• Korean Journal of Metals and Materials
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• v.49 no.4
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• pp.275-280
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• 2011

This paper focuses on reliability prediction of long-term creep strength for Modified 9Cr-1Mo steel (Gr. 91) which is considered as one of the structural materials of next generation reactor systems. A "Z-parameter" method was introduced to describe the magnitude of standard deviation of creep rupture data to the master curve which can be plotted by log stress vs. The larson-Miller parameter (LMP). Statistical analysis showed that the scattering of the Z-parameter for the Gr. 91 steel well followed normal distribution. Using this normal distribution of the Z-parameter, the various reliability curves for creep strength design, such as stress-time temperature parameter reliability curves (${\sigma}$-TTP-R curves), stress-rupture time-reliability curves (${\sigma}-t_{r}-R$ curves), and allowable stress-temperature- reliability curves ([${\sigma}$]-T-R curves) were reasonably drawn, and their results are discussed.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.667-680
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• 2021

We investigated changes in frost days and frost-free periods and to comparatively assess frost event prediction models developed using logistic regression (LR), random forest (RF), and long short-term memory (LSTM) networks. The meteorological variables for the model development were collected from the Suwon, Cheongju, and Gwangju stations for the period of 1973-2019 for spring (March - May) and fall (September - November). The developed models were then evaluated by Precision, Recall, and f-1 score and graphical evaluation methods such as AUC and reliability diagram. The results showed that significant decreases (significance level of 0.01) in the frequencies of frost days were at the three stations in both spring and fall. Overall, the evaluation metrics showed that the performance of RF was highest, while that of LSTM was lowest. Despite higher AUC values (above 0.9) were found at the three stations, reliability diagrams showed inconsistent reliability. A further study is suggested on the improvement of the predictability of both frost events and the first and last frost days by the frost event prediction models and reliability of the models. It would be beneficial to replicate this study at more stations in other regions.

• Journal of the Korea Safety Management & Science
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• v.26 no.1
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• pp.39-44
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• 2024

In order to prevent accidents via defective ammunition, this paper analyzes recent research on ammunition life prediction methodology. This workanalyzes current shelf-life prediction approaches by comparing the pros and cons of physical modeling, accelerated testing, and statistical analysis-based prediction techniques. Physical modeling-based prediction demonstrates its usefulness in understanding the physical properties and interactions of ammunition. Accelerated testing-based prediction is useful in quickly verifying the reliability and safety of ammunition. Additionally, statistical analysis-based prediction is emphasized for its ability to make decisions based on data. This paper aims to contribute to the early detection of defective ammunition by analyzing ammunition life prediction methodology hereby reducing defective ammunition accidents. In order to prepare not only Korean domestic war situation but also the international affairs from Eastern Europe and Mid East countries, it is very important to enhance the stability of organizations using ammunition and reduce costs of potential accidents.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.413-418
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• 2020

It is necessary to manage the prediction accuracy of the machine learning model to prevent the decrease in the performance of the grid network condition prediction model due to overfitting of the initial training data and to continuously utilize the prediction model in the field by maintaining the prediction accuracy. In this paper, we propose an automation technique for maintaining the performance of the model, which increases the accuracy and reliability of the prediction model by considering the characteristics of the power grid state data that constantly changes due to various factors, and enables quality maintenance at a level applicable to the field. The proposed technique modeled a series of tasks for maintaining the performance of the power grid condition prediction model through the application of the workflow management technology in the form of a workflow, and then automated it to make the work more efficient. In addition, the reliability of the performance result is secured by evaluating the performance of the prediction model taking into account both the degree of change in the statistical characteristics of the data and the level of generalization of the prediction, which has not been attempted in the existing technology. Through this, the accuracy of the prediction model is maintained at a certain level, and further new development of predictive models with excellent performance is possible. As a result, the proposed technique not only solves the problem of performance degradation of the predictive model, but also improves the field utilization of the condition prediction model in a complex power grid system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.269-273
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• 1998

The failure of material structures or mechanical system is considered as a direct or indirect result of fatigue. In the design of mechanical structure for estimating of reliability, the prediction of failure life is the most important failure mode to be considered. However, because of a complicated behavior of fatigue in mechanical structure, the analysis of fatigue is in need of much researches on life prediction. This document presents a prediction of fatigue life of the SAPH45 steel, which is extensively for vehicle frame. The method using lethargy coefficient and stress distribution factor at pediction of fatigue life based on the consideration of the failure characteristics from the tensile test should be provided in this study.

