• Journal of the Korean Society of Safety
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• v.39 no.3
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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.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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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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• v.1 no.4
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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.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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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.

• Journal of Environmental Science International
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• v.22 no.8
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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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• v.12 no.3
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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.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.3
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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.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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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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• v.20 no.12
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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.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.53-64
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• 2018

In this study, the evaluation to probability of failure for risk assessment of port structures on DCM reinforced soils, where stability and risk assessment are increasing in importance, was performed. As a random variables affecting the risk of DCM improved ground, the design strength, superposition (overlap) of construction, strength of the natural ground, internal friction angle and unit weight of the modified ground were selected and applied to the risk assessment. In addition, the failure probability for the entire system under ordinary conditions and under earthquake conditions were analyzed. As a result, it was found that the highest coefficient of variation in the random variable for the risk assessment of the DCM improved ground is the design strength, but this does not have a great influence on the safety factor, ie, the risk of the system. The main risk factor for the failure probability of the system for the DCM reinforced soils was evaluated as horizontal sliding in case of external stability and compression failure in case of internal stability both at ordinary condition and earthquake condition. In addition, the failure probability for ordinary horizontal sliding is higher than that for earthquake failure, and the failure probability for ordinary compression failure is lower than that for earthquake failure. The ordinary failure probability of the entire system is similar to the failure probability on earthquake condition, but in this case, the risk of earthquake is somewhat higher.