• 제목/요약/키워드: structure decomposition analysis

검색결과 311건 처리시간 0.03초

A Study of Singular Value Decomposition in Data Reduction techniques

  • Shin, Yang-Kyu
    • Journal of the Korean Data and Information Science Society
    • /
    • 제9권1호
    • /
    • pp.63-70
    • /
    • 1998
  • The singular value decomposition is a tool which is used to find a linear structure of reduced dimension and to give interpretation of the lower dimensional structure about multivariate data. In this paper the singular value decomposition is reviewed from both algebraic and geometric point of view and, is illustrated the way which the tool is used in the multivariate techniques finding a simpler geometric structure for the data.

  • PDF

The Comparison of Singular Value Decomposition and Spectral Decomposition

  • Shin, Yang-Gyu
    • Journal of the Korean Data and Information Science Society
    • /
    • 제18권4호
    • /
    • pp.1135-1143
    • /
    • 2007
  • The singular value decomposition and the spectral decomposition are the useful methods in the area of matrix computation for multivariate techniques such as principal component analysis and multidimensional scaling. These techniques aim to find a simpler geometric structure for the data points. The singular value decomposition and the spectral decomposition are the methods being used in these techniques for this purpose. In this paper, the singular value decomposition and the spectral decomposition are compared.

  • PDF

Proper Orthogonal Decomposition 기법을 이용한 세장한 구조물의 모드인자 파악 (Modal Identification of a Slender Structure using the Proper Orthogonal Decomposition Method)

  • 함희정
    • 산업기술연구
    • /
    • 제28권B호
    • /
    • pp.135-141
    • /
    • 2008
  • In this paper, the Proper Orthogonal Decomposition (POD) method, which is a statistical analysis technique to find the modal characteristics of a structure, is adapted to identify the modal parameters of a tall chimney structure. A wind force time history, which is applied to the structure, is obtained by a wind tunnel test of a scale down model. The POD method is applied on the wind force induced responses of the structure, and the true normal modes of the structure can be obtained. The modal parameters including, natural frequency, mode shape, damping ratio and kinetic energy of the structure can be estimated accurately. With these results, it may be concluded that the POD method can be applied to obtain accurate modal parameters from the wind-induced building responses.

  • PDF

Review of Data-Driven Multivariate and Multiscale Methods

  • Park, Cheolsoo
    • IEIE Transactions on Smart Processing and Computing
    • /
    • 제4권2호
    • /
    • pp.89-96
    • /
    • 2015
  • In this paper, time-frequency analysis algorithms, empirical mode decomposition and local mean decomposition, are reviewed and their applications to nonlinear and nonstationary real-world data are discussed. In addition, their generic extensions to complex domain are addressed for the analysis of multichannel data. Simulations of these algorithms on synthetic data illustrate the fundamental structure of the algorithms and how they are designed for the analysis of nonlinear and nonstationary data. Applications of the complex version of the algorithms to the synthetic data also demonstrate the benefit of the algorithms for the accurate frequency decomposition of multichannel data.

효율적 분산협동설계를 위한 분해 기반 병렬화 기법의 개발 (Decomposition Based Parallel Processing Technique for Efficient Collaborative Optimization)

  • 박형욱;김성찬;김민수;최동훈
    • 대한기계학회:학술대회논문집
    • /
    • 대한기계학회 2000년도 추계학술대회논문집A
    • /
    • pp.818-823
    • /
    • 2000
  • In practical design studies, most of designers solve multidisciplinary problems with complex design structure. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder original design processes to minimize total cost and time. This is accomplished by decomposing large multidisciplinary problem into several multidisciplinary analysis subsystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and multidisciplinary design optimization (MDO) methodology.

  • PDF

영역분할법을 이용한 2차원 유한차분 시간영역법 해석 (2D Finite Difference Time Domain Method Using the Domain Decomposition Method)

  • 홍익표
    • 한국정보통신학회논문지
    • /
    • 제17권5호
    • /
    • pp.1049-1054
    • /
    • 2013
  • 본 논문에서는 영역분할법을 이용한 2차원 유한차분시간영역법을 제안하였다. 영역분할법은 전체 해석구조를 분할하여 해석하는 수치해석방법으로 본 논문에서는 영역분할법 중 Schur complement 방법을 적용한 유한차분 시간영역법을 구현하고 시뮬레이션 모델로 2차원 해석구조를 설정하고 사각형의 도체에 입사하는 전자파의 산란특성을 해석하였다. 2차원 해석구조를 4개의 영역과 8개의 영역으로 각각 나누어 전자파특성을 계산하였고, 제안한 해석방법의 유효함을 입증하기 위해 일반적인 전체영역에 대한 2차원 유한차분 시간영역법의 해석결과와 비교하여 잘 일치하는 것을 확인하였다.

