• Journal of the Korean Society for Precision Engineering
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• 제21권12호
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• pp.109-118
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• 2004

Life cycle assessment (LCA) usually involves some uncertainty. These uncertainties are generally divided in two categories such lack of data and data inaccuracy in life cycle inventory (LCI). This paper explo.es a methodology on dealing with uncertainty due to lack of data in LCI. In order to treat uncertainty of LCI data, a model for data uncertainty is proposed. The model works with probabilistic curves as inputs and with Monte Carlo Simulation techniques to propagate uncertainty. The probabilistic curves were derived from the results of survey in expert network and Monte Carlo Simulation was performed using the derived probabilistic curves. The results of Monte Carlo Simulation were verified by statistical test. The proposed approach should serve as a guide to improve data quality and deal with uncertainty of LCI data in LCA projects.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.667-670
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• 2001

For major structural components periodic inspections and integrity assessments are needed for the safety. However, many flaws are undetectable because sampling inspection is carried out during in-service inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties and undetectable cracks. This paper describes a Probabilistic Fracture Mechanics(PEM) analysis based on the Monte Carlo(MC) algorithms. Taking a number of sampling data of probabilistic variables such as fracture toughness value, crack depth and aspect ratio of an initial surface crack, a MC simulation of failure judgement of samples is performed. For the verification of this analysis, a comparison study of th PFM analysis using a commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Computers and Concrete
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• 제19권3호
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• pp.305-313
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• 2017

A robust finite element based reinforced concrete bridge deck corrosion initiation model is applied for time-dependent probabilistic sensitivity analysis. The model is focused on uncertainties in the governing parameters that include variation of high performance concrete (HPC) diffusion coefficients, concrete cover depth, surface chloride concentration, holidays in reinforcements, coatings and critical chloride threshold level in several steel reinforcements. The corrosion initiation risk is expressed in the form of probability over intended life span of the bridge deck. Conducted study shows the time-dependent sensitivity analysis to evaluate the significance of governing parameters on chloride ingress rate, various steel reinforcement protection and the corrosion initiation likelihood. Results from this probabilistic analysis provide better insight into the effect of input parameters variation on the estimate of the corrosion initiation risk for the design of concrete structures in harsh chloride environments.

• Proceedings of the KSME Conference
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• 대한기계학회 2001년도 춘계학술대회논문집A
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• pp.459-464
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• 2001

For major nuclear power plant components periodic inspections and integrity assessments are needed for the safety. But many flaws are undetectable due to sampling inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties, applied load and undetectable flaws. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on Monte Carlo(MC) algorithms. Taking important parameters as probabilistic variables such as fracture toughness, crack growth rate and flaw shape, failure probability of major nuclear power plant components is archived as a results of MC simulation. For the verification of these analysis, a comparison study of the PFM analysis using other commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Proceedings of the KIEE Conference
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.61-62
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• 2007

This paper evaluates probabilistic reliability of KEPCO system using TRELSS, which is a probabilistic reliability evaluation program for large-scaled power system. In order to systematically evaluate probabilistic reliability of KEPCO system, contingency cases causing load loss in (N-1) & (N-2) contingency depth was analyzed and reliability indices such as LOLP, EDLC, EENS according to change of FOR was calculated.

• Journal of the Earthquake Engineering Society of Korea
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• 제19권6호
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• pp.265-271
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• 2015

The tsunami hazard analysis is performed for testing the application of probabilistic tsunami hazard analysis to nuclear power plant sites in the Korean Peninsula. Tsunami hazard analysis is based on the seismic hazard analysis. Probabilistic method is adopted for considering the uncertainties caused by insufficient information of tsunamigenic fault sources. Logic tree approach is used. Uljin nuclear power plant (NPP) site is selected for this study. The tsunamigenic fault sources in the western part of Japan (East Sea) are used for this study because those are well known fault sources in the East Sea and had several records of tsunami hazards. We have performed numerical simulations of tsunami propagation for those fault sources in the previous study. Therefore we use the wave parameters obtained from the previous study. We follow the method of probabilistic tsunami hazard analysis (PTHA) suggested by the atomic energy society of Japan (AESJ). Annual exceedance probabilities for wave height level are calculated for the site by using the information about the recurrence interval, the magnitude range, the wave parameters, the truncation of lognormal distribution of wave height, and the deviation based on the difference between simulation and record. Effects of each parameters on tsunami hazard are tested by the sensitivity analysis, which shows that the recurrence interval and the deviation dominantly affects the annual exceedance probability and the wave heigh level, respectively.

