• 대한기계학회논문집B
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• 제20권11호
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• pp.3589-3597
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• 1996

The Reynolds-averaged Navier-Stokes equations with the equations of the k-.epsilon. turbulence model are solved numerically in a general curvilinear system for a three-dimensional turbulent flow around an Ahmed body. The simulation is especially aimed at the evaluation of three finite differencing schemes for the convection term, which include the upwind differencing scheme(UDS), the second order upwind differencing scheme(SOU scheme) and the QUICK scheme. The drag coefficient, the velocity and pressure fields are found to be changed considerably with the adopted finite differencing schemes. It is clearly demonstrated that the large difference between computation and experiment in the drag coefficient is due to relatively high predicted values of pressure drag from both front part and vertical rear end base. The results also show that the simulation with the QUICK or SOU scheme predicts fairly well the flow field and gives more accurate drag coefficient than other finite differencing scheme.

• 오토저널
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• 제11권3호
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• pp.29-36
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• 1989

A multidimensional numerical simulation for flows in an engine with axisymmetric geometry was performed. Three kinds of differencing schemes, namely, skew upwind differencing scheme (SUDS), interpolated upwind differencing scheme (IUDS), upwind differencing scheme (UDS), are used in a comparative study. Simultaneously, the effects of the artificial dampings and the grids on numerical results are estimated. Compared with the measurements, the calculations with SUDS and proper artificial damping show very similar qualitative tendency with observed results. But there are some discrepancies due to numerical errors and unclear boundary conditions.

• 한국유체기계학회 논문집
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• 제6권1호
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• pp.23-29
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• 2003

Three-dimensional flow through a tubular centrifugal fan with airfoil type blades is analyzed, and the effects of turbulence model and numerical scheme on the results are investigated. Standard $k-{\epsilon}$ model and k - w model are tested as turbulence closures. The numerical schemes for convection terms, i.e., Upwind Differencing Scheme (UDS), Mass Weighted Skewed upstream differencing scheme (MWS), Linear Profile Skewed upstream differencing scheme (LPS), and Modified Linear Profile Skewed upstream differencing scheme (MLPS) are also tested, and the performances of these schemes coupled with two turbulence models are evaluated. The static pressure distributions are compared with experimental data obtained in this work, which shows that the $k-{\epsilon}$ model gives better results than the k-w model.

• 대한기계학회논문집B
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• 제23권1호
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• pp.104-113
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• 1999

A hybrid spatial differencing scheme for the discrete ordinates method is proposed to predict radiative heat transfer in two-dimensional rectangular enclosures. Since this scheme takes the advantages of the diamond scheme and step scheme and includes the characteristics of medium, more accurate and stable results can be obtained. In its development several spatial differencing schemes are examined to address the effect of numerical smearing (or false scattering). Predictions from the proposed hybrid scheme are compared to those of other schemes for transparent, purely absorbing, purely scattering, or absorbing-emitting-isotropically scattering media. It is found that the proposed scheme predicts stable and less smeared results than others.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2001년도 유체기계 연구개발 발표회 논문집
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• pp.23-29
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• 2001

Three-dimensional flow through a tubular centrifugal fan with airfoil type blades are analyzed using CFX-TASCflow. Standard k - $\epsilon$ model and k - $\omega$ model are used as turbulence closures. The numerical schemes for convetion terms, i.e., Upwind Differencing Scheme(UDS), Mass Weighted Skewed Upstream Differencing Scheme(MWS), Linear Profile Skewed Upstream Differencing Scheme(LPS), and Modified Linear Profile Skewed Upstream Differencing Scheme(MLPS) are also tested. And, the performance of these schemes coupled with two turbulence models are evaluated. Computational static pressure distributions are compared with experimental data obtained in this work.

• 설비공학논문집
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• 제11권1호
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• pp.73-80
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• 1999

This paper describes a numerical study of three-dimensional buoyant turbulent flow in a stairwell model with three convective differencing schemes, which include the upwind differencing scheme, the hybrid scheme and QUICK scheme. The Reynolds-averaged Navier-Stokes and energy equations are solved with a two-equation turbulence model. The Boussinesq approximation is used to model buoyancy terms in the governing equations. Three-dimensional predictions of the velocity and temperature fields are presented and are compared with experimental data. Three-dimensional simulations with each scheme have predicted the overall features of the flow fairly satisfactorily. A better agreement with experimental is achieved with QUICK scheme.

• Communications for Statistical Applications and Methods
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• 제26권5호
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• pp.497-506
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• 2019

Forecasting the U.S. employment level is made using machine learning methods of the artificial neural network: deep neural network, long short term memory (LSTM), gated recurrent unit (GRU). We consider the big data of the federal reserve economic data among which 105 important macroeconomic variables chosen by McCracken and Ng (Journal of Business and Economic Statistics, 34, 574-589, 2016) are considered as predictors. We investigate the influence of the two statistical issues of the dimension reduction and time series differencing on the machine learning forecast. An out-of-sample forecast comparison shows that (LSTM, GRU) with differencing performs better than the autoregressive model and the dimension reduction improves long-term forecasts and some short-term forecasts.

• Smart Structures and Systems
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• 제28권6호
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• pp.811-825
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• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• 전자공학회논문지
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• 제53권8호
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• pp.95-104
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• 2016

배열 안테나를 이용한 부공간 (subspace) 기반의 도래각 추정 알고리즘은 다중 경로에 의해 나타나는 coherent 신호가 입사하는 경우 원 신호 공분산 행렬의 특이성 (singularity)으로 인해 도래각 추정 정확도가 급격히 감소한다. Coherent 신호에 의한 도래각 추정 알고리즘의 성능 저하를 극복하기 위해 제안된 공간 차이 기법 (spatial differencing method)은 coherent 신호의 도래각 추정뿐만 아니라 안테나 개수 이상의 신호원을 추정하는 기법으로 주목받았다. 그러나, 공간 차이 기법은 수신 신호의 유한한 표본 수에 의해 발생하는 uncorrelated 신호 간의 상관관계 (correlation)에 따라 도래각 추정 성능이 크게 영향을 받는 구조적 문제가 존재한다. 이러한 문제를 극복하기 위해, 본 논문에서는 획득한 수신 신호의 정보를 최대한 활용하여 uncorrelated 신호간의 상관관계를 효과적으로 제거하는 일반화된 공간 차이 기법을 제안한다. 그리고 모의실험을 통해 도래각 추정 정확도와 추정 가능 신호원의 수의 관점에서 성능을 평가하여 제안한 기법의 우수성을 입증한다.

• 한국국방경영분석학회지
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• 제8권1호
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• pp.99-107
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• 1982

This paper is concerned with the optimality of exponential smoothing applied to the general IMA process with different moving average and differencing orders. Numerical experiments were performed for IMA(m,n) process with various combinations of m and n, and the corresponding forecast errors were compared. Results show that the higher differencing order is more critical to the optimality of exponential smoothing, i.e., the IMA process with the higher moving average order, forecasted by exponential smoothing, has comparatively smaller forecast error. If the difference between the differencing order and the moving average order becomes larger, the accuracy of forecast by exponential smoothing declines gradually.