• International Journal of Aeronautical and Space Sciences
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• 제8권2호
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• pp.67-75
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• 2007

An attitude control problem for a tethered spacecraft is studied. The tethered spacecraft is viewed as a multi-body spacecraft consisting of a base body, a massless tether that connects the base body and an end mass, and tether actuator dynamics. Moments about the pitch and roll axes of the base spacecraft arise by control of the point of attachment of the tether to the base spacecraft. The control objective is to stabilize the attitude of the base spacecraft while keeping the perturbations of the tether small. Analysis shows that linear equations of motion for the tethered spacecraft are not completely controllable. We study two different control design approaches: (1) we decouple the attitude dynamics from the tether dynamics and we design a linear feedback to achieve stabilization of the attitude dynamics, and (2) we decouple the controllable modes from the uncontrollable mode using Kalman decomposition and we design a linear feedback to achieve stabilization of the controllable modes. Simulation results show that, although it is difficult to control the tether, the tether motion can be maintained within an acceptable range while stabilizing the attitude dynamics of the base spacecraft.

• 대기
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• 제21권2호
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• pp.143-149
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• 2011

A new multi-timescale analysis method, Ensemble Empirical Mode Decomposition (EEMD), is used to diagnose the variation of the MJO activity determined by 850hPa and 200hPa zonal winds from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data for the 56-yr period from 1950 to 2005. The results show that MJO activity can be decomposed into 9 quasi-periodic oscillations and a trend. With each level of contribution of the quasi-periodic oscillation discussed, the bi-seasonal oscillation, the interannual oscillation and the trend of the MJO activity are the most prominent features. The trend increases almost linearly, so that prior to around 1978 the activity of the MJO is lower than that during the latter part. This may be related to the tropical sea surface temperature(SST). It is speculated that the interdecadal change in the MJO activity appeared in around 1978 is related to the warmer SST in the equatorial warm pool, especially over the Indian Ocean.

• 한국통신학회논문지
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• 제31권6C호
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• pp.589-602
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• 2006

잡음은 음성과 관련된 시스템의 성능을 제한하는 주된 원인이기 때문에 음성향상과 관련된 연구는 꾸준히 계속되어왔다. 전통적인 음성향상 방법은 무성음과 잡음을 구분하지 알기 때문에 잡음제거 과정에서 무성음이 함께 제거되는 단점이 있으며, 웨이블릿 기반의 전통적인 잡음제거 방법은 각 대역마다 동일한 문턱값을 사용하기 때문에 시변 환경에서 성능이 떨어지는 단점이 있다. 이 단점들을 개선하기위해 다중대역 파워 차감법과 Perceptual 웨이블릿 패킷 분해를 이용한 웨이블릿 기반의 개선된 음성향상 방법을 제안한다. 전처리 과정으로 다중대역 파워 차감법을 사용하여 광대역 잡음을 제거하고 뮤지컬 잡음의 발생을 줄이며, psycho-acoustic 모델 기반 Perceptual 웨이블릿 패킷으로 신호를 분해한 후 각 웨이블릿 노드의 엔트로피 비율과 음성검출을 이용하여 무성음/유성음/잡음을 구분한다. 구분된 신호에 따라 각 웨이블릿 노드마다의 문턱값을 기준으로 웨이블릿 Shrinkage를 적용하여 잡음을 제거하고 무성음이나 파워가 작은 유성음이 제거되는 오류를 최소화한다. 또한 잡음 파워 추정 과정에 적응적으로 망각 계수를 선택하여 잡음 파워 추정 오류를 최소화한다.

• Nuclear Engineering and Technology
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• 제46권5호
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• pp.655-666
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• 2014

The CUPID code has been developed at KAERI for a transient, three-dimensional analysis of a two-phase flow in light water nuclear reactor components. It can provide both a component-scale and a CFD-scale simulation by using a porous media or an open media model for a two-phase flow. In this paper, recent advances in the CUPID code are presented in three sections. First, the domain decomposition parallel method implemented in the CUPID code is described with the parallel efficiency test for multiple processors. Then, the coupling of CUPID-MARS via heat structure is introduced, where CUPID has been coupled with a system-scale thermal-hydraulics code, MARS, through the heat structure. The coupled code has been applied to a multi-scale thermal-hydraulic analysis of a pool mixing test. Finally, CUPID-SG is developed for analyzing two-phase flows in PWR steam generators. Physical models and validation results of CUPID-SG are discussed.

