• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.120-129
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• 2002

An integrated structure and controller design approach for rotating cantilever beam is presented. An optimization method is developed for improving positioning performance considering the elastic deformations during high speed rotation and adopting the beam shape and the control gains as design variables. For this end, a dynamic model is setup by the finite element method according to the shape of the beam. The mass and stiffness of the beam are distributed in such a way that the closed-loop poles of the control system should be located leftmost in the complex s-plane. For optimization method, the simulated annealing method is employed which has higher probability to find the global minimum than the gradient-based down-hill methods. Sequential design and simultaneous design methods are proposed to obtain the optimal shape and controller. Simulations are performed with new designs by the two methods to verify the effectiveness of the approach and the results show that the settling time is improved for point-to-point position controls.

• Journal of Korean Society of societal Security
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• v.4 no.1
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• pp.49-55
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• 2011

The primary objective of this paper is to develop optimal algorithms of reinforced concrete frame structural systems by the limit state design(CP 1110) and to look into the possibility of detailed design of these structural systems. The structural formulation is derived on the finite element method. The objective of optimization of a reinforced structure for a specified geometry is mainly to determine the optimum cross-sectional dimensions of concrete and the area of the various sizes of the reinforcement required for each member. In addition to the detail s such as the amount of web reinforcement, cutoff points of longitudinal reinforcedments etc. are also considered as design variables. In this study, the method of "Generalized Reduced Gradient, Rounding and with Neighborhood search" and "the Sequential Linear Programming" are employed as an analytical method of nonlinear optimization.

• Journal of computational fluids engineering
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• v.10 no.2
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• pp.38-47
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• 2005

Substructuring methods are often used in finite element structural analyses. In this study a multi-level substructuring(MLSS) algorithm is developed and proposed as a possible candidate for finite element fluid solvers. The present algorithm consists of four stages such as a gathering, a condensing, a solving and a scattering stage. At each level, a predetermined number of elements are gathered and condensed to form an element of higher level. At the highest level, each sub-domain consists of only one super-element. Thus, the inversion process of a stiffness matrix associated with internal degrees of freedom of each sub-domain has been replaced by a sequential static condensation of gathered element matrices. The global algebraic system arising from the assembly of each sub-domain matrices is solved using a well-known iterative solver such as the conjugare gradient(CG) or the conjugate gradient squared(CGS) method. A time comparison with CG has been performed on a 2-D Poisson problem. With one domain the computing time by MLSS is comparable with that by CG up to about 260,000 d.o.f. For 263,169 d.o.f using 8 x 8 sub-domains, the time by MLSS is reduced to a value less than $30\%$ of that by CG. The lid-driven cavity problem has been solved for Re = 3200 using the element interpolation degree(Deg.) up to cubic. in this case, preconditioning techniques usually accompanied by iterative solvers are not needed. Finite element formulation for the incompressible flow has been stabilized by a modified residual procedure proposed by Ilinca et al.[9].

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.39-49
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• 2000

In this paper, we propose an optimizing feature extraction method for multiclass problems assuming normal distributions. Initially, We start with an arbitrary feature vector Assuming that the feature vector is used for classification, we compute the classification error Then we move the feature vector slightly in the direction so that classification error decreases most rapidly This can be done by taking gradient We propose two search methods, sequential search and global search In the sequential search, an additional feature vector is selected so that it provides the best accuracy along with the already chosen feature vectors In the global search, we are not constrained to use the chosen feature vectors Experimental results show that the proposed algorithm provides a favorable performance.

• Journal of Power System Engineering
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• v.21 no.6
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• pp.56-61
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• 2017

