• Nuclear Engineering and Technology
• /
• v.55 no.12
• /
• pp.4561-4569
• /
• 2023

A correct understanding of vibration-based degradation is crucial from the standpoint of maintenance for Steam Generators (SG) as crucial mechanical equipment in nuclear power plants. This study has established a novel approach to developing a model for investigating tube bundle degradation according to crack growth caused by two-phase Flow-Induced Vibration (FIV). An important step in the approach is to calculate the two-phase flow field parameters between the SG tube bundles in various zones using the porous media model to determine the velocity and vapor volume fraction. Afterward, to determine the vibration properties of the tube bundles, the Fluid-Solid Interaction (FSI) analysis is performed in eighteen thermal-hydraulic zones. Tube bundle degradation based on crack growth using the sixteen most probable initial cracks and within each SG thermal-hydraulic zone is performed to calculate useful lifetime. Large Eddy Simulation (LES) model, Paris law, and Wiener process model are considered to model the turbulent crossflow around the tube bundles, simulation of elliptical crack growth due to the vibration characteristics, and estimation of SG tube bundles degradation, respectively. The analysis shows that the tube deforms most noticeably in the zone with the highest velocity. As a result, cracks propagate more quickly in the tube with a higher height. In all simulations based on different initial crack sizes, it was observed that zone 16 experiences the greatest deformation and, subsequently, the fastest degradation, with a velocity and vapor volume fraction of 0.5 m/s and 0.4, respectively.

• Journal of the Korea Computer Graphics Society
• /
• v.6 no.3
• /
• pp.9-15
• /
• 2000

We Propose a sensor fusion technique for motion capture system. In our system, two kinds of sensors are used for mutual assistance. Four magnetic sensors(markers) are attached on the upper arms and the back of the hands for assisting twelve optical sensors which are attached on the arms of a performer. The optical sensor information is not always complete because the optical markers can be hidden due to obstacles. In this case, magnetic sensor information is used to link discontinuous optical sensor information. We use a system identification techniques for modeling the relation between the sensors' signals. Dynamic systems are constructed from input-output data. We determine the best model from the set of candidate models using the canonical system identification techniques. Our approach is using a simple signal processing technique currently. In the future work, we will propose a new method using other signal processing techniques such as Wiener or Kalman filter.

• Journal of the Korea Society for Simulation
• /
• v.17 no.3
• /
• pp.19-26
• /
• 2008

In this paper, we propose a dynamic prediction algorithm to predict the bond price using actual data set of treasure note (T-Note). The proposed algorithm is based on term structure model of the interest rates, which takes place in various financial modelling, such as the standard Gaussian Wiener process. To obtain cumulative distribution functions (CDFs) of actual data for the interest rate measurement used, we use the natural cubic spline (NCS) method, which is generally used as numerical methods for interpolation. Then we also use the random number generation scheme (RNGS) to calculate the pricing of bond through the obtained CDF. In empirical computer simulations, we show that the lower values of precision in the proposed prediction algorithm corresponds to sharper estimates. It is very reasonable on prediction.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.8C
• /
• pp.795-802
• /
• 2003

It is very important to construct statistical model in order to exactly estimate the signal variance from a noisy image. In order to estimate variance, information of neighboring region is used generally. The size of neighbor region is varied according to the regional characteristics of image. More accurate estimation of edge variance is due to smaller region of neighbor, on the other hands, larger region of neighbor is used to estimate the variance of flat region. By using estimated variance of original image, in general, Wiener filter is constructed, and it is applied to the noisy image. In this paper, we propose a new method for determining the range of neighbors to estimate the variance in wavelet domain. Firstly, a significance map is constructed using the parent-child relationship of wavelet domain. Based on the number of the significant wavelet coefficients, the range of neighbors is determined and then the variance of the original signal is estimated using ML(maximum likelihood method. Experimental results show that the proposed method yields better results than conventional methods for image denoising.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.32 no.3
• /
• pp.147-160
• /
• 2020

A stochastic probabilistic model for harbor structures such as rubble-mound breakwater has been formulated by using the generalized Wiener process considering the nonlinearity of damage drift and its nonlinear uncertainty, by which the damage path with real-time can be tracked, the residual useful lifetime at some age can also be analyzed properly. The formulated stochastic model can easily calculate the probability of failure with the passage of time through the probability density function of cumulative damage. In particular, the probability density functions of residual useful lifetime of the existing harbor structures can be derived, which can take into account the current age, its present damage state and the future damage process to be occurred. By using the maximum likelihood method and the least square method together, the involved parameters in the stochastic model can be estimated. In the calibration of the stochastic model presented in this paper, the present results are very well similar with the results of MCS about tracking of the damage paths as well as evaluating of the density functions of the cumulative damage and the residual useful lifetime. MTTF and MRL are also evaluated exactly. Meanwhile, the stochastic probabilistic model has been applied to the rubble-mound breakwater. The related parameters can be estimated by using the experimental data of the cumulative damages of armor units measured as a function of time. The theoretical results about the probability density function of cumulative damage and the probability of failure are very well agreed with MCS results such that the density functions of the cumulative damage tend to move to rightward and the amounts of its uncertainty are increased as the elapsed time goes on. Thus, the probabilities of failure with the elapsed time are also increased sharply. Finally, the behaviors of residual useful lifetime have been investigated with the elapsed age. It is concluded for rubble-mound breakwaters that the probability density functions of residual useful lifetime tends to have a longer tail in the right side rather than the left side because of the gradual increases of cumulative damage of armor units. Therefore, its MRLs are sharply decreased after some age. In this paper, the special attentions are paid to the relationship of MTTF and MRL and the elapsed age of the existing structure. In spite of that the sum of the elapsed age and MRL must be equal to MTTF deterministically, the large difference has been shown as the elapsed age is increased which is due to the uncertainty of cumulative damage to be occurred in the future.