• 한국전산구조공학회논문집
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• 제23권5호
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• pp.475-482
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• 2010

본 논문에서는 대규모 자유도 시스템의 병렬처리를 위하여 2단계로 이루어진 영역분할법(Domain Decomposition Method) 기반의 병렬 알고리즘을 제안하였다. 분할된 영역의 내부 및 외부 경계를 상위영역문제로 정의하고 국부영역문제는 변위 경계조건이 모두 주어지는 분할영역에서의 Dirichlet 문제로 구성한다. 상위영역에서는 전체 상위영역에 대한 강성 행렬의 어셈블이 필요없는 반복법을 통하여 변위를 구하고, 이를 바탕으로 국부영역에서 Multi-Frontal Sparse Solver (MFSS)를 이용하여 변위를 계산한다. 상위영역문제의 연산에서 프로세서 간의 데이터 교환을 최소화하여 계산효율을 유지하며, 동시에 해석 가능한 자유도를 증대시키는 병렬 PCG(Preconditioned Conjugate Gradient)법 기반의 알고리즘을 개발하였다. 제안된 알고리즘을 적용하여 수치해석을 수행한 결과, 프로세서 수가 증가할수록 계산성능의 손실없이 해석 가능한 자유도가 비례하여 증가하는 선형 확장성을 관찰할 수 있었으며, 대규모 자유도 문제에 효과적으로 사용 가능함을 확인하였다.

• 한국항공우주학회지
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• 제37권11호
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• pp.1073-1079
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• 2009

본 연구에서는 전진 비행하는 헬리콥터 로터 블레이드 표면의 압력장에 대한 공력 특성 분석 및 차수축소모델 구축을 위해 적합직교분해 (POD) 방법을 이용하였다. 에너지가 큰 특정 모드를 기반으로 전진 비행하는 비정상 로터 블레이드에 대한 공기역학적 특성을 분석하였으며, CFD 계산 결과의 검증을 위해 제자리비행에 대한 실험 결과와 비교하였다. 수렴속도를 향상시키기 위해 Multi-grid 기법을 사용하였으며, 회전하는 로터 블레이드 주위의 비정상 유동을 모사하기 위해 슬라이딩 격자를 이용하였다. 그 결과 240개의 Snapshot에 대해 에너지율 99% 이상을 포함하는 지배적인 POD 모드 7개가 선정되었으며, POD 모드와 전개 계수를 이용하여 차수축소모델을 성공적으로 구축하였다.

• Smart Structures and Systems
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• 제13권2호
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• pp.257-280
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• 2014

In this paper, a novel PARAllel FACtor (PARAFAC) decomposition based Blind Source Separation (BSS) algorithm is proposed for modal identification of structures equipped with tuned mass dampers. Tuned mass dampers (TMDs) are extremely effective vibration absorbers in tall flexible structures, but prone to get de-tuned due to accidental changes in structural properties, alteration in operating conditions, and incorrect design forecasts. Presence of closely spaced modes in structures coupled with TMDs renders output-only modal identification difficult. Over the last decade, second-order BSS algorithms have shown significant promise in the area of ambient modal identification. These methods employ joint diagonalization of covariance matrices of measurements to estimate the mixing matrix (mode shape coefficients) and sources (modal responses). Recently, PARAFAC BSS model has evolved as a powerful multi-linear algebra tool for decomposing an $n^{th}$ order tensor into a number of rank-1 tensors. This method is utilized in the context of modal identification in the present study. Covariance matrices of measurements at several lags are used to form a $3^{rd}$ order tensor and then PARAFAC decomposition is employed to obtain the desired number of components, comprising of modal responses and the mixing matrix. The strong uniqueness properties of PARAFAC models enable direct source separation with fine spectral resolution even in cases where the number of sensor observations is less compared to the number of target modes, i.e., the underdetermined case. This capability is exploited to separate closely spaced modes of the TMDs using partial measurements, and subsequently to estimate modal parameters. The proposed method is validated using extensive numerical studies comprising of multi-degree-of-freedom simulation models equipped with TMDs, as well as with an experimental set-up.

