• Structural Engineering and Mechanics
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• v.63 no.4
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• pp.481-495
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• 2017

The present article examines the static response of multilayered magneto-electro-elastic (MEE) beam in thermal environment through finite element (FE) methods. On the basis of the minimum total potential energy principle and the coupled constitutive equations of MEE material, the FE equilibrium equations of cantilever MEE beam is derived. Maxwell's equations are considered to establish the relation between electric field and electric potential; magnetic field and magnetic potential. A simple condensation approach is employed to solve the global FE equilibrium equations. Further, numerical evaluations are made to examine the influence of different in-plane and through-thickness temperature distributions on the multiphysics response of MEE beam. A parametric study is performed to evaluate the effect of stacking sequence and different temperature profiles on the direct and derived quantities of MEE beam. It is believed that the results presented in this article serve as a benchmark for accurate design and analysis of the MEE smart structures in thermal applications.

• International Journal of Automotive Technology
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• v.5 no.3
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• pp.145-153
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• 2004

Potential fuel economy improvements and environmental legislation have renewed interest in Gasoline Direct Injection (GDI) engines. Computational models of fuel injection and mixing processes pre-ignition are being developed for engine optimisation. These highly transient thermofluid models require verification against temporally and spatially resolved data-sets. The authors have previously established the capability of PDA to provide suitable temporally and spatially resolved spray characteristics such as mean droplet size, velocity components and qualitative mass distribution. This paper utilises this data-set to assess the predictive capability of a numerical model for GDI spray prediction. After a brief description of the two-phase model and discretisation sensitivity, the influence of initial spray conditions is discussed. A minimum of 5 initial global spray characteristics are required to model the downstream spray characteristics adequately under isothermal, atmospheric conditions. Verification of predicted transient spray characteristics such as the hollow-cone, cone collapse, head vortex, stratification and penetration are discussed, and further improvements to modelling GDI sprays proposed.

• Journal of the Korean Society of Safety
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• v.25 no.4
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• pp.7-12
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• 2010

The average growth in the wind power energy market during the past five years has been 26% per year. Renewable energy resources, of which wind energy is prominent, are part of the solution to the global energy problem. Wind power system and the rotor blade concepts are reviewed, and loadings by wind and gravity as important factors for the mechanical performance of the materials are considered. So, the mechanical properties of fiber composite materials are discussed. In addition, it is necessary to analyze and evaluate the stress distribution and deformation for them in the design level. This study shows the result that CFRP rotor blade of wind turbine satisfies the strength and deformation through numerical analysis using the commercial finite element analysis program.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.129-132
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• 1992

Cellular kinetics formulate the basis of tumor immune system dynamics which may be synthesized mathematically as cascades of bilinear systems which are connected by nonlinear dynamical terms. In this manner, a foundation for the control of syngeneic tumors is presented. We have analyzed the mechanisms of controlling the infiltration of lymphocytes into tumor tissues. Simulated anneal ins, a general-purpose method of multivariate optimization, is applied to combinatorial optimization, which is to find the minimum of a given function depending on many parameters. We compare the results of the different methods including the global optimization algorithm, known as simutated annealing.

• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.95-101
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• 2015

To accurately extract absolute distance information from a self-mixing interferometry (SMI) signal, in this paper we propose an approach based on a particle swarm optimization (PSO) algorithm instead of frequency estimation for absolute distance. The algorithm is utilized to search for the global minimum of the fitness function that is established from the self-mixing signal to find out the actual distance. A resolution superior to $25{\mu}m$ in the range from 3 to 20 cm is obtained by experimental measurement, and the results demonstrate the superiority of the proposed approach in comparison with interpolated FFT. The influence of different external feedback strength parameters and different inertia weights in the algorithm is discussed as well.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.146-158
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• 1991

In this paper, we deal with the TSP (Traveling Salesperson Problem) which is well-known as NP-complete optimization problem. the TSP is applicable to network routing. task allocation or scheduling. and VLSI wiring. Well known numerical methods such as Newton's Metheod. Gradient Method, Simplex Method can not be applicable to find Global Solution but the just give Local Minimum. Exhaustive search over all cyclic paths requires 1/2 (n-1) ! paths, so there is no computer to solve more than 15-cities. Heuristic algorithm. Simulated Annealing, Artificial Neural Net method can be used to get reasonable near-optimum with polynomial execution time on problem size. Therefore, we are able to select the fittest one according to the environment of problem domain. Three methods are simulated about symmetric TSP with 30 and 50-city samples and are compared by means of the quality of solution and the running time.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.956-959
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• 1996

In this study, we propose a neuro-genetic controller combined with a linear controller in parallel to improve the tracking performance of the Line of Sight(LOS) stabilization system and reject the effect of disturbances. A Genetic Algorithm(GA) is used to optimize weights of the neuro-genetic controller since this algorithm can search a global minimum without derivatives or other auxiliary knowledge. The LOS system is very complex and has limited measurable output data. Under these specific circumstances GA solves many problems that other training methods have. Computer simulation results show that the, proposed controller makes better tracking response and rejection of disturbance than a linear controller.

• KIEAE Journal
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• v.8 no.2
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• pp.41-46
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• 2008

Owing to a space covered by glass, atrium is an attractive space with a possibility as an inner public space but a typical building type with a high-energy load. From the aspect of global environmental issues, to reduce energy load is an important assignment to solve. Contriving a planning guideline of an opening is considered as the most effective environment adjustment method, to offer a highly assessed amenity space and secure openness to outside, keep the energy load to a minimum, and apply the natural energy such as daylight to a maximum at the same time. Users' assessment of environment was performed by questionnaire survey, then the structure of users' assessment was analyzed and design condition was regulated by multiple regression analysis. The opening design guideline to offer a highly assessed space was proposed with concrete environment adjustment method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.125-130
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• 2001

In this paper, we propose a new type of evolution strategies combined with reinforcement learning. We use the variances of fitness occurred by mutation to make the reinforcement signals which estimate and control the step length of mutation. With this proposed method, the convergence rate is improved. Also, we use cauchy distributed mutation to increase global convergence faculty. Cauchy distributed mutation is more likely to escape from a local minimum or move away from a plateau. After an outline of the history of evolution strategies, it is explained how evolution strategies can be combined with the reinforcement learning, named reinforcement evolution strategies. The performance of proposed method will be estimated by comparison with conventional evolution strategies on several test problems.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.165.1-165
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• 2001

The evolution strategy is a good evolutionary algorithm to find the global optimum of a real-valued function. Since many engineering problems can be formulated as real valued function optimization, the evolution strategy is frequently employed in engineering fields. However, in many engineering optimization problems, an optimization parameter is often restricted in the bounded region between two specified values, the minimum and the maximum limit, respectively. Since an offspring individual is generated randomly around a parent individual during mutation process of the evolution strategy, an individual outside the search region can be generated even if the parent is inside the search region. This paper proposes two new boundary-handling techniques for evolution strategies. One is the ...