• ETRI Journal
• /
• v.38 no.3
• /
• pp.510-517
• /
• 2016

Recent developments in the field of separation of mixed signals into music/voice components have attracted the attention of many researchers. Recently, iterative kernel back-fitting, also known as kernel additive modeling, was proposed to achieve good results for music/voice separation. To obtain minimum mean square error (MMSE) estimates of short-time Fourier transforms of sources, generalized spatial Wiener filtering (GW) is typically used. In this paper, we propose an advanced music/voice separation method that utilizes a generalized weighted ${\beta}$-order MMSE estimation (WbE) based on iterative kernel back-fitting (KBF). In the proposed method, WbE is used for the step of mixed music signal separation, while KBF permits kernel spectrogram model fitting at each iteration. Experimental results show that the proposed method achieves better separation performance than GW and existing Bayesian estimators.

• Journal of electromagnetic engineering and science
• /
• v.6 no.4
• /
• pp.203-208
• /
• 2006

Channel estimation and data detection for OFDM systems over time- and frequency-selective channels are investigated. Relying on the complex exponential basis expansion channel model, a pilot-embedded channel estimation scheme with low computational complexity and spectral efficiency is proposed. A periodic pilot sequence is superimposed at a low power on information bearing sequence at the transmitter before modulation and transmission. The channel state information(CSI) can be estimated using the first-order statistics of the received data. In order to enhance the performance of channel estimation, we recover the transmitted data which can be exploited to estimate CSI iteratively. Simulation results show that the proposed method is suitable for doubly-selective channel estimation for the OFDM systems and the performance of the proposed method can be better than that of the Wiener filter method under some conditions. Through simulations, we also analyze the factors which can affect the system performances.

• Communications for Statistical Applications and Methods
• /
• v.9 no.1
• /
• pp.75-86
• /
• 2002

We consider the problem of estimating the change-point in mean change model with one change-point. Gombay and Huskova(1998) derived a class of change-point estimators with the score function of rank. A change-point estimator with the log score function of rank is suggested and is shown to be involved in the class of Gombay and Huskova(1988). The simulation results show that the proposed estimator has smaller rose, larger proportion of matching the true change-point than the other estimators considered in the experiment when the change-point occurs in the middle of the sample.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.05a
• /
• pp.1016-1019
• /
• 2002

This paper deals with a fundamental and classical scattering problem by a finite strip. For the analysis of scattered acoustic field, a “single” integral equation is derived. Firstly, the complexity by considering the effect of the mean flow is alleviated by the introduction of Prandtl-Glauert coordinate and the new dependent variable. Secondly, the difficulty of solving the resultant strongly-coupled integral equations which always appear in this kind of 3-part mixed boundary value problem is solved by observing some good properties of the functions in complex domain and manipulating the equations and variables for the use of those properties. The solution can be obtained asymptotically in terms of gamma function and Whittaker function. One aim of this study is the improvement of methodology for the research using integral equations. The other is the basic understanding of scattering by a finite strip related to the linear cascade model of rotating fan blades.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2011.11a
• /
• pp.321-324
• /
• 2011

본 논문에서는 contourlet 변환을 이용하여 잡음을 제거하는 방법을 제안한다. 영상 센서의 발전으로 이미지의 해상도가 좋아지는 반면 잡음에 민감해진다. 그러므로 이를 전처리 단계에서 처리해주는 것이 필요하다. 잡음은 주로 자연 영상의 윤곽선에서 민감하게 반응하기 때문에 고주파대의 잡음을 최대한 정확하게 제거하는 과정이 중요하다. Contourlet 변환은 기존의 wavelet 변환의 다중 스케일과 더불어 다양한 방향 필터뱅크를 이용하여 방향 성분에 대하여 풍부한 정보를 얻을 수 있는 변환이다. 영상의 화이트 가우시안 잡음을 제거하기 위해 contourlet 변환 영역에서의 계수를 이변수 가우스 확률 모델로 설정하고 Bayes 추정법을 사용한다. Bayes 추정법에 필요한 파라미터들은 근사적으로 추정한다. 제안한 방식을 통하여 잡음이 제거된 영상에 추가적으로 Wiener filter와 cycle-spinning을 적용하여 더 높은 PSNR (peak signal-to-noise ratio)값을 얻을 수 있다. 모의실험을 통해 제안한 방식의 PSNR 값과 결과영상으로 성능이 우수함을 확인하였다.