• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.296-297
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• 2011

A series of thermogravimetric analysis tests were conducted to predict the lifetime of the PTFE electrical insulation material. The prepared PTFE samples were heated from $25^{\circ}C$ to $700^{\circ}C$ at different heating rates. The kinetic energy of the PTFE was calculated from the logarithmic heating rate versus reciprocal temperature curves at constant conversion levels. Also, the lifetime of the PTFE for a given operating temperature can be predicted using the relationship between the activation energy and the estimated lifetime proposed by Toop.

• Journal of Applied Reliability
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• v.6 no.2
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• pp.135-150
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• 2006

Rubber material properties and lifetime evaluation are very important in design procedure to assure the safety and reliability of the rubber components. This paper discusses the failure mechanism and material tests were carried out to predict the useful lifetime of NBR and EPDM for compression motor, which is used in refrigerator component. The heat-aging process leads not only to mechanical properties change but also to chemical structure change so called degradation. In order to investigate the aging effects on the material properties, the accelerated test were carried out. The stress-strain curves were plotted from the results of the tensile test for virgin and heat-aged rubber specimens. The rubber specimens were heat-aged in an oven at the temperature ranging from $70^{\circ}C\;to\;100^{\circ}C$ for a period ranging from 1 to 180 days. Compression set results changes as the threshold are used for assessment of the useful life and time to threshold value were plotted against reciprocal of absolute temperature to give the Arrhenius plot. By using the compression set test, several useful lifetime prediction equations for rubber material were proposed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.12
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• pp.1379-1385
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• 2014

Even the rough prediction of the product test time before the lifetime test of mechanical component begins would be of use in estimating cost and deciding how to keep up with the test. The reliability predictions of mechanical components are difficult because failure or degradation mechanisms are complicated, and few plausible databases are available for lifetime prediction. Therefore, this study conducted lifetime predictions of elastomeric U seals that were respectively installed in a hydraulic actuator and a pneumatic actuator using lifetime models and a field database based on failure physics and an actual test database obtained from the NSWC handbook. To validate the results, the predicted failure rates were compared with the actual lifetime test results acquired in the lab durability tests. Finally, this study discussed an engineering procedure to determine the coefficients in the failure rate models and analyzed the sensitivity of each influential parameter on the seal lifetime.

• Proceedings of the Korean Reliability Society Conference
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• 2006.05a
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• pp.158-164
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• 2006

The creep behavior of newly developed composite geogrids which consists of PET yarns sheathed in PP were evaluated using SIM. For the SIM procedure, three test parameters, the applied loads, temperature steps and number of ribs were investigated, The study confirmed that temperature steps of 10 and 14$^{\circ}C$ up to 80$^{\circ}C$ are applicable for composite geogrids due to the different transition temperatures between two materials. At applied loads of 40 and 50%, only primary creep state was measured, while secondary creep state appeared at the applied loads of 60%, The lifetimes of composite geogrids were estimated at each of loading level using statistical reliability analysis technique. The results show that the lifetimes longer than 100 years can be predicted within 16 hours. Therefore, SIM is very effective and economical accelerated creep test methods, especially for lifetime prediction. This gives guidelines for users to select the appropriate factor of safety against creep considering the field condition within shorter test times.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.8
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• pp.828-832
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• 2015

This study is conducted for the evaluation of corrosion and lifetime prediction of fire extinguishing pipelines in residential buildings. The fire extinguishing pipeline is made of carbon steel. Twenty-four samples were selected among all the fire extinguishing pipelines in a building; the selection was based on specimenspositions, pipeline diameters, and pipeline thickness. Analysis was conducted by using the results of visual inspection, electrochemical potentiodynamic anodic polarization test, pitting depth measurements, and extreme value statistics with the Gumbel distribution. The maximum pitting depth and remaining life were statistically predicted using extreme value statistics. During visual inspection, pitting corrosion was observed in several samples. In addition, extreme value statistics demonstrated that there were several pipelines that were very sensitive to pitting corrosion. However, the pitting corrosion was not critical in all the pipelines; thus, it was necessary to change only those pipelines that were severely corroded.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1446-1452
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• 1994

In this paper, Weibull distribution is applied to the lifetme distribution of a device. The method of Bayesian estimate used to estimate requiring parameter in order to predict lifetime of device using accelerated lifetime test data, namely failure time of device. The method of Bayesian estimate needs prior information in order to estimate parameter. But this paper proposed the method of parameter estimate without prior information. As stress is temperature, Arrhenius model is applied and the method of linear estimate is applied to predict lifetime of device at the state of normal operation.

• Journal of the Korean Society of Safety
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• v.34 no.1
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• pp.8-13
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• 2019

Weight and elongation changes of IV and HIV insulations were measured simultaneously at several given temperature of $80^{\circ}C$, $90^{\circ}C$ and $100^{\circ}C$. And the lifetime was predicted using the Arrhenius model. Based on the initial weight values, a 50% elongation reduction was seen at 6.96% for the IV insulation and 10.29% for the HIV insulation. The activation energy from the slope of the lifetime regression equation was calculated as 92.895 kJ/mol(0.9632 eV) for the IV insulation and 95.213 kJ/mol(0.9873 eV) for the HIV insulation. Also, the expected lifetime at the operating temperature of $30^{\circ}C$ to $90^{\circ}C$ is 2.02 to 94.32 years, and longer lifetime was predicted on HIV insulated wires than on IV insulated wires. As a result, it was found that the thermal characteristics of the HIV insulated wires were about 12.44% better than those of IV insulated wires under the same conditions of use.

• Proceedings of the KIEE Conference
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• 1998.11c
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• pp.910-912
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• 1998

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, Ire use acoustic emission sensing system and calculate a fixed quantity statistic operator by pulse number and amplitude. Using statically operators such as the center of gravity(G) and the gradient of the discharge distribute(C), we analyzed the early stage and the middle stage. the fixed quantity statistic operators 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.

• Journal of the Korean Society for Railway
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• v.8 no.5
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• pp.439-443
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• 2005

The biggest challenge bridge agencies face is the maintenance of bridges, keeping them safe and serviceable, with limited funds. To maintain the bridges effectively, there is and urgent need to predict their remaining life from a system reliability viewpoint. In this paper, a model using lifetime functions to evaluate the overall system probability of survival of a rail road bridge is proposed. In this model, the rail load bridge is modeled as a system. Using the model, the lifetime of the rail road bridge is predicted.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.423-424
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• 2016

Recently, the mass production of Energy storage system (ESS) is actively perform around world. Energy storage system is a technique that stores power to energy storage device to supply energy into grid and load at peak-load. Therefore, the efficient energy management is available by using ESS system. The life of Lithium-ion battery is varied corresponding to the power usage, especially selected depth of discharge (DOD). The lifetime of battery is the one of the most issue of the ESS system because of its stability and reliability. Therefore, lifetime management of battery and power converter of ESS module is required. In this paper, the battery lifetime management method estimating residual power and lifetime of lithium ion battery of ESS system is proposed. Also, total avenue prediction of ESS system is simulated considering the total lifetime of battery.