• Smart Structures and Systems
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• v.10 no.2
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• pp.89-110
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• 2012

This study was intended to efficiently perform the probabilistic optimal safety assessment of steel cable-stayed bridges (SCS bridges) using stochastic finite element analysis (SFEA) and expected life-cycle cost (LCC) concept. To that end, advanced probabilistic finite element algorithm (APFEA) which enables to execute the static and dynamic SFEA considering aleatory uncertainties contained in random variable was developed. APFEA is the useful analytical means enabling to conduct the reliability assessment (RA) in a systematic way by considering the result of SFEA based on linearity and nonlinearity of before or after introducing initial tensile force. The appropriateness of APFEA was verified in such a way of comparing the result of SFEA and that of Monte Carlo Simulation (MCS). The probabilistic method was set taking into account of analytical parameters. The dynamic response characteristic by probabilistic method was evaluated using ASFEA, and RA was carried out using analysis results, thereby quantitatively calculating the probabilistic safety. The optimal design was determined based on the expected LCC according to the results of SFEA and RA of alternative designs. Moreover, given the potential epistemic uncertainty contained in safety index, failure probability and minimum LCC, the sensitivity analysis was conducted and as a result, a critical distribution phase was illustrated using a cumulative-percentile.

• Geomechanics and Engineering
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• v.24 no.4
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• pp.399-406
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• 2021

It is a key issue in the tunnel design to evaluate the stability of the excavation face. Two efficient analytical models in the context of the limit equilibrium method (LEM) and the limit analysis method (LAM) are used to carry out the deterministic calculations of the safety factor. The safety factor obtained by these two models agrees well with that provided by the numerical modelling by FLAC 3D, but consuming less time. A simple probabilistic approach based on the Mote-Carlo Simulation technique which can quickly calculate the probability distribution of the safety factor was used to perform the probabilistic analysis on the tunnel face stability. Both the cumulative probabilistic distribution and the probability density function in terms of the safety factor were obtained. The obtained results show the effectiveness of this probabilistic approach in the tunnel design.

• Journal of the Korean Society of Safety
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• v.27 no.1
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• pp.44-48
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• 2012

The seismic safety of long-period cable-stayed bridges is assessed by probabilistic finite element analysis and reliability analysis under NFE. The structural response of critical members of cable-stayed bridges is evaluated using the developed probabilistic analysis algorithm. In this study, the real earthquake recording(Chi-Chi Earthquake; 1997) was selected as the input NFE earthquake for investigating response characteristics. The probabilistic response and reliability index shows the different aspect comparing the result from FFE earthquake. Therefore, the probabilistic seismic safety assessment on NFE earthquakes should be performed for the exact evaluation of long-period cable-stayed bridges and the earthquake resistant design criteria should be complemented.

• Journal of the Korean Society of Safety
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• v.18 no.2
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• pp.98-103
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• 2003

Based on ASME probabilistic risk assessment (PRA) and NEI PRA peer review guidance, we evaluate a human reliability analysis (HRA) in probabilistic safety assessment (PSA) for Korea standard nuclear power plants, Ulchin Unit 3&4, to improve it performed at under design. The HRA for Ulchin Unit 3&4 is assessed as higher than Grade I based on ASME PRA standard and as higher than Grade 2 based on NEI PRA peer review guidance. The major items to be improved identified through the evaluation process are the documentation, the systematic human reliability analysis, the participitation of operators in the works and review of HRA. We suggest the guidance on the identification and qualitative screening analysis for pre-accident human errors and solve some items to be improved using the suggested guidance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.10a
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• pp.40-45
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• 1989

In order to take account of the statistical properties of random variables used in the structural analysis, the conventional approach usually adopts the safety factor based on past experiences for the qualitative assessment of structural safety problem. Recently, new approach based on the probabilistic concept has been applied to the assessment of structural safety in order to circumvent the difficulties of the conventional approach in choosing the appropriate safety factor. Thus, computer program called "Probabilistic finite element method" is developed by incorporation the probabilistic concept into the conventional matrix method in order to investigate the effects of the random variables on the final output of the structural analysis. From the comparison of some examples, it can be concluded that the PFEM developed in this study deals with consistently with the uncertainty of random variables and provides the rational tool for the assessment of structural safety of plane frame.

• Korean Journal of Culture and Social Issue
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• v.9 no.spc
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• pp.123-147
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• 2003

This paper provides a comparative analysis of the probabilistic versus deterministic view of accident and safety using the indigenous and cultural perspectives. Death and injury due to accidents is the leading cause of preventable death in most countries, including Korea. The first part of this paper delineates the limitation of the linear, deterministic model that has been adopted in social and applied sciences. The transactional model, advocated by indigenous psychology, is provided to understand the probabilistic nature of accident and safety at home, in the workplace and in society. Second, factors related to accidents and safety are reviewed. Third, application of the probabilistic model for preventing accidents and promoting safety in Korea is outlined.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.101-110
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• 2021

This paper presents the results of an initiating event analysis as part of a Level 1 probabilistic safety assessment (PSA) for at-power internal events for the Korea Research Reactor (KRR). The PSA methodology is widely used to quantitatively assess the safety of research reactors (RRs) in the domestic nuclear industry. Initiating event frequencies are required to conduct a PSA, and they considerably affect the PSA results. Because there is no domestic database for domestic trip events, the safety of RRs is usually assessed using foreign databases. In this paper, operating experience data from the KRR for trip events were collected and analyzed in order to determine the frequency of specific initiating events. These frequencies were calculated using two approaches according to the event characteristics and data availability: (1) based on KRR operating experience or (2) using generic data.

• Computational Structural Engineering
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• v.2 no.4
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• pp.89-98
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• 1989

In order to take account of the statistical properties of random variables used in the structural analysis, the conventional approach usually adopts the safety factor based on past experiences for the qualitative assessment of structural safety problem. Recently, new approach based on the probabilistic concept has been applied to the assessment of structural safety in order to circumvent the difficulties of the conventional approach in choosing the appropriate safety factor. Thus, computer program called "Probabilistic finite element method" is developed by incorporating the probabilistic concept into the conventional matrix method in order to investigate the effects of the random variables on the final output of the structural analysis. From the comparison of some examples, it can be concluded that the PFEM developed in this study deals consistently with the uncertainty of random variables and provides the rational tool for the assessment of structural safety of plane frame.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2084-2093
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• 2022

Probabilistic safety assessment is widely used to quantify the risks of nuclear power plants and their uncertainties. When the lognormal distribution describes the uncertainties of basic events, the uncertainty of the top event in a fault tree is approximated with the sum of lognormal random variables after minimal cutsets are obtained, and rare-event approximation is applied. As handling complicated analytic expressions for the sum of lognormal random variables is challenging, several approximation methods, especially Monte Carlo simulation, are widely used in practice for uncertainty analysis. In this study, a theoretical approach for analyzing the sum of lognormal random variables using an efficient numerical integration method is proposed for uncertainty analysis in probability safety assessments. The change of variables from correlated random variables with a complicated region of integration to independent random variables with a unit hypercube region of integration is applied to obtain an efficient numerical integration. The theoretical advantages of the proposed method over other approximation methods are shown through a benchmark problem. The proposed method provides an accurate and efficient approach to calculate the uncertainty of the top event in probabilistic safety assessment when the uncertainties of basic events are described with lognormal random variables.

• 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.