• Smart Structures and Systems
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• 제30권1호
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• pp.75-88
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• 2022

Engineering structures in operation essentially belong to time-varying or nonlinear structures and the resultant response signals are usually non-stationary. For such time-varying structures, it is of great importance to extract time-dependent dynamic parameters from non-stationary response signals, which benefits structural health monitoring, safety assessment and vibration control. However, various traditional signal processing methods are unable to extract the embedded meaningful information. As a newly developed technique, variational mode decomposition (VMD) shows its superiority on signal decomposition, however, it still suffers two main problems. The foremost problem is that the number of modal components is required to be defined in advance. Another problem needs to be addressed is that VMD cannot effectively separate non-stationary signals composed of closely spaced or overlapped modes. As such, a new method named generalized adaptive variational modal decomposition (GAVMD) is proposed. In this new method, the number of component signals is adaptively estimated by an index of mean frequency, while the generalized demodulation algorithm is introduced to yield a generalized VMD that can decompose mode overlapped signals successfully. After that, synchrosqueezing wavelet transform (SWT) is applied to extract instantaneous frequencies (IFs) of the decomposed mono-component signals. To verify the validity and accuracy of the proposed method, three numerical examples and a steel cable with time-varying tension force are investigated. The results demonstrate that the proposed GAVMD method can decompose the multi-component signal with overlapped modes well and its combination with SWT enables a successful IF extraction of each individual component.

• 품질경영학회지
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• 제50권4호
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• pp.701-716
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• 2022

Purpose: This study aims to predict the dry cargo transportation market economy. The subject of this study is the BDI (Baltic Dry Index) time-series, an index representing the dry cargo transport market. Methods: In order to increase the accuracy of the BDI time-series, we have pre-processed the original time-series via time-series decomposition and data augmentation techniques and have used them for ANN learning. The ANN algorithms used are Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) to compare and analyze the case of learning and predicting by applying time-series decomposition and data augmentation techniques. The forecast period aims to make short-term predictions at the time of t+1. The period to be studied is from '22. 01. 07 to '22. 08. 26. Results: Only for the case of the MAPE (Mean Absolute Percentage Error) indicator, all ANN models used in the research has resulted in higher accuracy (1.422% on average) in multivariate prediction. Although it is not a remarkable improvement in prediction accuracy compared to uni-variate prediction results, it can be said that the improvement in ANN prediction performance has been achieved by utilizing time-series decomposition and data augmentation techniques that were significant and targeted throughout this study. Conclusion: Nevertheless, due to the nature of ANN, additional performance improvements can be expected according to the adjustment of the hyper-parameter. Therefore, it is necessary to try various applications of multiple learning algorithms and ANN optimization techniques. Such an approach would help solve problems with a small number of available data, such as the rapidly changing business environment or the current shipping market.

• 한국인터넷방송통신학회논문지
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• 제13권3호
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• pp.165-170
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• 2013

공간상에서 원하는 목표물의 도래 방향 추정은 수신 안테나에 입사하는 신호의 입사 방향을 찾는 것이다. 본 논문에서는 최대 우도 추정 방법을 이용하여 원하는 목표물의 도래 방향을 추정하였다. 도래 방향 추정방법은 최대 우도 방법에서 수신 신호 한계점 이상의 신호에 특이 값 분해를 적용하여 최대 우도 추정의 첨예도를 계산하여 원하는 목표물을 추정하였다. 모의실험을 통하여 본 연구에서 제안된 방법의 성능을 기존 방법과 비교분석하였다. 목표물 도래방향 추정에서 본 연구에서 제안한 방법이 고유치 전개를 하지 않기 때문에 처리시간 단축에서 효과적이고 원하는 목표물의 방향을 정확히 추정하였다. 본 연구에서 제안한 방법이 목표물 추정에서 기존 방법보다 우수함을 나타내었다.