• Journal of the Semiconductor & Display Technology
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• v.10 no.4
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• pp.25-29
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• 2011

Emerging demands for rechargeable battery for various applications needs more effective battery management system such as the prediction of the usable time about a battery. Many prediction methods have been suggested but none of them come into bounds of reliability. In this paper, we proposed a new prediction algorithm for the remaining capacity of a rechargeable battery by using the transformed curve based on its impedance. Hardware for monitoring a battery was designed and made. Through a series of experiment, we showed the effectiveness of the proposed prediction algorithm of a battery's remaining capacity.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2610-2615
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• 2021

The prediction of irradiation-induced transition temperature shift for RPV steels is an important method for long term operation of nuclear power plant. Based on the irradiation embrittlement data, an irradiation-induced transition temperature shift prediction model is developed with machine learning method XGBoost. Then the residual, standard deviation and predicted value vs. measured value analysis are conducted to analyze the accuracy of this model. At last, Cu content threshold and saturation values analysis, temperature dependence, Ni/Cu dependence and flux effect are given to verify the reliability. Those results show that the prediction model developed with XGBoost has high accuracy for predicting the irradiation embrittlement trend of RPV steel. The prediction results are consistent with the current understanding of RPV embrittlement mechanism.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.48-54
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• 2023

Guided missiles are a one-shot system that finishes their purpose after being used once, and due to the long-term storage until launch, the storage reliability is calculated during development, and performance is maintained through periodic inspections until the life cycle arrives. However, the reliability standards applied in the development of guided missiles were established by analyzing data accumulated by the United States during long-term operation in the country, and since they are different from our environment, the 00 guided missiles that have been deployed in the armed forces for more than 10 years under the premise that there is a difference from actual reliability. As a result of verifying the appropriateness of the current inspection cycle by analyzing the actual reliability of the missile, the necessity of changing the inspection period was derived because it was higher than the predicted reliability. It is proposed to build and utilize a lifespan management system that can systematically collect all data such as shooting and maintenance results by classification, and to establish a reliable reliability standard based on the accumulated data.

• Computers and Concrete
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• v.17 no.1
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• pp.87-106
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• 2016

This paper deals with the reliability analysis of design formulations derived for predicting the punching shear capacity of FRP-reinforced two-way slabs. Firstly, a new design code formulation was derived by means of gene expression programming. This formulation differs from the existing ones as the slab length (L) was introduced in the equation. Next, the proposed formulation was tested for its generalization capability by a parametric study. Then, the stochastic analyses of derived and existing formulations were performed by Monte Carlo simulation. Finally, the reliability analyses of these equations were carried out based on the results of stochastic analysis and the ultimate state function of ASCE-7 and ACI-318 (2011). The results indicate that the prediction performance of new formulation is significantly higher as compared to available design equations and its reliability index is within acceptable limits.

• Smart Structures and Systems
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• v.14 no.4
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• pp.559-567
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• 2014

The model of unit dynamic reliability of repairable k/n (G) system with unit strength degradation under repeated random shocks has been developed according to the stress-strength interference theory. The unit failure number is obtained based on the unit failure probability which can be computed from the unit dynamic reliability. Then, the transfer probability function of the repairable k/n (G) system is given by its Markov property. Once the transfer probability function has been obtained, the probability density matrix and the steady-state probabilities of the system can be retrieved. Finally, the dynamic reliability of the repairable k/n (G) system is obtained by solving the differential equations. It is illustrated that the proposed method is practicable, feasible and gives reasonable prediction which conforms to the engineering practice.