• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1495-1507
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• 2022

The improvement of thermal-hydraulic analysis techniques is essential to ensure the safety and reliability of nuclear power plants. The one-dimensional two-fluid model has been adopted in state-of-the-art thermal-hydraulic system codes. Current constitutive equations used in the system codes reach a mature level. Some exceptions are the partition method of wall friction in the momentum equation of the two-fluid model and the interfacial drag force model for a horizontal two-phase flow. This study is focused on deriving the partition method of wall friction in the momentum equation of the two-fluid model and modeling the interfacial drag force model for a horizontal bubbly flow. The one-dimensional momentum equation in the two-fluid model is derived from the local momentum equation. The derived one-dimensional momentum equation demonstrates that total wall friction should be apportioned to gas and liquid phases based on the phasic volume fraction, which is the same as that used in the SPACE code. The constitutive equations for the interfacial drag force are also identified. Based on the assessments, the Rassame-Hibiki correlation, Hibiki-Ishii correlation, Ishii-Zuber correlation, and Rassame-Hibiki correlation are recommended for computing the distribution parameter, interfacial area concentration, drag coefficient, and relative velocity covariance of a horizontal bubbly flow, respectively.

• Wind and Structures
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• v.17 no.6
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• pp.565-587
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• 2013

Obvious vortex induced vibration (VIV) was observed during section model wind tunnel tests for a single main cable suspension bridge. An optimized section configuration was found for mitigating excessive amplitude of vibration which is much larger than the one prescribed by Chinese code. In order to verify the maximum amplitude of VIV for optimized girder, a full bridge aeroelastic model wind tunnel test was carried out. The differences between section and full aeroelastic model testing results were discussed. The maximum amplitude derived from section model tests was first interpreted into prototype with a linear VIV approach by considering partial or imperfect correlation of vortex-induced aerodynamic force along span based on Scanlan's semi-empirical linear model. A good consistency between section model and full bridge model was found only by considering the correlation of vortex-induced force along span.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.215-221
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• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.727-733
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• 2011

To understand the stock market structure it is very important to extract meaningful information by analyzing the correlation matrix between stock returns. Recently there has been many studies on the correlation matrix using the Random Matrix Theory. In this paper we adopt this random matrix methodology to a single-factor model and we obtain meaningful information on the correlation matrix. In particular we observe the analysis of the correlation matrix using the single-factor model explains the real market data and as a result we confirm the usefulness of the single-factor model.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.201-212
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• 2017

This study presented the new evaluation index which can evaluate the discrimination of DEA models. To evaluate the discrimination of DEA models, data were analyzed using importance index as suggested in previous study and the coefficient of variation as suggested in this study for the discrimination evaluation. This study selected the CCR-DEA, BCC-DEA, entropy, bootstrap, super efficiency, and cross efficiency DEA model for the discrimination evaluation and accomplished empirical analysis. In order to grasp the rank correlation of the models, this study implemented the rank correlation analysis between the efficiency of CCR model and BCC model and entropy, bootstrap, super efficiency, and efficiency of the cross efficiency model. The obtained results of this study are as follows. First, the discrimination rank of models using the importance index and the coefficient of variation was shown to be identical. Therefore, the coefficient of variation can be used the discrimination evaluation index of DEA model. Second, the discrimination of the super efficiency model was found to be the highest rank among 4 models according to the analysis of this present study. Third, the highest rank correlation with CCR model was the super efficiency model. In addition, the super efficiency model was found to be the highest rank correlation with BCC model.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1903-1906
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• 2005

We proposed a new variant of correlation approach for ARMA model. The proposed method is is intended to make the current prediction error uncorrelated with the past one. In the investigation of the properties, the uniqueness, consistency and asymptotic normality of the estimate are shown. Via simulation results, we show that the proposed method give good estimates for various systems.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.105-112
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• 2015

The estimation of missing sensor values is an important problem in sensor network applications, but the existing approaches have some limitations, such as the limitations of application scope and estimation accuracy. Therefore, in this paper, we propose a new estimation model based on a spatial-temporal correlation analysis (STCAM). STCAM can make full use of spatial and temporal correlations and can recognize whether the sensor parameters have a spatial correlation or a temporal correlation, and whether the missing sensor data are continuous. According to the recognition results, STCAM can choose one of the most suitable algorithms from among linear interpolation algorithm of temporal correlation analysis (TCA-LI), multiple regression algorithm of temporal correlation analysis (TCA-MR), spatial correlation analysis (SCA), spatial-temporal correlation analysis (STCA) to estimate the missing sensor data. STCAM was evaluated over Intel lab dataset and a traffic dataset, and the simulation experiment results show that STCAM has good estimation accuracy.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.305-307
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• 1992

This paper presents a technique, which identifies both process noise covariance and sensor noise covariance by using innovation correlation test. A correlation test, which checks whether the square root Kalman filter is workingly optimal or not, is given. The system is stochastic autoregressive moving-average model with auxiliary white noise Input. The linear quadratic Gaussian control is used for minimizing stochastic cost function. This paper indentifies Q, R, and estimates parametric matrics $A(q^{-1}),B(q^{-1}),C(q^{-1})$ by means of extended recursive least squares and model reference control. And The proposed technique has been validated in simulation results on the fourth order system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.825-829
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• 2009

In this paper, we examine the fundamental performance of image coding schemes based on multipulse model. First, we introduce several kinds of pulse search methods (i.e., correlation method, pulse overlap search method and pulse amplitude optimization method) for the model. These pulse search methods are derived from auto-correlation function of impulse responses and cross-correlation function between host signals and impulse responses. Next, we explain the basic procedure of multipulse image coding scheme, which uses the above pulse search methods in order to encode the high frequency component of an original image. Finally, by means of computer simulation for some test images, we examine the PSNR(Peak Signal-to-Noise Ratio) and computational complexity of these methods.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.11a
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• pp.620-621
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• 2010

Thermal models are made to verify the process that operate in space orbit. In this study, thermal analysis model correlation was performed to satisfy the criteria of correlation. Ground thermal vacuum test results are used for the correlation thermal model in the process of thermal model verification.