• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4411-4417
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• 2012

The present study proposes the optimization of wing structure base on reduced model which assures the solution accuracy and computational efficiency. Well-constructed reduced model assures the accurate result in the eigenvalue problem, dynamic analysis or sensitivity of design optimization. Reduced system is classified into the reduce-order model based on structural modes and the reduced system based on degrees of freedom. Because this study uses the reduced system based on degrees of freedom, it is important to select the dominant degrees of freedom properly. For this work, robust selection method, two-level selection scheme, is employed and IRS(Improved Reduced System) is applied to construct the final reduced system. In the optimization process based on the reduced system, all of the equivalent stress, eigenvalue and design sensitivities are calculated from the reduced system. Through a numerical example, it is shown that the present optimization methodology based on the reduction method can provide an optimal results for objective function satisfying constraint condition.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.453-458
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• 2004

This study proposes a new two-level condensation scheme for the construction of a reduced system. In the first step, the candidate area is selected for the construction of the reduced system by energy estimation in element-level. In the second step, primary degrees of freedom are selected by sequential elimination from the candidate degrees of freedom linked to the selected elements. Numerical examples demonstrate that the proposed method saves the computational cost effectively and provides a reduced system which predicts the eigenvalues accurately. Moreover, the well-constructed reduced system can present the reliable behavior of the structure under arbitrary dynamic loads comparing to that of global system. Time integration in a reduced system can save the computing time remarkably. Through a few numerical examples, the efficiency and reliability of the proposed scheme are verified.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.1-1
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• 2003

In this talk, a reduced-order modeling methodology based on centroidal Voronoi tessellations (CVT's)is introduced. CVT's are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi cells. The discrete data sets, CVT's are closely related to the h-means clustering techniques. Even with the use of good mesh generators, discretization schemes, and solution algorithms, the computational simulation of complex, turbulent, or chaotic systems still remains a formidable endeavor. For example, typical finite element codes may require many thousands of degrees of freedom for the accurate simulation of fluid flows. The situation is even worse for optimization problems for which multiple solutions of the complex state system are usually required or in feedback control problems for which real-time solutions of the complex state system are needed. There hava been many studies devoted to the development, testing, and use of reduced-order models for complex systems such as unsteady fluid flows. The types of reduced-ordered models that we study are those attempt to determine accurate approximate solutions of a complex system using very few degrees of freedom. To do so, such models have to use basis functions that are in some way intimately connected to the problem being approximated. Once a very low-dimensional reduced basis has been determined, one can employ it to solve the complex system by applying, e.g., a Galerkin method. In general, reduced bases are globally supported so that the discrete systems are dense; however, if the reduced basis is of very low dimension, one does not care about the lack of sparsity in the discrete system. A discussion of reduced-ordering modeling for complex systems such as fluid flows is given to provide a context for the application of reduced-order bases. Then, detailed descriptions of CVT-based reduced-order bases and how they can be constructed of complex systems are given. Subsequently, some concrete incompressible flow examples are used to illustrate the construction and use of CVT-based reduced-order bases. The CVT-based reduced-order modeling methodology is shown to be effective for these examples and is also shown to be inexpensive to apply compared to other reduced-order methods.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.5
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• pp.439-450
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• 2008

In this study, the reduced system for the dynamic analysis is proposed and the selection criterion of the primary degrees of freedom is presented considering the relation between natural frequency and external loading frequency. A well-constructed reduced system can assure the accurate representation of the dynamic behavior under arbitrary dynamic loads. For selecting the primary degrees of freedom of the reduced system, we employ the robust two-level condensation scheme of which the reliability has been proven through previous study. In the numerical examples, the reliability of the dynamic analysis based on the reduced system is demonstrated through comparing with those of global system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.9 s.252
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• pp.1070-1077
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• 2006

In the present study, sizing and shape optimizations are performed based on the reduced system of large-scaled problem. In the analysis part to achieve efficiency and reliability of computation, two-level condensation scheme is applied. In the construction of reduced system of large scaled problems, it is much more efficient to use sub-domain method. Thus, in the present paper, two-level reduction method combined with sub-domain method is employed. Once the reduced system is constructed, it is straightforward to obtain design sensitivities from the analysis results of the reduced system We use semi-analytic method to obtain design sensitivities. Performance of the efficiency and reliability of the present reduction method in the structural optimization problem is demonstrated through the numerical examples. The present framework of reduction method should serve as a fast and reliable design tool in analysis and design of large-scaled dynamic problems.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.50-59
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• 1997

This paper is on the generalized singular perturbation approximation (GSPA) preserving the discrete positive real property. We transform the discrete positive real(PR) system into a stochastically banlanced system and get the reduced order discrete system from the GSPA of the full order stochastically balanced system. eSPECIALLY, WHEN THE FREE PARAMETER OF THE gspa IS .+-.1, we show that the reduced order discrete system retains stability, minimality, and positive real and stochstically balancing properties. And we derived the .inf.-norm error bound with the reduced order discrete strictly positive real(SPR) system by the proposed method. Finally, we give an example to ascertain the properties of the proposed reduced order discrete system and to compare with the conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.9
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• pp.630-637
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• 2004

In this paper, we present a local reduced-order observer for a class of nonlinear systems that have full robust relative degree. The proposed observer utilizes the coordinate change which transforms a nonlinear system into an approximate normal form. The proposed reduce order observer is applied to a ball and beam system, and simulation results show that substantial improvement in the performance was achieved compared with the jacobian linearization observers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.9 s.252
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• pp.1062-1069
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• 2006

Reduction schemes approximate the lower eigenvalues that represent the global behavior of the structures. But, they are not efficient to be applied to large-scaled problems because these schemes require considerable amount of computing time in constructing reduced one from the original large-scaled systems. In addition, the selection of the primary degrees of freedom might be localized to cause the excessive emphasis of the lower mode or lost of the important modes. In the present study, a new reduction method combined with the subdomain method is proposed. For the construction of the final reduced system the system of each domain subdivided into primary, slave and interface degrees of freedom. It is remarkably efficient and accurate comparable to full-scale system. Numerical examples demonstrate that the proposed method saves computational cost effectively and provides a reduced system which predicts accurate eigen-pairs of global system.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.631-636
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• 2007

Eigenvalue reduction schemes approximate the lower eigenmodes that represent the global behavior of the structures. In the, we proposed a two-level condensation scheme(TLCS) for the construction of a reduced system. In first step, the of candidate elements by energy estimation, Rayleigh quotient, through Ritz vector calculation, and next, the primary degrees of freedom is selected by sequential elimination from the degrees of freedom connected the candidate elements in the first step. In the present study, we propose TLCS combined with iterative improved reduced system(IIRS) to increase accuracy of higher modes intermediate range. Also, it possible to control the accuracy of the eigenvalues and eigenmodes of the reduced system. Numerical examples demonstrate performance of proposed method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.19-26
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• 2004

This study constructs the reduced system by two-level condensation scheme. This scheme consists of two steps. First step selects the candidate area for the primary degrees of freedom by energy estimation in element level. In the second step, the primary degrees of freedom are selected by the sequential elimination scheme. The efficiency and reliability of this scheme is shown through the prediction of eigenvalues of a few numerical examples. Time integration in the reduced system can save the computing time effectively. The well-constructed reduced system can present the accurate behavior of the structure under arbitrary dynamic loads so much as the global system. Through the numerical example, the efficiency and reliability of the proposed scheme will be demonstrated.