• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1173-1184
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• 2018

The lifetime of a lithium-ion battery is one of the most important issues of the energy storage system (ESS) because of its stable and reliable operation. In this paper, the lifetime management method of the lithium-ion battery for energy storage system is proposed. The lifetime of the lithium-ion battery varies, depending on the power usage, operation condition, and, especially the selected depth of discharge (DOD). The proposed method estimates the total lifetime of the lithium-ion battery by calculating the total transferable energy corresponding to the selected DOD and achievable cycle (ACC) data. It is also demonstrated that the battery model can obtain state of charge (SOC) corresponding to the ESS operation simultaneously. The simulation results are presented performing the proposed lifetime management method. Also, the total revenue and entire lifetime prediction of a lithium-ion battery of ESS are presented considering the DOD, operation and various condition for the nations of USA and Korea using the proposed method.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.7-12
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• 2004

A lifetime prediction of holddown spring screw in nuclear fuel assembly was performed using fracture mechanics approach. The spring screw was designed such that it was capable of sustaining the loads imposed by the initial tensile preload and operational loads. In order to investigate the cause of failure and to predict the stress corrosion cracking life of the screw, a stress analysis of the top nozzle spring assembly was done using finite element analysis. The elastic-plastic finite element analysis showed that the local stresses at the critical regions of head-shank fillet and thread root significantly exceeded than the yield strength of the screw material, resulting in local plastic deformation. Normalized stress intensity factors for PWSCC life prediction was proposed. Primary water stress corrosion cracking life of the Inconel 600 screw was predicted by using integration of the Scott model and resulted in 1.78 years, which was fairly close to the actual service life of the holddown spring screw.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.218-224
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• 1996

The purpose of this syudy is to set up a proper repair plan and to extend the remaining lifetime of them by measuring the remaining lifetime of reinforced concrete structures quantitatively. This method is based on the actual research on age deterioration, carbonation depth and covering depth of the reinforced concrete structures. Also, it measure the remaining lifetime through quantitatively defining the probability of steel corrosion by the damage of steel corrosion. By doing that, we proceed the proper repair plan after reviewing the possibility of lifetime extension.

• Magazine of the Korea Concrete Institute
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• v.6 no.3
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• pp.96-100
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• 1994

• Elastomers and Composites
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• v.44 no.2
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• pp.116-121
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• 2009

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.3
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• pp.273-281
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• 2010

In this paper, a method to predict the fatigue life of an axle drive shaft by the calibrated accelerated life test (CALT) method is proposed. The CALT method is very effective for predicting lifetimes, significantly reducing test time, and quantifying reliability. The fatigue test is performed by considering two high stress and one low stress levels, and the lifetime at the normal stress level is predicted by extrapolation. In addition, in this study, the major reliability parameters such as the lifetime, accelerated power index, shape parameter, and scale parameter are determined by conducting various experiments. The lifetime prediction of the axle drive shaft is verified by comparing the experimental results with load spectrum data. The results confirm that the CALT method is effective for lifetime prediction and requires a short test time.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.21-30
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• 1997

In accelerated life tests, the failure time of an item is observed under a high stress level, and based on the time the performances of items are investigated at the normal stress level. In this paper, when the mean of the prior of a failure rate is known in the exponential lifetime distribution with censored accelerated failure time data, we utilize the empirical Bayesian method by using the moment estimators in order to estimate the parameters of the prior distribution and obtain the empirical Bayesian predictive density and predictive intervals for a future observation under the normal stress level.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.63-82
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• 2014

The main objective of this research is to investigate whether the RFM (recency-frequency-monetary value) information of a customer's redemption behavior of loyalty points can improve the prediction of future value of the customer. The conventional measurement of customer value has been primarily based on purchase transactions behavior although a customer's future behavior can be also influenced by other interactions between the customer and the firm such as redemption of rewards in a loyalty program. We theorize why a customer's redemption behavior can influence her future purchases and thereby the customer's total value based on operant learning theory, goal gradient hypothesis, and lock-in effect. Using a dataset from a major book store in Korea spanning three years between 2008 and 2010, we analyze both purchase transactions and redemption records of over 10,000 customers. The results show that the redemption-based RFM information does improve the prediction accuracy of the customer's future purchases. Based on this result, we also propose an improved estimate of customer lifetime value (CLV) by combining purchase transactions and loyalty points redemption data. Managerial implications will be also discussed for firms managing loyalty programs to maximize the total value customers.

• The Journal of Information Technology
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• v.2 no.2
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• pp.13-22
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• 1999

In this paper, we purpose automatic diagnosis in online, as the fundamental study to diagnose the partial discharge mechanism and to predict the lifetime by introduction a neural network. In the proposed method, we use AE(acoustic emission) sensing system and calculate a quantitative statistic parameter by pulse number and amplitude. Using statically parameters such as the center of gravity(G) and the gradient if the discharge distribute(C), we analyzed the early stage and the middle stage. the quantitative statistic parameters are learned by a neural network. The diagnosis of insulation degradation and a lifetime prediction by the early stage time are achieved. On the basis of revealed excellent diagnosis ability through the neural network learning for the patterns during degradation, it was proved that the neural network is appropriate for degradation diagnosis and lifetime prediction in partial discharge.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3A
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• pp.341-347
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• 2008

Among coating systems used for steel bridge coatings on highway such as red lead-pigmented alkyd, chlorinated rubber, waterborne inorganic zinc, inorganic zinc/epoxy/urethane and inorganic zinc/epoxy/fluororesin, evaluation of deterioration degree and prediction of lifetime through regression analysis were carried out for coating systems widely used and grossly degraded. For evaluation of deterioration degree, 75 bridges on highway were selected, and evaluations were carried out according to point offering method regulated by Guideline of maintenance coating for steel bridges used in Korea Expressway Corporation. Lifetime prediction results showed 13.0~13.3 years for the whole nation, 11.8 years for urban and industrial region in the metropolitan area, 13.2 years for rural region except the metropolitan area, 13.5~13.7 years for chlorinated rubber coating systems, and 12.86 years for red lead-pigmented alkyd systems. For prediction of the rest life of coating, we tried to execute parallel translations of standard deterioration curve to current life and deterioration degree for both x and y axes, and it was thought that parallel translation for x axis corresponded to deterioration aspects in actual environment. Maximum and minimum equations were derived from standard deterioration equation by adding and subtracting error values deduced in regression analysis to/from each coefficient in order to establish maintenance coating criteria for overall steel bridges on highway. Whole domain was divided into 8 parts in order to predict the rest life of coating and optimum time of maintenance coating, and maintenance coating criteria for each 8 domains were presented.