• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.4
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• pp.661-674
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• 2002

The objective of this study is to develop efficient numerical method to enable solution of optimal control problems of Navier-Stokes flows and to apply these technique to the problem of viscous drag minimization on a bluff body by controlling boundary velocities on the surface of the body. In addition to the industrial importance of the drag reduction problem, it serves as a model for other more complex flow optimization settings, and allows us to study, modify, and improve the behavior of the optimal control methods proposed here. The control is affected by the suction or injection of fluid on portions of the boundary, and the objective function represents the rate at which energy is dissipated in the fluid. This study shows how reduced Hessian successive quadratic programming method, which avoid converging the flow equations at each iteration, can be tailored to these problems.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.3
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• pp.195-202
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• 2012

Two nonlinear frame elements taking into account geometric nonlinearity is presented and compared based on the Lagrangian co-rotational formulation. The first frame element is believed to be geometrically-exact because not only tangent stiffness matrices is exactly evaluated including stiffness matrices due to initial deformation but also total member forces are directly determined from total deformations in the deformed state. Particularly two exact tangent stiffness matrices based on total Lagrangian and updated Lagrangian formulation, respectively, are verified to be identical. In the second frame element, the deformed curved shape is regarded as the polygon and current flexural deformations in iteration process are neglected in evaluating tangent stiffness matrices and total member forces. Two numerical examples are given to demonstrate the accuracy and the good performance of the first frame element compared with the second element. Furthermore it is shown that the first frame element can be used in tracing nonlinear behaviors of cable members.

• Magazine of the Korean Society of Agricultural Engineers
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• v.29 no.4
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• pp.73-92
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• 1987

Formulation of the geometric optimization for truss structures based on the elasticity theory turn out to be the nonlinear programming problem which has to deal with the cross-sectional area of the member and the coordinates of its nodes simultaneously. A few techniques have been proposed and adopted for the analysis of this nonlinear programming problem for the time being. These techniques, however, bear some limitations on truss shapes, loading conditions and design criteria for the practical application to real structures. A generalized algorithm for the geometric optimization of the truss structures, which can eliminate the above mentioned limitations, is developed in this study. The algorithm proposed utilizes the two-levels technique. In the first level which consists of two phases, the cross-sectional area of the truss member is optimized by transforming the nonlinear problem into SUMT, and solving SUMT utilizing the modified Newton Raphson method. In the second level, which also consists of two phases the geometric shape is optimized utillzing the unindirectional search technique of the Powell method which make it possible to minimize only the objective functlon. The algorithm proposed in this study is numerically tested for several truss structures with various shapes, loading conditions and design criteria, and compared with the results of the other algorithms to examine its applicability and stability. The numerical comparisons show that the two- levels algorithm proposed in this study is safely applicable to any design criteria, and the convergency rate is relatively fast and stable compared with other iteration methods for the geometric optimization of truss structures. It was found for the result of the shape optimization in this study to be decreased greatly in the weight of truss structures in comparison with the shape optimization of the truss utilizing the algorithm proposed with the other area optimum method.

• Geophysics and Geophysical Exploration
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• v.5 no.1
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• pp.33-45
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• 2002

It was necessary to devise new techniques to overcome and enhance the resolution limits of traveltime tomography. Waveform inversion has been one of the methods for giving very high resolution result. High resolution image could be acquired because waveform inversion used not only phase but amplitude. But waveform inversion was much time consuming Job because forward and backward modeling was needed at each iteration step. Velocity-stress method was used for effective modeling. Resolution limits of imaging methods such as travel time inversion, acoustic and elastic waveform inversion were investigated with numerical models. it was investigated that Resolution limit of waveform inversion was similar tn resolution limit of migration derived by Schuster. Horizontal resolution limit could be improved with increased coverage by adding VSP data in cross hole that had insufficient coverage. Also, waveform inversion was applied to realistic models to evaluate applicability and using initial guess of travel time tomograms to reduce non-linearity of waveform inversion showed that the better reconstructed image could be acquired.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.1-8
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• 2007

