• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.5
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• pp.405-409
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• 2009

Reliability analysis of coastal structure using importance sampling was shown. When Monte Carlo simulation is used to evaluate overturng failure probability of coastal structure, very low failure probability leads to drastic increase in simulation time. However, importance sampling which uses randomly chosen design candidates around the failure surface makes it possible to analyze very low failure probability efficiently. In the numerical example, failure probability of caisson type quay wall was analyzed by using importance sampling and performance according to the level of failure probability was shown.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.283-290
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• 2014

In the flat panel display industry, to meet production target quantities and the deadline of production, the scheduler and dispatching systems are major production management systems which control the order of facility production and the distribution of WIP (Work In Process). Especially the delivery time is a key factor of the dispatching system for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors of the delivery time and to build the delivery time forecasting model. To select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the accelerated failure time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the mean square error (MSE) criteria, the AFT model decreased by 33.8% compared to the statistics prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing the delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.508-512
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• 2004

An aerospace vehicle in flight can be exposed to random gust which may cause critical structural failure. In this paper, the failure analysis is conducted for composite wing subjected to random gust. For this, the profile of random gust is idealized as a stationary Gaussian random process and the power spectral density (PSD) of wing bending moment induced by gust is obtained. The PSD function is converted to probabilistic distributions and the failure probability during total flight time is calculated by Monte Carlo simulation.

• International journal of steel structures
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• v.18 no.4
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• pp.1384-1396
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• 2018

One of the failure modes observed in steel yield energy dissipating devices (SYEDs) excited by a strong earthquake would be the low-cycle fatigue failure. Fatigue cracks of a SYED are prone to initiate at the notch areas where stress concentration is usually occurred, which is demonstrated by the cyclic tests and analyses carried out for this study. Since the fatigue failure of SYEDs dramatically deteriorates their structural capacities, the thorough investigation on their fatigue life is usually required. To do this, sophisticated modeling with considering a time-consuming and complicate fracture mechanism is generally needed. This study makes an effort to investigate the low-cycle fatigue life of SYEDs predicted by a simplified method utilizing damage indices and fatigue prediction equations that are based on the plastic strain amplitudes obtained from typical finite element analyses. This study shows that the low-cycle fatigue failure of SYEDs predicted by the simplified method can be conservatively in good agreement with the test results of SYED specimens prepared for experimental validation.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.1
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• pp.67-73
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• 2014

A reliability evaluation or prediction can be defined as MTBF which stands for mean time between failures (Exclusively for repairable failures). Spindle system has huge effect on performance of machine tools and working quality as well as is required of high reliability. Especially, it takes great importance in producing automobiles which includes a large number of working processes. However, it is unusually difficult to predict reliability because there are lack of data and research about reliability of spindle system. Standards and methods of examinations for reliability evaluation of machine tools are scarce at local and abroad as well. Therefore, this research is meant to improve the reliability of spindle system before mass produced with developing standards of reliability and methods of examinations through FMEA to assess reliability of spindle system in prototype stages of developing high speed spindle system of machining center.

• Proceedings of the Korean Reliability Society Conference
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• 2004.07a
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• pp.227-232
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• 2004

The failure of geogrids can be defined as an excessive creep strain which causes the collapse of slopes and embankments. In this study, the accelerated creep tests were applied to two different types of polyester geogrids, at 75, 80, 85$^{\circ}C$ by applying 50% load of ultimate tensile strengths using a newly designed test equipment which is allowed the creep testing at higher temperatures. And then the creep curves were shifted and superposed in the time axis by applying time-temperature supposition principles. In predicting the lifetimes of geogrids, the underlying distribution for failure times were determined based on identification of the failure mechanism. The results indicate that the conventional procedures with the newly designed test equipment are shown to be effective in prediction of the lifetimes of geogrids with shorter test times. In addition, the predicted lifetimes of geogrids having different structures at various creep strains give guidelines for users to select the proper geogrids in the fields.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.7-14
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• 2011

Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rate per fault (hazard function). This infinite non-homogeneous Poisson process is model which reflects the possibility of introducing new faults when correcting or modifying the software. In this paper, polynomial hazard function have been proposed, which can efficiency application for software reliability. Algorithm for estimating the parameters used to maximum likelihood estimator and bisection method. Model selection based on mean square error and the coefficient of determination for the sake of efficient model were employed. In numerical example, log power time model of the existing model in this area and the polynomial hazard function model were compared using failure interval time. Because polynomial hazard function model is more efficient in terms of reliability, polynomial hazard function model as an alternative to the existing model also were able to confirm that can use in this area.

• Journal of Welding and Joining
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• v.23 no.6
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• pp.61-66
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• 2005

A probabilistic approach for evaluating failure risk is suggested in this paper. Probabilistic fracture analyses were performed for a pressurized pipe of a Cr-Mo steel reflecting variation of material properties at high temperature. A crack was assumed to be located along the weld fusion line. Probability density functions of major variables were determined by statistical analyses of material creep and creep crack growth data measured by the previous experimental studies by authors. Distributions of these variables were implemented in Monte Carlo simulation of this study. As a fracture parameter for characterizing growth of a fusion line crack between two materials with different creep properties, $C_t$ normalized with $C^*$ was employed. And the elapsed time was also normalized with tT, Resultingly, failure probability as a function of operating time was evaluated fur various cases. Conventional deterministic life assessment result was turned out to be conservative compared with that of probabilistic result. Sensitivity analysis for each input variable was conducted to understand the most influencing variable to the analysis results. Internal pressure, creep crack growth coefficient and creep coefficient were more sensitive to failure probability than other variables.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.484-497
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• 2021

This paper proposes an extended time uncertainty analysis approach in Level 2 human reliability analysis (HRA) considering severe accident management (SAM) strategies. The method is a time-based model that classifies two time distribution functions-time required and time available-to calculate human failure probabilities from delayed action when implementing SAM strategies. The time required function can be obtained by the combination of four time factors: 1) time for diagnosis and decision by the technical support center (TSC) for a given strategy, 2) time for strategy implementation mainly by the local emergency response organization (ERO), 3) time to verify the effectiveness of the strategy and 4) time for portable equipment transport and installation. This function can vary depending on the given scenario and includes a summation of lognormal distributions and a choice regarding shifting the distribution. The time available function can be obtained via thermal-hydraulic code simulation (MAAP 5.03). The proposed approach was applied to assess SAM strategies that use portable equipment and safety depressurization system valves in a total loss of component cooling water event that could cause reactor vessel failure. The results from the proposed method are more realistic (i.e., not conservative) than other existing methods in evaluating SAM strategies involving the use of portable equipment.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.703-712
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• 2017

The composite blades of offshore wind turbines accumulate structural damage such as fatigue cracking due to harsh operation environments during their service time, leading to premature structural failures. This paper investigates various fatigue crack models for reproducing crack development in composite blades and proposes a stochastic approach to predict fatigue crack evolution and to analyse failure probability for the composite blades. Three typical fatigue models for the propagation of fatigue cracks, i.e., Miner model, Paris model and Reifsnider model, are discussed to reproduce the fatigue crack evolution in composite blades subjected to cyclical loadings. The lifetime probability of fatigue failure of the composite blades is estimated by stochastic deterioration modelling such as gamma process. Based on time-dependent reliability analysis and lifecycle cost analysis, an optimised maintenance policy is determined to make the optimal decision for the composite blades during the service time. A numerical example is employed to investigate the effectiveness of predicting fatigue crack growth, estimating the probability of fatigue failure and evaluating an optimal maintenance policy. The results from the numerical study show that the stochastic gamma process together with the proper fatigue models can provide a useful tool for remaining useful life predictions and optimum maintenance strategies of the composite blades of offshore wind turbines.