• Title/Summary/Keyword: dimension matrix

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A Study on the Bending Analysis of Rectangular Plates by Substructuring Technique (분할구조기법을 이용한 장방형판의 휨해석에 관한 연구)

  • 오숙경;김성용;김일중;이용수
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1997.10a
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    • pp.65-72
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    • 1997
  • This study is the bending analysis of rectangular plates with 4-sides simply supported by Finite Element Method using substructuring technique. In finite element method, as the more number of finite element, the more dimension of matrix, it is difficult to obtain accuracy solution. In this paper substructuring technique is applied to finite element method in order to reduce the dimension of matrix according to the number of finite element mesh. To validate finite element method using substructuring technique, deflections and moments of rectangular plates by that method is compared with those of references. Considering the symmetry of the plate and load, one fourth of plate is analyzed. Operating time and the error of solutions according to the number of finite element mesh and substructure are compared with each other.

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Searching for the Steady State of Unstable Link Structures by using Reduced Dimension Technique (차원 저감화기법을 이용한 불안정 링크구조물의 안정경로 탐색)

  • Kim, Jae-Yeol
    • Journal of Korean Association for Spatial Structures
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    • v.4 no.1 s.11
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    • pp.39-48
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    • 2004
  • Generally, a structural system with large inextensional deformations, or in other words, non-strained deformation is called as 'Unstable Structure', Truss-linked structures, cable structures, membrane structures and movable structures as foldable space structures etc, are included in this category. In this paper, a dynamic analysis method for unstable structural systems is presented. Governing equations for dynamic analysis of unstable truss structures with inextensional displacements are derived. Because of singularity of inverse matrixin in practical analysis of unstable structure, the generalized inverse matrix is Introduced to resolve the singular problem. Also, the RREF technique is used to get the inextensional displacement mode. Two unstable truss structures are analyzed by using presented method. Damping is not considered. From the given results, it is known that proposed method is useful to figure out the dynamic behavior of unstable truss structures.

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Comparison of accuracy between LC model and 4-PFM when COVID-19 impacts mortality structure

  • Choi, Janghoon
    • Communications for Statistical Applications and Methods
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    • v.28 no.3
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    • pp.233-250
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    • 2021
  • This paper studies if the accuracies of mortality models (LC model vs. 4-parametric model) are aggravated if a mortality structure changes due to the impact of COVID-19. LC model (LCM) uses dimension reduction for fitting to the log mortality matrix so that the performance of the dimension reduction method may not be good when the matrix structure changes. On the other hand, 4-parametric factor model (4-PFM) is designed to use factors for fitting to log mortality data by age groups so that it would be less affected by the change of the mortality structure. In fact, the forecast accuracies of LCM are better than those of 4-PFM when life-tables are used whereas those of 4-PFM are better when the mortality structure changes. Thus this result shows that 4-PFM is more reliable in performance to the structural changes of the mortality. To support the accuracy changes of LCM the functional aspect is explained by computing eigenvalues produced by singular vector decomposition

Intensive numerical studies of optimal sufficient dimension reduction with singularity

  • Yoo, Jae Keun;Gwak, Da-Hae;Kim, Min-Sun
    • Communications for Statistical Applications and Methods
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    • v.24 no.3
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    • pp.303-315
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    • 2017
  • Yoo (2015, Statistics and Probability Letters, 99, 109-113) derives theoretical results in an optimal sufficient dimension reduction with singular inner-product matrix. The results are promising, but Yoo (2015) only presents one simulation study. So, an evaluation of its practical usefulness is necessary based on numerical studies. This paper studies the asymptotic behaviors of Yoo (2015) through various simulation models and presents a real data example that focuses on ordinary least squares. Intensive numerical studies show that the $x^2$ test by Yoo (2015) outperforms the existing optimal sufficient dimension reduction method. The basis estimation by the former can be theoretically sub-optimal; however, there are no notable differences from that by the latter. This investigation confirms the practical usefulness of Yoo (2015).

Non-linear distributed parameter system estimation using two dimension Haar functions

  • Park Joon-Hoon;Sidhu T.S.
    • Journal of information and communication convergence engineering
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    • v.2 no.3
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    • pp.187-192
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    • 2004
  • A method using two dimension Haar functions approximation for solving the problem of a partial differential equation and estimating the parameters of a non-linear distributed parameter system (DPS) is presented. The applications of orthogonal functions, including Haar functions, and their transforms have been given much attention in system control and communication engineering field since 1970's. The Haar functions set forms a complete set of orthogonal rectangular functions similar in several respects to the Walsh functions. The algorithm adopted in this paper is that of estimating the parameters of non-linear DPS by converting and transforming a partial differential equation into a simple algebraic equation. Two dimension Haar functions approximation method is introduced newly to represent and solve a partial differential equation. The proposed method is supported by numerical examples for demonstration the fast, convenient capabilities of the method.

