• 제목/요약/키워드: matrix methods

검색결과 2,914건 처리시간 0.027초

Optimization of a Piezoelectric Actuator using Bridge-Type Hinge Mechanism (브릿지형 힌지 메커니즘을 이용한 압전구동기의 최적화)

  • 김준형;김수현;곽윤근
    • Journal of the Korean Society for Precision Engineering
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    • 제20권2호
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    • pp.168-175
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    • 2003
  • In this research, a bridge-type flexure hinge mechanism is developed and optimized to amplify the displacement of a multilayer piezostack. Developed hinge mechanism has three-dimensional structure to reduce link size, so it have high amplification ratio with respect to small size. A flexure hinge is assumed to be 6 degree-of-freedom spring elements and matrix methods are used to model a hinge mechanism. To verify derived matrix model, a displacement and frequency experiments are performed. The analysis result shows that the displacemental error between matrix model and experiments is below 10 percents and the deformation of hinge in parasitic direction should be considered In hinge modeling. Using developed matrix model, an optimal design is performed to maximize the performance of hinge mechanism.

Microstructure Characterization of $SiC_p$-reinforced Aluminum Matrix Composites by Newly Developed Computer-based Algorithms

  • Kretz, Ferenc;Gacsi, Zoltan;Gur, C. Hakan
    • Proceedings of the Korean Powder Metallurgy Institute Conference
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    • 한국분말야금학회 2006년도 Extended Abstracts of 2006 POWDER METALLURGY World Congress Part2
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    • pp.1061-1062
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    • 2006
  • This paper presents a new approach for analyzing the microstructure of $SiC_p$-reinforced aluminum matrix composites from digital images. Various samples of aluminum matrix composite were fabricated by hot pressing the powder mixtures with certain volume and size combinations of pure Al and SiC particles. Microstructures of the samples were analyzed by computer-based image processing methods. Since the conventional methods are not suitable for separating phases of such complex microstructures, some new algorithms have been developed for the improved recognition and characterization of the particles in the metal matrix composites.

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The Stress Analysis of Web Frame by the Transfer Matrix Method (전달(傳達)매트릭스법(法)에 의(依)한 선체특설늑골(船體特設肋骨) 해석(解析))

  • Yim, S.J.;Yang, Y.S.
    • Bulletin of the Society of Naval Architects of Korea
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    • 제12권1호
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    • pp.31-36
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    • 1975
  • As the size of tanker increase, the analysis and strength prediction of the transverse web frames in a tanker have become important problems. Therefore, several papers dicussed the subject and various method of analysis have been presented. Most of these studies are based on the elastic framework analysis. Framework analysis is carried out by the matrix methods. The matrix methods used most frequently are the displacement method, force method and the transfer matrix method. In this paper, the analysis is carried out by the transfer matrix method. The program has been tested by IBM 1130 and the results of example show good agreements with those by the program of stress analysis, STRESS, which was developed in M.I.T.

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Dynamic linear mixed models with ARMA covariance matrix

  • Han, Eun-Jeong;Lee, Keunbaik
    • Communications for Statistical Applications and Methods
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    • 제23권6호
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    • pp.575-585
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    • 2016
  • Longitudinal studies repeatedly measure outcomes over time. Therefore, repeated measurements are serially correlated from same subject (within-subject variation) and there is also variation between subjects (between-subject variation). The serial correlation and the between-subject variation must be taken into account to make proper inference on covariate effects (Diggle et al., 2002). However, estimation of the covariance matrix is challenging because of many parameters and positive definiteness of the matrix. To overcome these limitations, we propose autoregressive moving average Cholesky decomposition (ARMACD) for the linear mixed models. The ARMACD allows a class of flexible, nonstationary, and heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the random effects covariance matrix. We analyze a real dataset to illustrate our proposed methods.

