• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.37-41
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• 2018

Process safety technology has developed from qualitative methods such as HAZOP (hazard and operability study) to semi-quantitative methods such as LOPA (layer of protection analysis), and quantitative methods are actively studied these days. Quantitative risk assessment (QRA) is often based on fault tree analysis (FTA). FTA is efficient, but difficult to apply when failure events are not independent of each other. This problem can be avoided using a Markov process (MP). MP requires definition of all possible states, and thus, generally, is more complicated than FTA. A method is proposed in this work that uses an MP model and a Weibull distribution model in order to construct a reliability model for multiple dependent failures. As a case study, a pressure safety valve (PSV) is considered, for which there are three kinds of failure, i.e. open failure, close failure, and gas tight failure. According to recently reported inspection results, open failure and close failure are dependent on each other. A reliability model for a PSV group is proposed in this work that is to reproduce these results. It is expected that the application of the proposed method can be expanded to QRA of various systems that have partially dependent multiple failure states.

• Structural Engineering and Mechanics
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• v.71 no.4
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• pp.329-339
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• 2019

Assessment of failure probability, especially for a complex structure, requires a considerable number of calls to the numerical model. Reliability methods have been developed to decrease the computational time. In this approach, the original numerical model is replaced by a surrogate model which is usually explicit and much faster to evaluate. The current paper proposed an efficient reliability method based on Monte Carlo simulation (MCS) and multi-gene genetic programming (MGGP) as a robust variant of genetic programming (GP). GP has been applied in different fields; however, its application to structural reliability has not been tested. The current study investigated the performance of MGGP as a surrogate model in structural reliability problems and compares it with other surrogate models. An adaptive Metropolis algorithm is utilized to obtain the training data with which to build the MGGP model. The failure probability is estimated by combining MCS and MGGP. The efficiency and accuracy of the proposed method were investigated with the help of five numerical examples.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.267-274
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• 2004

Since there is a large variation in measurements of the thickness of corroded elements, the thickness of corroded elements are considered as imprecise elements. There is also a considerable degree of uncertainty in a visual assessment of thickness loss. The remaining thickness of a severly corroded element may be represented by an imprecise which expresses the range over which there is uncertainty about the thickness. Therefore, the objective of this paper is to propose a new methodology to safety assessment using imprecise reliability into conventional safety assessment frameworks. For this purpose, this study presents a safety assessment model using Imprecise reliability for large civil structures and demonstrates the applicability of the approach to cable-stayed bridge projects.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.181-186
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• 2003

There are many uncertainties in structural failures or structures, so probabilistic failure cause assessment should be performed in order to consider the uncertainties. However, in many cases of forensic engineering, the failure cause assessments are performed by deterministic approach though number of uncertainties are existed in the failures or structures. Thus, deterministic approach may have possibility for leading to unreasonable and unrealistic failure cause assessment due to ignorance of the uncertainties. Therefore, probabilistic approach is needed to complement the shortcoming of deterministic approach and to perform the more reasonable and realistic failure cause assessment. In this study, reliability-based failure cause assessment (reliability based forensic engineering) is performed, which can incorporate uncertainties in failures and structures. For more practical application, the modified ETA technique is proposed, which automatically generates the defected structural model, performs structural analysis and reliability analysis, and calculates the failure probabilities of the failure events and the occurrence probabilities of the failure scenarios. Also, for more precise reliability analysis, uncertainties are estimated more reasonably by using bayesian approach based on the experimental laboratory testing data in forensic report.

• Journal of Navigation and Port Research
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• v.35 no.4
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• pp.281-287
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• 2011

According to the Marine Traffic Safety Law, revised in 2009, Marine Traffic Safety Audit is introduced to secure the safe navigation, to prevent the marine accident and to maximize the efficiency of the port. In this audit system, marine traffic safety assessment is the most important scheme because the primary purpose of the audit system is to identify potential risk elements affecting safe navigation. Even though the reliability of audit result depends on the selection of assessment models, there are no independent assessment models for Korean coastal waters and most of models used in Korea currently are developed by foreign countries. Therefore, the development of the independent assessment model for Korean coastal water is required. This study, prior to the development of independent assessment model, aims to provide a basic data by comparing two foreign assessment models in Ulsan port area with marine accident statistics data.

