• 한국안전학회지
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• 제39권3호
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• pp.75-83
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• 2024

Accurately assessing and managing risks in any endeavor is crucial. Risk assessment in engineering translates the abstract concept of risk into actionable strategies for systematic risk management. However, risk validation is met with significant skepticism, particularly concerning the uncertainty of probability. This study aims to address the aforementioned uncertainty in a multitude of ways. Firstly, instead of relying on deterministic probability, it acknowledges uncertainty and presents a probabilistic interval. Secondly, considering the uncertainty interval highlighted in OREDA, it delineates the bounds of the probabilistic interval. Lastly, it investigates how much explanatory power deterministic probability has within the defined probabilistic interval. By utilizing fault tree analysis (FTA) and integrating confidence intervals, a probabilistic risk assessment was conducted to scrutinize the explanatory power of deterministic probability. In this context, explanatory power signifies the proportion of probability within the probabilistic risk assessment interval that lies below the deterministic probability. Research results reveal that at a 90% confidence interval, the explanatory power of deterministic probability decreases to 73%. Additionally, it was confirmed that explanatory power reached 100% only with a probability application 36.9 times higher.

• 한국정밀공학회지
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• 제22권10호
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• pp.137-143
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• 2005

The integrity of steam generator tubes in nuclear power plant should be maintained sufficiently during operation. For sake of this, complicated assessment procedures are required such as fracture mechanics analysis, etc. The integrity assessment of tubes has been performed by using conventional deterministic approaches while there are many uncertainties to carry out a rational evaluation. In this respect, probabilistic integrity assessment is considered as an alternative method for integrity assessment. The objectives of this study are to develop an integrity assessment system based on probabilistic fracture mechanics and to predict the failure probability of steam generator tubes containing an axial through-wall crack. The developed integrity assessment system consists of three evaluation modules, which apply first order reliability method, second order reliability method and Monte Carlo simulation method, respectively. The system has been applied to predict failure probability of steam generator tubes and the estimation results showed a promising applicability of the probabilistic integrity assessment system.

• Journal of Computational Design and Engineering
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• 제1권4호
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• pp.266-271
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• 2014

The survivability of the naval ship is the capability of a warship to avoid or withstand a hostile environment. The survivability of the naval ship assessed by three categories (susceptibility, vulnerability and recoverability). The magnitude of susceptibility of a warship encountering with threat is dependent upon the attributes of detection equipment and weapon system. In this paper, as a part of a naval ship's survivability analysis, an assessment process model for the ship's susceptibility analysis technique is developed. Naval ship's survivability emphasizing the susceptibility is assessed by the probability of detection, and the probability of hit. Considering the radar cross section (RCS), the assessment procedure for the susceptibility is described. It's emphasizing the simplified calculation model based on the probability density function for probability of hit. Assuming the probability of hit given a both single-hit and multiple-hit, the susceptibility is accessed for a RCS and the hit probability for a rectangular target is applied for a given threat.

• 한국농공학회논문집
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• 제54권2호
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• pp.37-46
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• 2012

The change of rainfall pattern and hydrologic factors due to climate change increases the occurrence probability of agricultural reservoir water shortage. Water supply assessment of reservoir is usually performed current reservoir level compared to historical water levels or the simulation of reservoir operation based on the water budget analysis. Since each reservoir has the native property for watershed, irrigation district and irrigation water requirement, it is necessary to improve the assessment methods of agricultural reservoir water capability about water resources system. This study proposed a practical methods that water supply vulnerability assessment for an agricultural reservoir based on a concept of probabilistic reliability. The vulnerability assessment of water supply is calculated from probability distribution of water demand condition and water supply condition that influences on water resources management and reservoir operations. The water supply vulnerability indices are estimated to evaluate the performance of water supply on agricultural reservoir system, and thus it is recommended a more objective method to evaluate water supply reliability.

