• Current Photovoltaic Research
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• 제8권4호
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• pp.124-128
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• 2020

Output power of photovoltaic (PV) modules installed outdoors decreases every year due to environmental conditions such as temperature, humidity, and ultraviolet irradiations. In order to promote the installation of PV modules, the reliability must be guaranteed. One of the important factors affecting reliability is intermetallic compounds (IMC) layer formed in ribbon solder joint. For this reason, various studies on soldering properties between the ribbon and cell have been performed to solve the reliability deterioration caused by excessive growth of the IMC layer. However, the IMC layer of the PV module interconnected by multi-wires has been studied less than using the ribbon. It is necessary to study soldering characteristics of the multi-wire module for improvement of its reliability. In this study, we analyzed the growth of IMC layer of the PV module with multi-wire and the degradation of output power through damp-heat test. The fabricated modules were exposed to damp-heat conditions (85 ºC and 85 % relative humidity) for 1000 hours and the output powers of the modules before and after the damp-heat test were measured. Then, the process of dissolving ethylene vinyl acetate (EVA) as an encapsulant of the modules was performed to observe the IMC layer. The growth of IMC layer was evaluated using OM and FE-SEM for cross-sectional analysis and EDS for elemental mapping. Based on these results, we investigated the correlation between the IMC layer and output power of modules.

• Journal of Korea Society of Digital Industry and Information Management
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• 제10권4호
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• pp.19-27
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• 2014

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the reliability model with log type mean value function (Musa-Okumoto and log power model), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing log type mean value function was employed. This analysis of failure data compared with log type mean value function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of information and communication convergence engineering
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• 제20권2호
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• pp.79-89
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• 2022

To compute the mean and variance of component-based reliability software, we focused on path-based reliability analysis. System reliability depends on the transition probabilities of components within a system and reliability of the individual components as basic input parameters. The uncertainty in these parameters is estimated from the test data of the corresponding components and arises from the software architecture, failure behaviors, software growth models etc. Typically, researchers perform Monte Carlo simulations to study uncertainty. Thus, we considered a Markov chain Monte Carlo (MCMC) simulation to calculate uncertainty, as it generates random samples through sequential methods. The MCMC approach determines the input parameters from the probability distribution, and then calculates the average approximate expectations for a reliability estimation. The comparison of different techniques for uncertainty analysis helps in selecting the most suitable technique based on data requirements and reliability measures related to the number of components.

• Electronics and Telecommunications Trends
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• 제14권4호통권58호
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• pp.1-9
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• 1999

In this paper, we summarize the lessons learned from the applications of the software reliability engineering to a large-scale software project. The considered software is the software system of the TDX-10 ISDN switching system. The considered software consists of many components, called functional blocks. These functional blocks serve as the unit of coding and test. The software is continuing to be developed by adding new functional blocks. We are mainly concerned with the analysis of the effects of these software components to software reliability and with the analysis of the reliability evolution. We analyze the static characteristics of the software related to software reliability using failure data collected during system test. We also discussed a pattern which represents a local and global growth of the software reliability as version evolves. To find the pattern of software of the TDX-10 ISDN system, we apply the S-shaped model to a collection of failure data sets of each evolutionary version and the Goel-Okumoto (G-O) model to a grouped overall failure data set. We expect this pattern analysis will be helpful to plan and manage necessary human/resources for a new similar software project which is developed under the same developing circumstances by estimating the total software failures with respect to its size and time.

• Journal of Korean Society for Quality Management
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• 제26권3호
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• pp.71-81
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• 1998

In reliability analysis, the time difference between the expected next failure time and the current failure time or the Mean Time Between Failure(MTBF) is of significant interest. Until recently, in reliability growth studies, the reciprocal of the intensity function at current failure time has been used as being equal to MTBE($t_n$)at the n-th failure time $t_n$. That is MTBF($t_n$)=l/$\lambda (t_n)$. However, such a relationship is only true for Homogeneous Poisson Process(HPP). Tsokos(1995) obtained the upper bound and lower bound for the MTBF($t_n$) and proposed an estimator for the MTBF($t_n$) as the mean of the two bounds. In this paper, we provide the estimator for the MTBF($t_n$) which does not depend on the value of the shape parameter. The result of the Monte Carlo simulation shows that the proposed estimator has better efficiency than Tsokos's estimator.

• Proceedings of the KSR Conference
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.1014-1023
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• 2008

The K-AGT test line is managed similarly to revenue operation and operated automatically 120km per day, total 90,000km from August 2004 to December 2007. To enhance reliability of developed system, maintenance information system based on RCM is applied. The maintenance program applied in test line is based on RCM which prevent a fault before it happens and a fault made in test line is analysed by reliability growth test. Vehicle system, power supply system, signalling system, track and infrastructure are built in test line and it is reviewed enhancing system performance and changing designs to commercialize through reliability growth analysis method.

• The Transactions of the Korea Information Processing Society
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• 제7권3호
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• pp.852-861
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• 2000

Software reliability growth models are used in testing stages of software development to model the error content and time intervals betwewn software failures. In this paper, using priors for the number of fault with the negative binomial distribution nd the error rate with gamma distribution, Bayesian inference and model selection method for Jelinski-Moranda and Goel-Okumoto and Schick-Wolverton models in software reliability. For model selection, we explored the sum of the relative error, Braun statistic and median variation. In Bayesian computation process, we could avoid the multiple integration by the use of Gibbs sampling, which is a kind of Markov Chain Monte Carolo method to compute the posterior distribution. Using simulated data, Bayesian inference and model selection is studied.

• Journal of the Korean Society for Railway
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• 제8권5호
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• pp.434-438
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• 2005

In this paper, as the first step to assess and enhance the reliability of Korea High Speed Train, an electric traction system is selected and reliability analysis is carried out. The electric traction system is classified into subsystems and functional block diagrams and reliability block diagrams are drawn. Expressions for evaluating the reliability are derived and Mean Kilometer Between Service Failure is calculated using the trial track test results. The calculation results show reliability growth of the proposed system.

• Convergence Security Journal
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• 제12권1호
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• pp.9-16
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• 2012

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed for testing time. The testing time on the right is truncated in this model. The intensity function, mean-value function, reliability of the software, estimation of parameters and the special applications of Pareto NHPP model are discussed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection, depended on difference between predictions and actual values, were efficient using the mean square error and $R_{SQ}$.

• Structural Engineering and Mechanics
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• 제53권6호
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• pp.1183-1200
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• 2015

Reinforcement corrosion can cause serious safety deterioration to aging concrete structures exposed in aggressive environments. This paper presents an approach for reliability analyses of deteriorating reinforced concrete structures affected by reinforcement corrosion on the basis of the representative symptoms identified during the deterioration process. The concrete cracking growth and rebar bond strength evolution due to reinforcement corrosion are chosen as key symptoms for the performance deterioration of concrete structures. The crack width at concrete cover surface largely depends on the corrosion penetration of rebar due to the expansive rust layer at the bond interface generated by reinforcement corrosion. The bond strength of rebar in the concrete correlates well with concrete crack width and decays steadily with crack width growth. The estimates of cracking development and bond strength deterioration are examined by experimental data available from various sources, and then matched with symptom-based lifetime Weibull model. The symptom reliability and remaining useful life are predicted from the predictive lifetime Weibull model for deteriorating concrete structures. Finally, a numerical example is provided to demonstrate the applicability of the proposed approach for forecasting the performance of concrete structures subject to reinforcement corrosion. The results show that the corrosion rate has significant impact on the reliability associated with serviceability and load bearing capacity of reinforced concrete structures during their service life.