• Journal of Applied Reliability
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• v.14 no.2
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• pp.129-136
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• 2014

Reliability test is focusing to detect the unexpected reliability failure and solve them for the high quality of products. The test data should be used to assess and project the current level of interesting product reliability and so it is very important to have the accurately assessing methodology with test data. There are two type of trend for test data as constant and changing one during testing and this paper shows the difference in the assessing results of these two cases. There is less information how to define the existence of reliability growth rate changing and calculate the parameters of the reliability growth models to make an accurate assessment with such condition, so i established the process and mathematical model to calculate the parameters at such condition to make reliability growth curve with high Goodness of Fit. I validated the new method with the data made from Monte Carlo Simulation and case from Demko (1993). Even the assessed result with the new methodology may be different with the case by case because of very diversity in test condition and testing product quality, but the process and method founded in this research can be applied to any case using Duane and AMSAA model for their test data assessment. I also present the evaluation method to see the effectiveness with new one which is a conventional knowledge and not popular to use, so it is possible to compare the results with the newly presented and conventional method for better business decision.

• Journal of Korean Society of Steel Construction
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• v.15 no.2
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• pp.187-196
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• 2003

Today, the Working Stress Rating (WSR) is being widely used for the capacity-rating and the safety assessment of railroad steel bridges. Since it cannot incorporate the uncertainties, several studies have been carried out in order to get over the incompleteness of the conventional capacity-rating and safety assessment. A system reliability-based equivalent capacity-rating method, which can evaluate the capacity of existing bridges, has been recently proposed. For more efficient reliability analysis, probabilistic parameters of the random variables in the limit-state models should be reasonably evaluated. Especially, uncertainties for live load effects must be realistically included. In this study, an improved limit-state model was used for the system reliability-based equivalent strength method. This model can incorporate the probabilistic parameters obtained from ambient measurement data. To demonstrate the applicability of the improved system reliability-based equivalent capacity rating method, this was applied to the existing steel plate girder bridge for comparison with the conventional capacity-rating and safety assessment.

• Structural Engineering and Mechanics
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• v.38 no.2
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• pp.171-193
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• 2011

One of the possible alternatives of simulation-based time-dependent reliability assessment of pre-stressed biconcave and biconvex cable trusses, the Monte Carlo method, is applied in this paper. The influence of an excessive deflection of cable truss (caused by creep of cables and rheologic changes) on its time-dependent serviceability is investigated. Attention is given to the definition of the basic random variables and their statistical functions (basic, mutually dependent random variables such as the pre-stressing forces of the bottom and top cable, structural geometry, the Young's modulus of elasticity of the cables, and the independent variables, such as permanent load, wind, snow and thermal actions). Then, the determination of the response of the cable truss to the loading effects, and the definition of the limiting values considering serviceability of the structure are performed. The potential of the method, using direct Monte Carlo technique for simulation-based time-dependent reliability assessment as a powerful tool, is emphasized. Results obtained by the First order reliability method (FORM) are compared with those obtained by the Monte Carlo simulation technique.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.320-328
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• 2011

This research proposes comprehensive models for analyzing common cause failures (CCF) due to cumulative shocks and to assess system reliability under the CCF. The proposed cumulative shock models are based on the binomial failure rate (BFR) model. Six kinds of models are proposed so as to explain diverse cumulative shock phenomena. The models are composed of the initial failure probability, shape parameter, and the total shock number. Some parameters of the proposed models can not be explicitly estimated, so we adopt the Expectation-maximization (EM) algorithm in order to obtain the maximum likelihood estimator (MLE) for the parameters. By estimating the parameters for the cumulative shock models, the system reliability with CCF can be assessed sequentially according to the number of cumulative shocks. The result can be utilizes in dynamic probabilistic safety assessment (PSA), aging studies, or risk management for nuclear power plants. Replacement or maintenance policies can also be developed based on the proposed model.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.427-435
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• 2008

A reliability based slope stability assessment method is proposed and examined considering the variation of matric suction which is measured by a real time slope monitoring system. Mean value first order reliability method and advanced first order reliability method are used to calculate reliability indices of a slope. The applicability of methods is compared by applying them to the range of matric suctions measured by the real-time monitoring system. Sensitivity analysis is also performed to examine the contribution of random variables to the reliability index of slope. Finally, the proposed method is applied to a model slope. The results show that the reliability index of slope can be used for efficient slope management by quantifying the risk of slope in real time.