• Proceedings of the KIEE Conference
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• 대한전기학회 2005년도 추계학술대회 논문집 전력기술부문
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• pp.46-48
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• 2005

This paper discusses a probabilistic method for power system security assessment. The security analysis relates to the ability of the electric power systems to survive sudden disturbances such as electric short circuits or unanticipated loss of system elements. It consists of both steady state and dynamic security analyses, which are not two separate issues but should be considered together. In steady state security analysis including voltage security analysis, the analysis checks that the system is operated within security limits by OPF (optimal power flow) after the transition to a new operating point. Until now, many utilities have difficulty in including dynamic aspects due to computational capabilities. On the other hand. dynamic security analysis is required to ensure that the transition may lead to an acceptable operating condition. Transient stability, which is the ability of power systems to maintain synchronism when subjected to a large disturbance. is a principal component in dynamic security analysis. Usually any loss of synchronism may cause additional outages and make the present steady state analysis of the post-contingency condition inadequate for unstable cases. This is the reason for the need of dynamic studies in power systems. Probabilistic criterion can be used to recognize the probabilistic nature of system components while considering system security. In this approach. we do not have to assign any predetermined margin of safety. A comprehensive conceptual framework for probabilistic static and dynamic assessment is presented in this paper. The simulation results of the Western System Coordinating Council (WSCC) system compare an analytical method with Monte-Carlo simulation (MCS).

• Tunnel and Underground Space
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• 제22권2호
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• pp.86-92
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• 2012

Point estimate method has a less accuracy than Monte Carlo simulation that is usually considered as an exact probabilistic method, but this method still remains popular in probability-based reliability assessment in geotechnical and rock engineering, because it significantly reduce the number of sampling points and produces the statistical moments of a performance function in a reasonable accuracy. In the present study, we investigated the accuracy and applicability of point estimate methods proposed by Rosenblueth and Zhou & Nowak by comparing the results of these two methods with those of Monte Carlo simulations. The comparison was carried out for the problem of a lined circular tunnel in an elastic medium where an closed-form analytical solution is given. The comparison results showed that despite the non-linearity of the analytical solution, the statistical moments calculated by the point estimate methods and the Monte Carlo simulations agreed well with an average error of roughly 1-2%. This average error demonstrates the applicability of the two point estimate methods for the probabilistic reliability assessment of underground structures in combination with numerical analysis.

• Journal of the Computational Structural Engineering Institute of Korea
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• 제31권1호
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• pp.31-38
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• 2018

Earthquake disasters that exceed the design criteria can pose significant threats to nuclear facilities. Seismic probabilistic safety assessment(PSA) is a probabilistic way to quantify such risks. Accordingly, seismic PSA has been applied to domestic and overseas nuclear power plants, and the safety of nuclear power plants was evaluated and prepared against earthquake hazards. However, there were few examples where seismic PSA was applied in case of a research reactor with a relatively small size compared to nuclear power plants. Therefore, in this study, seismic PSA technique was applied to actually completed research reactor to analyze its safety. Also, based on these results, the optimization study on the seismic capacity of the system constituting the research reactor was carried out. As a result, the possibility of damage to the core caused by the earthquake hazard was quantified in the research reactor and its safety was confirmed. The optimization study showed that the optimal seismic capacity distribution was obtained to ensure maximum safety at a low cost compared with the current design. These results, in the future, can expect to be used as a quantitative indicator to effectively improve the safety of the research reactor with respect to earthquakes.

• Journal of the Computational Structural Engineering Institute of Korea
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• 제37권3호
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• pp.205-216
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• 2024

Recently, seismic Probabilistic Safety Assessment (PSA) methods have been developed for process plants, such as gas plants, oil refineries, and chemical plants. The framework originated from the PSA of nuclear power plants, which aims to assess the risk of reactor core damage. The original PSA method was modified to adopt the characteristics of a process plant whose purpose is continuous operation without shutdown. Therefore, a fault tree, whose top event is shut down, was constructed and transformed into a Bayesian Network (BN), a probabilistic graph model, for efficient risk-informed decision-making. In this research, the fault tree-based BN from the previous research is further developed to consider the multi-hazard of earthquake-induced fire and explosion (EQ-induced F&E). For this purpose, an event tree describing the occurrence of fire and explosion from a release is first constructed and transformed into a BN. And then, this BN is connected to the previous BN model developed for seismic PSA. A virtual plot plan of a gas plant is introduced as a basis for the construction of the specific EQ-induced F&E BN to test the proposed BN framework. The paper demonstrates the method through two examples of risk-informed decision-making. In particular, the second example verifies how the proposed method can establish a repair and retrofit strategy when a shutdown occurs in a process plant.