• 한국환경과학회지
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• 제22권8호
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• Ocean Systems Engineering
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• 제12권3호
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• pp.267-284
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• 2022

A subsea pipeline designed across active shipping lane prones to failure against external interferences such as anchorage activities, hence risk assessment is essential. It requires quantifying the geometric probability derived from ship traffic distribution based on Automatic Identification System (AIS) data. The actual probability density function from historical vessel traffic data is ideal, as for rapid assessment, conceptual study, when the AIS data is scarce or when the local vessels traffic are not utilised with AIS. Recommended practices suggest the probability distribution is assumed as a single peak Gaussian. This study compares several fitted Gaussian distributions and Monte Carlo simulation based on actual ship traffic data in main ship direction in an active shipping lane across a subsea pipeline. The results shows that a Gaussian distribution with five peaks is required to represent the ship traffic data, providing an error of 0.23%, while a single peak Gaussian distribution and the Monte Carlo simulation with one hundred million realisation provide an error of 1.32% and 0.79% respectively. Thus, it can be concluded that the multi-peak Gaussian distribution can represent the actual ship traffic distribution in the main direction, but it is less representative for ship traffic distribution in other direction. The geometric probability is utilised in a quantitative risk assessment (QRA) for subsea pipeline against vessel anchor dropping and dragging and vessel sinking.

• 상하수도학회지
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• 제28권3호
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• pp.345-358
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• 2014

For introducing the groundwater quality assessment using background concentration of groundwater, several methods had been studied to estimate the background concentration of groundwater and to suggest the background concentration of study area. Some methods such as Box whisker plot, Percentile and Cumulative probability distribution had been adopted to estimate background concentration, and it was evaluated that the Cumulative probability distribution method presents more reasonable background concentration because it can consider the data distribution. So we estimated the background concentration of study area using cumulative probability distribution method. We suggested the background concentration for each hydrogeology respectively in case hydrogeological water quality similarity is very low.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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• pp.357-365
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• 2003

The major problems with the conventional neural network, especially Back Propagation Neural Network, arise from the necessity of many training data for neural network learning and ambiguity in the relation of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damage of structure to avoid those drawbacks of the conventional neural network. In the PNN-based pattern classification problems, the probability density function for patterns is usually assumed by Gaussian distribution. But, in this paper, several probability density functions are investigated in order to select the most approriate one for structural damage assessment.

• Journal of Mechanical Science and Technology
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• 제20권12호
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• pp.2124-2135
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• 2006

In this paper, the reliability estimation of pipelines is performed by employing the probabilistic method, which accounts for the uncertainties in the load and resistance parameters of the limit state function. The FORM (first order reliability method) and the SORM (second order reliability method) are carried out to estimate the failure probability of pipeline utilizing the FAD (failure assessment diagram). And the reliability of pipeline is assessed by using this failure probability and analyzed in accordance with a target safety level. Furthermore, the MCS (Monte Carlo Simulation) is used to verify the results of the FORM and the SORM. It is noted that the failure probability increases with the increase of dent depth, gouge depth, operating pressure, outside radius, and the decrease of wall thickness. It is found that the FORM utilizing the FAD is a useful and is an efficient method to estimate the failure probability in the reliability assessment of a pipeline. Furthermore, the pipeline safety assessment technique with the deterministic procedure utilizing the FAD only is turned out more conservative than those obtained by using the probability theory together with the FAD. The probabilistic method such as the FORM, the SORM and the MCS can be used by most plant designers regarding the operating condition and design parameters.

• 한국지반신소재학회논문집
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• 제17권4호
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• pp.53-64
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• 2018

본 연구에서는 안정성과 위험도 평가의 중요성이 증대되고 있는 DCM(Deep Cement Mixing, 이하 DCM) 보강 지반상의 항만 구조물에 대하여 위험도 평가를 위한 파괴확률을 산정하였다. DCM 개량 지반의 위험도에 영향을 미치는 확률변수로 개량체의 설계기준강도와 시공중첩, 원지반의 강도 및 내부마찰각, 개량지반의 단위중량을 선정하고 관련 통계치를 산정하여 적용하였다. 또한, 상시 조건과 지진시 조건에서의 전체 시스템에 대한 파괴확률을 분석하였다. 본 연구를 통해 DCM 개량지반의 위험도 평가를 위한 확률변수에서 변동계수가 가장 큰 것은 설계기준강도이나 안전율의 변동성 즉, 시스템의 위험도에는 큰 영향을 미치지는 않는 것을 알 수 있었다. DCM 보강 지반에 대한 시스템의 파괴확률 영향인자 즉, 주된 위험요소는 상시 및 지진시 모두 외적안정의 경우 수평활동, 내적안정의 경우 압축파괴인 것으로 평가되었다. 또한, 수평활동에 대해서는 상시 파괴확률이 지진시 파괴확률보다 높고 압축파괴에 대해서는 상시 파괴확률이 지진시 파괴확률보다 낮은 것으로 나타났다. 전체 시스템의 상시 파괴확률과 지진시 파괴확률은 유사하지만, 본 사례의 경우 지진시 위험도가 다소 높은 것으로 나타났다.