• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.6
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• pp.804-811
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• 2010

The fatigue crack propagation is stochastic in nature, because the variables affecting the fatigue behavior are random and have uncertainty. Therefore, the fatigue life prediction is critical for the design and the maintenance of many structural components. In this study, fatigue experiments are conducted on the specimens of magnesium alloy AZ31 under various conditions such as thickness of specimen, the load ratio and the loading condition. The probability distribution fit to the fatigue failure life are investigated through a probability plot paper by these conditions. The probabilities of failure at various conditions are also estimated. The fatigue design life is predicted by using the Weibull distribution.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.123-130
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• 2007

Recently, a lot of work and interest have been devoted to the development of multiaxial fatigue parameters for fretting fatigue life prediction. In this study, the fretting fatigue lift and critical location ware estimated and evaluated through the multiaxial fatigue theories in a cylinder-on-flat contact configuration far Cr-Mo steel, SCM420, the material commonly is used in gears of the automobile and rollers of the conveyor. The strain-life curve was obtained from fatigue test for SCM420. The Fretting fatigue life and critical location were estimated through stress distributions, SWT-parameters and FS-parameters obtained from FEA. This paper showed possibility of applying multiaxial fatigue theories to fretting fatigue lift prediction comparing predicted life with experimental results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.4
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• pp.410-418
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• 2004

The multiaxial fatigue test under in-phase and out-of$.$phase load were performed to study what degradation phenomenon affects fatigue life with virgin and 3600 hrs degraded materials. The various kind of fatigue data fur fatigue life prediction were acquired under pure axial and pure torsional load of fully reversal condition. The models which was investigated are: 1) the von Mises equivalent strain range, 2) the critical shear plane approach method of Fatemi-Socie(FS) parameter, 3) the modified Smith-Watson-Topper(SWT) parameter. The result showed that, fatigue life by material degradation are decreased and life prediction which was used the FS parameter is not conservative but the best result.

• Transactions of Materials Processing
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• v.30 no.4
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• pp.172-178
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• 2021

The cold forging process induces material deformation in an enclosed space, generating a very high forging load. Therefore, it is mainly designed as a multi-stage process, and fatigue failure occurs in forging die due to cyclic load. Studies have been conducted previously to quantitatively predict the fatigue limit of cold forging dies, however, there was a limit to field application due to the large error range and the need for expert intervention. To solve this problem, we conducted a study on the introduction of a real-time forging load measurement technology and an automated system for quantitative prediction of die life cycle. As a result, it was possible to reduce the error range of the quantitative prediction of die life cycle to within ±7%, and it became possible to use the die life cycle calculation algorithm into an automated system.

• Smart Structures and Systems
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• v.29 no.6
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• pp.799-805
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• 2022

Permanent magnet synchronous motors (PMSMs) are widely used in systems requiring high control precision, efficiency, and reliability. Predicting the remaining useful life (RUL) with health monitoring of PMSMs prevents catastrophic failure and ensures reliable operation of system. In this study, a model-based method for predicting the RUL of PMSMs using phase current and vibration signals is proposed. The proposed method includes feature selection and RUL prediction based on a particle filter with a degradation model. The Paris-Erdogan model describing micro fatigue crack propagation is used as the degradation model. An experimental set-up to conduct accelerated life test, capable of monitoring various signals was designed in this study. Phase current and vibration data obtained from an accelerated life test of the PMSMs were used to verify the proposed approach. Features extracted from the data were clustered based on monotonicity and correlation clustering, respectively. The results identify the effectiveness of using the current data in predicting the RUL of PMSMs.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.1
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• pp.48-55
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• 2022

This paper proposes a battery remaining useful life (RUL) prediction method using a deep learning-based EMD-CNN-LSTM hybrid method. The proposed method pre-processes capacity data by applying empirical mode decomposition (EMD) and predicts the remaining useful life using CNN-LSTM. CNN-LSTM is a hybrid method that combines convolution neural network (CNN), which analyzes spatial features, and long short term memory (LSTM), which is a deep learning technique that processes time series data analysis. The performance of the proposed remaining useful life prediction method is verified using the battery aging experiment data provided by the NASA Ames Prognostics Center of Excellence and shows higher accuracy than does the conventional method.

• Journal of Korean Academy of Nursing
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• v.39 no.4
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• pp.518-527
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• 2009

Purpose: The purpose of this study was to identify factors influencing quality of life in kidney transplant recipients and to understand the concrete pathway of influence and the power of each variable, so that integrated prediction model to promote the quality of life of kidney transplant recipients could be developed. Methods: The sample was composed of 218 patients in follow-up care after a kidney transplant in one of 4 university hospitals in the Honam area. A structured questionnaire was used and the collected data were analyzed for fitness, using the LISREL program. Results: This model was concise and extensive in predicting the quality of life of kidney transplant recipients. Conclusion: The research verified the factors influencing quality of life for kidney transplant recipients and it verified that direct factors such as perception of health state, compliance, self-efficacy, stress and indirect factors such as self-efficacy and social support can be important factors to predict the quality of life for recipients. Moreover, those variables represent 87% of variance in explaining quality of life in a prediction model so that the variables can be utilized to predict quality of life for kidney transplant recipients.

• Journal of Power System Engineering
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• v.19 no.5
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• pp.45-51
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• 2015

Grade 91 steel is used for the major structural components of Generation-IV reactor systems such as a very high temperature reactor (VHTR) and sodium-cooled fast reactor (SFR). Since these structures are designed for up to 60 years at elevated temperatures, the prediction of long-term creep life is very important to determine an allowable design stress of elevated temperature structural component. In this study, a large body of creep rupture data was collected through world-wide literature surveys, and using these data, the long-term creep life was predicted in terms of three methods: Larson-Miller (L-M), Manson-Haferd (M-H) and Wilshire methods. The results for each method was compared using the standard deviation of error. The L-M method was overestimated in the longer time of a low stress. The Wilshire method was superior agreement in the long-term life prediction to the L-M and M-H methods.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.5
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• pp.921-927
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• 1989

One of the most important problems in recent life prediction is to introduce the degradation effects into life prediction procedure. In the present paper, the effect of the material degradation on the fatigue surface crack growth and fatigue life prediction in a 2 1/4 Cr-1Mo steel were investigated. The 2 1/4 Cr-1Mo steel has been used in a plant having operated for over 60000hours and subjected to material degradation due to temper-embitterment. A Monte-Carlo simulation was made on the basis of the data obtained in the experiment in order to determine the P-S-N diagrams of surface crack growth for the degraded and recovered steels.

• Journal of the Korean Society of Propulsion Engineers
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• v.26 no.5
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• pp.1-10
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• 2022

For Cu-Cr alloy developed for rocket engines, estimated fatigue lives were calculated using various fatigue life prediction methods and compared with fatigue life acquired from low-cycle fatigue tests. The utilized methods for fatigue life prediction are as follows: Coffin-Manson relation, plastic/total strain energy density relations, Smith-Watson-Topper relation, Tomkins relation, and Jahed-Varvani relation. As results of estimation of fatigue lives, it satisfied within scatter band two compared to the test fatigue lives in all methods. The quantitative calculation of the deviation of predicted fatigue lives gives that the total strain energy density relation presents the best result.