The check valves are mechanical valves that permit fluids to flow in only one direction, preventing flow from reversing. It is classified as one way directional valves. There are various types of check valves that used in a marine application. A lift type check valve uses the disc to open and close the passage of fluid. The disc lift up from seat as pressure below the disc increases, while drop in pressure on the inlet side or a build up of pressure on the outlet side causes the valve to close. An important concept in check valves is the cracking pressure which is the minimum upstream pressure at which the valve will operate. On the other hand, optimization is a process of finding the best set of parameters to reach a goal while not violating certain constraints. The AMESim software provides NLPQL(Nonlinear Programming by Quadratic Lagrangian) and genetic algorithm(GA) for optimization. NLPQL is the implementation of a SQP(sequential quadratic programming) algorithm. SQP is a standard method, based on the use of a gradient of objective functions and constraints to solve a non-linear optimization problem. A characteristic of the NLPQL is that it stops as soon as it finds a local minimum. Thus, the simulation results may be highly dependent on the starting point which user give to the algorithm. In this paper, we carried out optimization design of the check valve with NLPQL algorithm.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.12 s.117
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• pp.1192-1200
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• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature. However, the identification procedure of the four-parameter is very time-consuming one. In this study a new identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured frequency response functions(FRF) coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment step. A numerical example shows that the proposed method is useful in identifying the viscoelastic material parameters of fractional derivative model.

• Proceedings of the KSMRM Conference
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• 2001.11a
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• pp.109-109
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• 2001

Purpose： To assess the feasibility of sequential administration of ferumoxides and mangafodi trisodium in the same imaging protocols. Method： Thirty patients underwent double-contrast enhanced MR imaging of liver usi ferumoxides (Fe-MRI) and mangafodipir trisodium (Mn-MRI) on 1.5T GE Horizon system. In twenty patients, Mn-MRI was immediately followed by Fe-MRI. In ten patients, Fe-MR was performed first, then Mn-MRI was performed immediately, In all cases, precontras T1-weighted in-phase and opposed-phase spoiled gradient echo (GRE) images an T2-weighted fast spin-echo images (TR 4000ms, TE 102ms, ETL 8-12) were obtained Fe-MRI was performed with FSE and steady state GRE (TE 10 msec, flip angle 30 sequences. Mn-MRI was performed with in-phase and opposed-phase spoiled GR sequences. The SNR changes after the use of each contrast agents were calculated.

• 한국전산유체공학회:학술대회논문집
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• 1999.11a
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• pp.77-84
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• 1999

Numerical design optimization techniques are implemented for the improvement of the ram accelerator performance. The design object is to find the minimum ram tube length required to accelerate projectile from initial velocity $V_0$ to target velocity $V_e$. The premixture is composed of $H_2,\;O_2,\;N_2$ and the mole numbers of these species are selected as design variables. The objective function and the constraints are linearized during the optimization process and gradient-based Simplex method and SLP(Sequential Linear Programming) have been employed. With the assumption of two dimensional inviscid flow for internal flow field, the analyses of the nonequilibrium chemical reactions for 8 steps 7 species lave been performed. To determined the tube length, ram tube internal flow field is assumed to be in a quasi-steady state and the flow velocity is divided into several subregions with equal interval. Hence the thrust coefficients and accelerations for corresponding subregions are obtained and integrated for the whole velocity region. With the proposed design optimization techniques, the total ram tube length had been reduced $19\%$ within 7 design iterations. This optimization procedure can be directly applied to the multi-stage, multi-premixture ram accelerator design optimization problems.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.2 s.95
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• pp.161-168
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• 2005

The absorbing material is mostly used to changing the acoustic energy to the heat energy in the passive control, and that consists of the porous media. That controls an air borne noise while the stiffened plates, damping material and additional mass control a structure borne noise. The additional mass can decrease the sound by mass effect and shift of natural frequency, and damping material can decrease the sound by damping effect. The passive acoustic control using these kinds of control materials has an advantage that is possible to control the acoustic in the wide frequency band and the whole space at a price as compared with the active control using the various electronic circuit and actuator. But the space efficiency decreased and the control ability isn't up to the active control. So it is necessary to maximize the control ability in the specific frequency to raise the capacity of passive control minimizing the diminution of space efficiency such an active control. Therefore, the characteristics of control materials and the optimum layout of control materials that attached to the boundary of structure-acoustic coupled cavity were studied using sequential optimization on this study.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1235-1242
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• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the nonlinear dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature with fewer parameters than conventional spring-dashpot models. However the identification procedure of the four-parameter is very time-consuming one. An efficient identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured FRFs coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment. A numerical example shows that the proposed method is efficient and robust in identifying the viscoelastic material parameters of fractional derivative model.