• Corrosion Science and Technology
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• v.14 no.1
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• pp.1-11
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• 2015

Local wall thinning and integrity degradation caused by several mechanisms, such as flow accelerated corrosion (FAC), cavitation, flashing and/or liquid drop impingements, are a main concern in carbon steel piping systems of nuclear power plant in terms of safety and operability. Thinned pipe management program (TPMP) had been developed and optimized to reduce the possibility of unplanned shutdown and/or power reduction due to pipe failure caused by wall thinning in the secondary side piping system. This program also consists of several technical elements such as prediction of wear rate for each component, prioritization of components for inspection, thickness measurement, calculation of actual wear and wear rate for each component. Decision making is associated with replacement or continuous service for thinned pipe components. Establishment of long-term strategy based on diagnosis of plant condition regarding overall wall thinning is also essential part of the program. Prediction models of wall thinning caused by FAC had been established for 24 operating nuclear plants. Long term strategies to manage the thinned pipe component were prepared and applied to each unit, which was reflecting plant specific design, operation, and inspection history, so that the structural integrity of piping system can be maintained. An alternative integrity assessment criterion and a computer program for thinned piping items were developed for the first time in the world, which was directly applicable to the secondary piping system of nuclear power plant. The thinned pipe management program is applied to all domestic nuclear power plants as a standard procedure form so that it contributes to preventing an accident caused by FAC.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.4
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• pp.87-92
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• 1999

Generally the life of die is limited by fatigue fracture or dimensional inaccuracy originated from wear. In this paper to predict the fatigue life of die the stress and strain histories of die can be predicted by the analysis of elastic-plastic finite element method and the elastic analysis of die during the process analysis of workpiece. Also the stress-life curve of die material can be obtained through experiment. With the above to재 facts we propose the analysis method of prediction fatigue life in die,. In the proposed model the analysis of elastic-plastic finite element method for material is carried out by using ABAQUS. Surface force resulted from the contacting border of the die and workpiece is transformed into the nodal force of die to implement elastic analysis. besides the proposed analysis model of die is applied to extrusion die and forging. die.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.2
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• pp.453-467
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• 2018

The excavation performance and the cutting tool wear prediction of shield TBM are very important issues for design and construction in TBM tunneling. For hard-rock TBMs, CSM and NTNU model have been widely used for prediction of disc cutter wear and penetration rate. But in case of soft-ground TBMs, the wear evaluation and the excavation performance have not been studied in details due to the complexity of the ground behavior and therefore few testing methods have been proposed. In this study, a new soil abrasion and penetration tester (SAPT) that simulates EPB TBM excavation process is introduced which overcomes the drawbacks of the previously developed soil abrasivity testers. Parametric tests for penetration rate, foam mixing ratio, foam concentration were conducted to evaluate influential parameters affecting TBM excavation and also ripper wear was measured in laboratory. The results of artificial soil specimen composed of 70% illite and 30% silica sand showed TBM additives such as foam play a key role in terms of excavation and tool wear.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.39-58
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• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.

• Tribology and Lubricants
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• v.18 no.2
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• pp.160-166
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• 2002

In case of rough contact fatigue, the accurate calculation of surface tractions is essential to the prediction of crack initiation life. Accurate Surface tractions influencing shear stress amplitude can be obtained by contact analysis based on the morphology of contact surfaces. In this study, to simulate rough contact under sliding condition, gaussian rough surface generated numerically in the previous study was used and to calculate clack initiation life in the substrate, dislocation pileup theory was used.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2000.11a
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• pp.72-79
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• 2000

In case of rough contact fatigue, the accurate calculation of surface tractions is essential to the prediction of crack initiation life. Accurate Surface tractions influencing shear stress amplitude can be obtained by contact analysis based on tile morphology of contact surfaces. In this study, to simulate rough contact under sliding condition, gaussian rough surface generated numerically in the previous study was used and to calculate crack initiation life in the substrate, dislocation pileup theory was used.

• The Journal of Bigdata
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• v.4 no.1
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• pp.29-38
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• 2019

In this paper, we propose a sales forecasting model that forecasts the sales volume of short sleeves and outerwear according to the temperature change by utilizing accumulated big data from the online shopping mall 'A' over the past five years to increase sales volume and efficient inventory management. The proposed model predicts sales of short sleeves and outerwear according to temperature changes in 2018 by analyzing sales volume of short sleeves and outerwear from 2014 to 2017. Using the proposed sales forecasting model, we compared the sales forecasts of 2018 with the actual sales volume and found that the error rates are ±1.5% and ±8% for short sleeve and outerwear respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1193-1215
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• 2021

The measurement of the key product quality index plays an important role in improving the production efficiency and ensuring the safety of the enterprise. Since the actual working conditions and parameters will inevitably change to some extent with time, such as drift of working point, wear of equipment and temperature change, etc., these will lead to the degradation of the quality variable prediction model. To deal with this problem, the selective integrated moving windows based principal component regression (SIMV-PCR) is proposed in this study. In the algorithm of traditional moving window, only the latest local process information is used, and the global process information will not be enough. In order to make full use of the process information contained in the past windows, a set of local models with differences are selected through hypothesis testing theory. The significance levels of both T - test and χ² - test are used to judge whether there is identity between two local models. Then the models are integrated by Bayesian quality estimation to improve the accuracy of quality variable prediction. The effectiveness of the proposed adaptive soft measurement method is verified by a numerical example and a practical industrial process.

• Journal of Applied Reliability
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• v.11 no.4
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• pp.387-398
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• 2011

$217Plus^{TM}$, a newly developed as a surrogate of the MIL-HDBK-217, may be widely applied for reliability predictions of electronic systems. In this study, we performed sensitivity study of the $217Plus^{TM}$ system model to various parameters. Specific attention was put to logistics model and its behavior has been examined in terms of non-component failure causes. We first briefly explained the $217Plus^{TM}$ methodology with system level failure rate evaluation. We then applied experimental designs with several failure causes as factors. We used an orthogonal array with three levels of each parameter. Our results indicate that cannot duplicate, induced, and wear-out causes have dominant effects on the system failures and design, parts, and system management have much less but a little strong effects. The results in this study not only figure out the behavior of the predicted failure rate as functions of failure causes but provide meaningful guidelines for practical applications.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.836-842
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• 2001

The more sophisticated patterns of propagation model is presented in this paper, which includes three different source characteristics. The spherical, cosine and dipole radiation characteristics compared and sound event level and the maximum sound level are calculated by experiment and calculation. It is shown that patterns of propagation has dipole characteristics for low speed range(below about 150km/h) at electric multiple system. We know that push-pull high speed system(maximum speed: 300km/h) has cosine characteristics of noise propagation. For this purpose, We conduct the experiment of noise and know the empirical formula of noise level and radiation coefficient K. This model of simulation is conducted through point source array model at wheel/rail contact point by using program and experimental formula. We can guess prediction of profile, flat and wear of wheel by above modeling in near field.