Adaptive Parallel Decomposition for Multidisciplinary Design

  • Park, Hyung-Wook;Lee, Se J.;Lee, Hyun-Seop;Park, Dong-Hoon
    • Journal of Mechanical Science and Technology
    • /
    • 제18권5호
    • /
    • pp.814-819
    • /
    • 2004
  • The conceptual design of a rotorcraft system involves many different analysis disciplines. The decomposition of such a system into several subsystems can make analysis and design more efficient in terms of the total computation time. Adaptive parallel decomposition makes the structure of the overall design problem suitable to apply the multidisciplinary design optimization methodologies and it can exploit parallel computing. This study proposes a decomposition method which adaptively determines the number and sequence of analyses in each sub-problem corresponding to the available number of processors in parallel. A rotorcraft design problem is solved and as a result, the adaptive parallel decomposition method shows better performance than other previous methods for the selected design problem.

Partitioned analysis of nonlinear soil-structure interaction using iterative coupling

  • Jahromi, H. Zolghadr;Izzuddin, B.A.;Zdravkovic, L.
    • Interaction and multiscale mechanics
    • /
    • 제1권1호
    • /
    • pp.33-51
    • /
    • 2008
  • This paper investigates the modelling of coupled soil-structure interaction problems by domain decomposition techniques. It is assumed that the soil-structure system is physically partitioned into soil and structure subdomains, which are independently modelled. Coupling of the separately modelled partitioned subdomains is undertaken with various algorithms based on the sequential iterative Dirichlet-Neumann sub-structuring method, which ensures compatibility and equilibrium at the interface boundaries of the subdomains. A number of mathematical and computational characteristics of the coupling algorithms, including the convergence conditions and choice of algorithmic parameters leading to enhanced convergence of the iterative method, are discussed. Based on the presented coupling algorithms a simulation environment, utilizing discipline-oriented solvers for nonlinear structural and geotechnical analysis, is developed which is used here to demonstrate the performance characteristics and benefits of various algorithms. Finally, the developed tool is used in a case study involving nonlinear soil-structure interaction analysis between a plane frame and soil subjected to ground excavation. This study highlights the relative performance of the various considered coupling algorithms in modelling real soil-structure interaction problems, in which nonlinearity arises in both the structure and the soil, and leads to important conclusions regarding their adequacy for such problems as well as the prospects for further enhancements.

Speech Denoising via Low-Rank and Sparse Matrix Decomposition

  • Huang, Jianjun;Zhang, Xiongwei;Zhang, Yafei;Zou, Xia;Zeng, Li
    • ETRI Journal
    • /
    • 제36권1호
    • /
    • pp.167-170
    • /
    • 2014
  • In this letter, we propose an unsupervised framework for speech noise reduction based on the recent development of low-rank and sparse matrix decomposition. The proposed framework directly separates the speech signal from noisy speech by decomposing the noisy speech spectrogram into three submatrices: the noise structure matrix, the clean speech structure matrix, and the residual noise matrix. Evaluations on the Noisex-92 dataset show that the proposed method achieves a signal-to-distortion ratio approximately 2.48 dB and 3.23 dB higher than that of the robust principal component analysis method and the non-negative matrix factorization method, respectively, when the input SNR is -5 dB.

국내 제조업부문에 대한 에너지소비 요인 분해 분석 (Decomposition Analysis on Energy Consumption of Manufacturing Industry)

  • 김수이
    • 자원ㆍ환경경제연구
    • /
    • 제31권4호
    • /
    • pp.825-848
    • /
    • 2022
  • 이 논문은 국내 제조업부문의 에너지소비 증가 요인을 LMDI(Log mean divisia index) 분해 분석방법을 이용하여 분석하였다. 1999년부터 2019년까지 20년간의 에너지소비 변화를 분석하였다. LMDI 분해 분석방법 중 에너지소비 증가량을 분석한 가법적 요인분해 분석과 에너지소비 증가율을 분석한 승법적 요인분해 분석 모두를 사용하였다. 분석결과, 국내 제조업의 에너지소비를 증가시킨 요인은 생산효과이며, 구조효과와 집약도 효과는 에너지소비를 감소시키는 요인으로 나타났다. 특히 구조효과에 의한 에너지소비 감소가 집약도 효과에 의한 에너지소비 효과보다 더 크게 나타났다. 시기별로 보면, 2011년까지는 에너지소비가 생산효과에 의해 급속히 증가한 반면 그 이후에는 생산효과에 의한 에너지소비 증가가 둔화된 것을 알 수 있다. 이에 반해 그 이후에는 구조효과와 집약도효과에 의한 에너지 감소효과가 두드러지고 있는데 이는 2011년부터 실시된 온실가스·에너지목표관리제와 2015년 이후 실시된 배출권거래제의 효과가 나타난 결과로 보인다. 향후 제조업부문의 에너지절약을 위해서는 EMS(Energy management system), FEMS(Factory energy management system) 등을 통한 에너지진단과 관리가 더욱 필요해 보인다. 아울러 에너지저소비형 산업으로의 구조조정도 더 필요해 보인다.