results show that the various safety factors cause the serious accident combined with mechanical failure and safety culture will reduce the possibility of the accidents in these high-risk organizations. This simulation model can contribute to analyzing the impact of the organizational and human factors of safety culture and can provide the alternatives in high-risk facilities.

• Environmental Analysis Health and Toxicology
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• v.10 no.1_2
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• pp.21-35
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• 1995

Risk assessment processes, which include processes for the estimation of human cancer potency using animal bioassay data and calculation of human exposure, entail uncertainties. In the exposure assessment process, exposure scenarios with various assumptions could affect the exposure amount and excess cancer risk. We compared risk estimates among various exposure scenarios of vinyl chloride, trichloroethylene and tetrachloroethylene in tap water. The contaminant concentrations were analyzed from tap water samples in Seoul from 1993 to 1994. The oral and inhalation cancer potencies of the contaminants were estimated using multistage, Weibull, lognormal, and Mantel-Bryan model in TOX-RISK computer software. In the first case, human excess cancer risk was estimated by the US EPA method used to set the MCL(maximum contaminant level). In the second and third case, the risk was estimated for multi-route exposure with and without adopting Monte-Carlo simulation, respectively. In the second case, exposure input parameters and cancer potencies used probability distributions, and in the third case, those values used point estimates(mean, and maximum or 95% upper-bound value). As a result, while the excess cancer risk estimated by US EPA method considering only direct ingestion tended to be underestimated, the risk which was estimated by considering multi-route exposure without Monte-Carlo simulation and then using the maximum or 95% upper-bound value as input parameters tended to be overestimated. In risk assessment for volatile organic compounds, considering multi-route exposure with adopting Monte-Carlo analysis seems to provide the most reasonable estimations.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.274-281
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• 2019

Objective: The objective of this study was to estimate the risk of Campylobacter jejuni (C. jejuni) infection from various jerky products in Korea. Methods: For the exposure assessment, the prevalence and predictive models of C. jejuni in the jerky and the temperature and time of the distribution and storage were investigated. In addition, the consumption amounts and frequencies of the products were also investigated. The data for C. jejuni for the prevalence, distribution temperature, distribution time, consumption amount, and consumption frequency were fitted with the @RISK fitting program to obtain appropriate probabilistic distributions. Subsequently, the dose-response models for Campylobacter were researched in the literature. Eventually, the distributions, predictive model, and dose-response model were used to make a simulation model with @RISK to estimate the risk of C. jejuni foodborne illness from the intake of jerky. Results: Among 275 jerky samples, there were no C. jejuni positive samples, and thus, the initial contamination level was statistically predicted with the RiskUniform distribution [RiskUniform (-2, 0.48)]. To describe the changes in the C. jejuni cell counts during distribution and storage, the developed predictive models with the Weibull model (primary model) and polynomial model (secondary model) were utilized. The appropriate probabilistic distribution was the BetaGeneral distribution, and it showed that the average jerky consumption was 51.83 g/d with a frequency of 0.61%. The developed simulation model from this data series and the dose-response model (Beta Poisson model) showed that the risk of C. jejuni foodborne illness per day per person from jerky consumption was $1.56{\times}10^{-12}$. Conclusion: This result suggests that the risk of C. jejuni in jerky could be considered low in Korea.

• Environmental and Resource Economics Review
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• v.9 no.4
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• pp.641-661
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• 2000

The study examines the relation between yield insurance and nitrogen fertilizer in Korea. Since the yield insurance has never been introduced in Korea, the simulation method developed by Babcock & Hennessy is used to see the effect. From the simulation, we obtained the following results: (1) When a farmer is assumed to have a risk-neutral utility function, the yield insurance reduces nitrogen fertilizer by 19.74% (2) When a farmer is assumed to have a risk-averse utility function, the yield insurance reduces nitrogen fertilizer by 24.53%.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.437-447
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• 2010

Spatial estimation of environmental variables has been regarded as an important preliminary procedure for decision-making. A minimum variance criterion, which has often been adopted in traditional kriging algorithms, does not always guarantee the optimal estimates for subsequent decision-making processes. In this paper, a geostatistical framework is illustrated that consists of uncertainty modeling via stochastic simulation and risk modeling based on loss functions for the selection of optimal estimates. Loss functions that quantify the impact of choosing any estimate different from the unknown true value are linked to geostatistical simulation. A hybrid loss function is especially presented to account for the different impact of over- and underestimation of different land-use types. The loss function-specific estimates that minimize the expected loss are chosen as optimal estimates. The applicability of the geostatistical framework is demonstrated and discussed through a case study of copper mapping.