Bayesian baseline-category logit random effects models for longitudinal nominal data

  • Kim, Jiyeong;Lee, Keunbaik
    • Communications for Statistical Applications and Methods
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    • 제27권2호
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    • pp.201-210
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    • 2020
  • Baseline-category logit random effects models have been used to analyze longitudinal nominal data. The models account for subject-specific variations using random effects. However, the random effects covariance matrix in the models needs to explain subject-specific variations as well as serial correlations for nominal outcomes. In order to satisfy them, the covariance matrix must be heterogeneous and high-dimensional. However, it is difficult to estimate the random effects covariance matrix due to its high dimensionality and positive-definiteness. In this paper, we exploit the modified Cholesky decomposition to estimate the high-dimensional heterogeneous random effects covariance matrix. Bayesian methodology is proposed to estimate parameters of interest. The proposed methods are illustrated with real data from the McKinney Homeless Research Project.

Solving a Matrix Polynomial by Conjugate Gradient Methods

  • Ko, Hyun-Ji;Kim, Hyun-Min
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제11권4호
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    • pp.39-46
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    • 2007
  • One of well known and much studied nonlinear matrix equations is the matrix polynomial which has the form G(X)=$A_0X^m+A_1X^{m-1}+{\cdots}+A_m$ where $A_0$, $A_1$, ${\cdots}$, $A_m$ and X are $n{\times}n$ real matrices. We show how the minimization methods can be used to solve the matrix polynomial G(X) and give some numerical experiments. We also compare Polak and Ribi$\acute{e}$re version and Fletcher and Reeves version of conjugate gradient method.

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Matrix Formation in Univariate and Multivariate General Linear Models

  • Arwa A. Alkhalaf
    • International Journal of Computer Science & Network Security
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    • 제24권4호
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    • pp.44-50
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    • 2024
  • This paper offers an overview of matrix formation and calculation techniques within the framework of General Linear Models (GLMs). It takes a sequential approach, beginning with a detailed exploration of matrix formation and calculation methods in regression analysis and univariate analysis of variance (ANOVA). Subsequently, it extends the discussion to cover multivariate analysis of variance (MANOVA). The primary objective of this study was to provide a clear and accessible explanation of the underlying matrices that play a crucial role in GLMs. Through linking, essentially different statistical methods, by fundamental principles and algebraic foundations that underpin the GLM estimation. Insights presented here aim to assist researchers, statisticians, and data analysts in enhancing their understanding of GLMs and their practical implementation in diverse research domains. This paper contributes to a better comprehension of the matrix-based techniques that can be extended to GLMs.

Second-order analysis of planar steel frames considering the effect of spread of plasticity

  • Leu, Liang-Jenq;Tsou, Ching-Huei
    • Structural Engineering and Mechanics
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    • 제11권4호
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    • pp.423-442
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    • 2001
  • This paper presents a method of elastic-plastic analysis for planar steel frames that provides the accuracy of distributed plasticity methods with the computational efficiency that is greater than that of distributed plasticity methods but less than that of plastic-hinge based methods. This method accounts for the effect of spread of plasticity accurately without discretization through the cross-section of a beam-column element, which is achieved by the following procedures. First, nonlinear equations describing the relationships between generalized stresses and strains of the cross-section are derived analytically. Next, nonlinear force-deformation relationships for the beam-column element are obtained through lengthwise integration of the generalized strains. Elastic-plastic flexibility coefficients are then calculated by differentiating the above element force-deformation relationships. Finally, an elastic-plastic stiffness matrix is obtained by making use of the flexibility-stiffness transformation. Adding the conventional geometric stiffness matrix to the elastic-plastic stiffness matrix results in the tangent stiffness matrix, which can readily be used to evaluate the load carrying capacity of steel frames following standard nonlinear analysis procedures. The accuracy of the proposed method is verified by several examples that are sensitive to the effect of spread of plasticity.

A new approach to model reduction using matrix pencil method (Matrix Pencil을 이용한 모델 저차화의 새로운 접근방법)

  • 권혁성;정정주;서병설
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.105-108
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    • 1997
  • This paper proposes a new approach of balanced model reduction using matrix pencil. The algorithm presented in this paper is to convert full-rank high-order system into rank-deficient system using perturbation made by matrix pencil method. Then the system can be truncated to a low-order system that we want via balanced realization. We discuss the comparison with other methods and the various observations by simulations.

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