Multi-Step Reheating Process of Metal Matrix Composites for Thixoforming (Thixoforming을 위한 금속 복합재료의 다단 재가열 공정)

  • 허재찬;강충길
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.10a
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    • pp.180-183
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    • 1997
  • The forming process of metal matrix composites by the die casting and squeeze casting process are limited in size and dimension in term of final parts without machining. The thixoforming process for metal matrix composites has numerous advantages compared to die casting, squeeze casting and compocasting. The characteristics of thixoforming process can decrease the liquid segregation because of he improvement in fluidity in a globular microstructure state and utilizes flow without air entrapment. Therefore, in order to obtain the sound parts of metal matrix composites by using thixoforming process which as co-existing solidus-liquidus pahse, it si very important to obtain reheating condition. However, for he thixoforming process, the billet with the desired volume fraction must be heated to obtain a uniform temperature distribution over the entire cross-sectional areas. To obtain the reheating conditions of composites, the particulate reinforced metal matrix composites for thixoforming were fabricated by combined stirring process which is simultaneously performed with electro-magnetic stirring process which is simultaneously performed with electro-magnetic stirring and mechanical stirring process.

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Global Covariance based Principal Component Analysis for Speaker Identification (화자식별을 위한 전역 공분산에 기반한 주성분분석)

  • Seo, Chang-Woo;Lim, Young-Hwan
    • Phonetics and Speech Sciences
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    • v.1 no.1
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    • pp.69-73
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    • 2009
  • This paper proposes an efficient global covariance-based principal component analysis (GCPCA) for speaker identification. Principal component analysis (PCA) is a feature extraction method which reduces the dimension of the feature vectors and the correlation among the feature vectors by projecting the original feature space into a small subspace through a transformation. However, it requires a larger amount of training data when performing PCA to find the eigenvalue and eigenvector matrix using the full covariance matrix by each speaker. The proposed method first calculates the global covariance matrix using training data of all speakers. It then finds the eigenvalue matrix and the corresponding eigenvector matrix from the global covariance matrix. Compared to conventional PCA and Gaussian mixture model (GMM) methods, the proposed method shows better performance while requiring less storage space and complexity in speaker identification.

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DECOUPLING OF MULTI-INPUT MULTI-OUTPYT TWO DIMENSIONAL SYSTEMS

  • Kawakami, Atsushi
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.1130-1134
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    • 1990
  • In this paper, we propose a mthod to decouple the multi-input multi-output two-dimensional system. Then, we analyze the realization dimension of the feedback, feedforward given to decouple. Moreover, we consider the possibility of the reduction of the dynamical dimension needed to decouple. Besides, in order to stabilize the decoupled two-dimensional system, we suggest a method to assign the poles of each entry of the transfer function matrix to the desired positions.

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C32-CONSTRUCTION ON Mn(κ)

  • Song, Youngkwon
    • Korean Journal of Mathematics
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    • v.12 no.1
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    • pp.23-32
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    • 2004
  • Let (B, $m_B$, ${\kappa}$) be a maximal commutative ${\kappa}$-subalgebra of a matrix algebra $M_n(\kappa)$. We will construct a maximal commutative ${\kappa}$-subalgebra (R, $m$, ${\kappa}$) of $M_n+3(\kappa)$ from the algebra B such that the algebra R has dimension greater than the dimension of B by 3. Moreover, we will show a $C_i$-construction doesn't imply a $C^3_2$-construction for $i=1,2$.

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Parallel solution of linear systems on the CRAY-2 using multi/micro tasking library (CRAY-2에서 멀티/마이크로 태스킹 라이브러리를 이용한 선형시스템의 병렬해법)

  • Ma, Sang-Back
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.11
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    • pp.2711-2720
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    • 1997
  • Multitasking and microtasking on the CRAY machine provides still another way to improve computational power. Since CRAY-2 has 4 processors we can achieve speedup up to 4 properly designed algorithms. In this paper we present two parallelizations of linear system solution in the CRAY-2 with multitasking and microtasking library. One is the LU decomposition on the dense matrices and the other is the iterative solution of large sparse linear systems with the preconditioner proposed by Radicati di Brozolo. In the first case we realized a speedup of 1.3 with 2 processors for a matrix of dimension 600 with the multitasking and in the second case a speedup of around 3 with 4 processors for a matrix of dimension 600 with the multitasking and in the second case a speedup of around 3 with 4 processors for a matrix of dimension 8192 with the microtasking. In the first case the speedup is limited because of the nonuniform vector lenghts. In the second case the ILU(0) preconditioner with Radicati's technique seem to realize a reasonable high speedup with 4 processors.

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