In this paper, research on joint optimization of the image spatial registration and the exposure compensation is conducted. The exposure compensation is performed in a frame work of the intensity compensation based on the polynomial approximation of the relationship between images. This compensation is jointly combined with the registration problem employing the Gauss-Newton nonlinear optimization method. In this paper, to perform for a simple and stable optimization, the block-coordinate method is combined with the Gauss-Newton optimization and extensively compared with the traditional approaches. Furthermore, regression analysis is considered in the compensation part for a better stable performance. By combining the block-coordinate method with the Gauss-Newton optimization, we can obtain a compatible performance reducing the computational complexity and stabilizing the performance. In the numerical result for a particular image, we obtain a satisfactory result for 10 repeats of the iteration, which implies a 50% reduction of the computational complexity. The error is also further reduced by 1.5dB compared to the ordinary method.

• Journal of Korean Association for Spatial Structures
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• v.5 no.3 s.17
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• pp.83-89
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• 2005

This paper provides the results of the investigation on the optimum topology of simply supported deep beam structures with multi-point load cases. In this study, the strain energy to be minimized is considered as the objective function and the initial volume of structures is used as the constraint function. The resizing algorithm based on the optimality criteria is adopted to update the hole size existing inside the material. In this study, the sensitivities of topology optimization parameters to the optimum topology of the deep bean structures is investigated and also the effect of filtering process on the optimum topology is thoroughly tested. From numerical tests, the optimum topology of the deep beam is closely related with the optimization parameters used in the iteration and the filtering process play important role in order to find the optimum topology of the deep beam.

• Journal of Korean Association for Spatial Structures
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• v.12 no.2
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• pp.89-98
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• 2012

This study investigates the optimum structural design of space truss considering global buckling, and is to obtain the minimal weight of the structure. The mathematical programming method is used for optimization of each member by member force. Besides, dynamic programming method is adapted for consideration in snap-through buckling. The mathematical modeling for optimum design of truss members consists of objective function of total weight and constrain equations of allowable tensile (or compressive) stress and slenderness. The tangential stiffness matrix is examined to find the critical point on equilibrium path, and a ratio of the buckling load to design load is reflected in iteration procedures of dynamic programming method to adjust the stiffness of space truss. The star dome is examined to verify the proposed optimum design processor. The numerical results of the model are conversed well and satisfied all constrains. This processor is a relatively simple method to carry out optimum design with consideration in global buckling, and is viable in practice with respect to structural design.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.4
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• pp.701-715
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• 2018

A reliability based design approach of the tunnel reinforcement with umbrella arch method was considered to better represent the uncertainties of the weak rock properties around the tunnel. For this, a machine learning approach called an Adaptive Support Vector Machine (ASVM) together with the limit equilibrium method were introduced to minimize the iteration numbers during the classification training of the tunnel stability. The proposed method was compared with the results of typical Monte Carlo simulations. It was concluded that the ASVM was very efficient and accurate to calculate the probability of failure having auxiliary umbrella arches and uncertain material properties of the tunnel. Future work will be concentrated on the refinement of the fast adaptation of the SVM classification so that the minimum number of numerical analyses can be used where the limit solution is not available.

• Journal of IKEEE
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• v.19 no.2
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• pp.219-224
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• 2015

Electrical impedance tomography is an imaging technique to reconstruct the internal conductivity distribution based on applied currents and measured voltages in a domain of interest. In this paper, a modified Gauss-Newton method is proposed for conductivity image reconstruction. In the proposed method, the dimension of the inverse term is reduced by replacing the number of elements with the number of measurement data in the conductivity updating equation of the conventional Gauss-Newton method. Therefore, the computation time is greatly reduced as compared to the conventional Gauss-Newton method. Moreover, the regularization parameter is selected by computing the minimum-maximum from the diagonal components of the Jacobian matrix at every iteration. The numerical experiments with several scenarios were carried out to evaluate the reconstruction performance of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.561-570
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• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.