• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.194-202
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• 2019

Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters' posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

• Proceedings of the KSR Conference
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• 2002.05a
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• pp.330-335
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• 2002

To estimate the reliability of the standard electric multiple unit developed by Korea Railroad Research Institute, the vehicle system composed of 4 cars is divided into 14 subsystems. The 14 subsystems are connected in series. For each subsystem except for car body and bogie, failure rate is evaluated by an optimal failure model used in reliability engineering. For car body and bogie probabilistic structural integrity analysis is carried out. The distribution of failure rate of each part and system is assumed to be exponential. The estimated MTBF of the vehicle satisfies the planned MTBF.

• Journal of the Korea Concrete Institute
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• v.16 no.3 s.81
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• pp.345-356
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• 2004

A plasticity model was developed to predict the behavioral characteristics of concrete in multiaxial compression. To extend the applicability of the proposed model to concrete in various stress states, a new approach for failure criteria was attempted. A stress was decomposed into one volumetric and two deviatoric components orthogonal to each other. Three failure criteria wire provided independently for each stress component. To satisfy the three failure criteria, the plasticity model using multiple failure criteria was Implemented. Each failure surface was defined by equivalent volumetric or deviatoric plastic strain. To present dilatancy due to compressive damage a non-associative flow nile was proposed. The proposed model was implemented to finite element analysis, and it was verified by comparisons with various existing test results. The comparisons show that the proposed model predicted well most of the experiments by using three independent failure criteria.

• Journal of the Korean Institute of Gas
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• v.22 no.6
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• pp.40-43
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• 2018

For pressure safety valves, open failure and close failure are partially dependent on each other. A method is proposed in this work that uses a Markov process model and a Weibull distribution model in order to construct a reliability model for two kinds of failure. A pressure safety valve model is obtained from a known open failure model, an induced close failure model, and a simultaneous failure model that reproduces recently reported inspection results. It is expected that the application of the proposed method can be expanded to quantitative risk assessment of various systems that have partially dependent multiple failure states.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.11
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• pp.1813-1821
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• 2004

Until now, the 40% of wall thickness criterion, which is generally used for the plugging of steam generator tubes, has been applied only to a single cracked geometry. In the previous study by the authors, a total number of 9 local failure prediction models were introduced to estimate the coalescence load of two collinear through-wall cracks and, then, the reaction force model and plastic zone contact model were selected as the optimum ones. The objective of this study is to estimate the coalescence load of two collinear through-wall cracks in steam generator tube by using the optimum local failure prediction models. In order to investigate the applicability of the optimum local failure prediction models, a series of plastic collapse tests and corresponding finite element analyses for two collinear through-wall cracks in steam generator tube were carried out. Thereby, the applicability of the optimum local failure prediction models was verified and, finally, a coalescence evaluation diagram which can be used to determine whether the adjacent cracks detected by NDE coalesce or not has been developed.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.553-560
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• 2007

In this paper, we consider two components system which lifetimes have Freund's bivariate exponential model with equal failure rates. We propose Bayesian multiple comparisons procedure for the failure rates of I Freund's bivariate exponential populations based on Dirichlet process priors(DPP). The family of DPP is applied in the form of baseline prior and likelihood combination to provide the comparisons. Computation of the posterior probabilities of all possible hypotheses are carried out through Markov Chain Monte Carlo(MCMC) method, namely, Gibbs sampling, due to the intractability of analytic evaluation. The whole process of multiple comparisons problem for the failure rates of bivariate exponential populations is illustrated through a numerical example.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.268-272
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• 2012

A propulsion controller for vehicles should be designed to overcome a sensor failure during a flight, and it is necessary to control the system properly at any circumstances. Therefore, the vehicles need to retain reliability on the sensor measurements by implementing extra sensors to replace the original control sensors in case of their failure. This paper presents the MIMO NARX model by simulation which substitutes measured values with estimated ones by the state estimation technique in case of a sensor failure in a turbojet engine. It is also presented that the NARX model can be adapted as an engine model in HILS equipments.

• Geomechanics and Engineering
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• v.18 no.4
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• pp.449-457
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• 2019

Physical model tests were first performed to investigate the failure pattern of multiple pillar-roof support system. It was observed in the physical model tests, pillars were design with the same mechanical parameters in model #1, cracking occurred simultaneously in panel pillars and the roof above barrier pillars. When pillars 2 to 5 lost bearing capacity, collapse of the roof supported by those pillars occurred. Physical model #2 was design with a relatively weaker pillar (pillar 3) among six pillars. It was found that the whole pillar-roof system was divided into two independent systems by a roof crack, and two pillars collapse and roof subsidence events occurred during the loading process, the first failure event was induced by the pillars failure, and the second was caused by the roof crack. Then, for a multiple pillar-roof support system, three types of failure patterns were analysed based on the condition of pillar and roof. It can be concluded that any failure of a bearing component would cause a subsidence event. However, the barrier pillar could bear the transferred load during the stress redistribution process, mitigating the propagation of collapse or cutting the roof to insulate the collapse area. Importantly, some effective methods were suggested to decrease the risk of catastrophic collapse, and the deep-hole-blasting was employed to improve the stability of the pillar and roof support system in a room and pillar mine.

• Structural Engineering and Mechanics
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• v.81 no.4
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• pp.429-441
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• 2022

A probabilistic assessment of the seismic-excited buildings with a multiple-tuned-mass-damper (MTMD) system is carried out in the presence of uncertainties of the structural model, MTMD system, and the stochastic model of the seismic excitations. A free search optimization procedure of the individual mass, stiffness and, damping parameters of the MTMD system based on the snap-drift cuckoo search (SDCS) optimization algorithm is proposed for the optimal design of the MTMD system. Considering a 10-story structure in three cases equipped with single tuned mass damper (STMS), 5-TMD and 10-TMD, sensitivity analyses are carried out using Sobol' indices based on the Monte Carlo simulation (MCS) method. Considering different seismic performance levels, the reliability analyses are done using MCS and kriging-based MCS methods. The results show the maximum structural responses are more affected by changes in the PGA and the stiffness coefficients of the structural floors and TMDs. The results indicate the kriging-based MCS method can estimate the accurate amount of failure probability by spending less time than the MCS. The results also show the MTMD gives a significant reduction in the structural failure probability. The effect of the MTMD on the reduction of the failure probability is remarkable in the performance levels of life safety and collapse prevention. The maximum drift of floors may be reduced for the nominal structural system by increasing the TMDs, however, the complexity of the MTMD model and increasing its corresponding uncertainty sources can be caused a slight increase in the failure probability of the structure.

• Journal of Korean Society for Quality Management
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• v.26 no.1
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• pp.99-107
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• 1998

This paper presents a software reliability model that is based on a nonhomogeneous poisson process. The major contribution of this model is combining multiple failure types with imperfect debugging by use of S-shaped mean value function. The software reliability model allows for three different types of errors: Critical errors are the most difficult to detect and the most expensive to remove. Major errors are moderately difficult to detect and fairly expensive to remove. Minor errors are easy to detect and inexpensive to remove. The model also allows for the introduction of any of these types of errors during the removal of an error. A numerical example is provided to illustrate the above techniques.