• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.12-23
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• 1994

This paper proposes an optimal design software for the open-chain dynamic systems whose governing equations are expressed as differential equation. In this software, an input module and an automatic creation module of the equation of motion are developed to contrive the user's convenience. To analyze the equation of motion of the dynamic systems, variable-order and variable-stepsize Adams-Bashforth-Moulton predictor-corrector method is used to improve the efficiency. For the optimization and the design sensitivity analysis, ALM(augmented lagrange multiplier)method and adjoint variable method are adopted respectively. An output module with which the user can compare and investigate the analysis and the optimization results through tables and graphs is also provided. The developed software is applied to three typical dynamic response optimization problems, and the results compare very well with those available in the literature, demonstrating its effectiveness.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.876-888
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• 2001

For a large scaled optimization based on response surface methods, an efficient quadratic approximation method is presented in the context of the trust region model management strategy. If the number of design variables is η, the proposed method requires only 2η+1 design points for one approximation, which are a center point and tow additional axial points within a systematically adjusted trust region. These design points are used to uniquely determine the main effect terms such as the linear and quadratic regression coefficients. A quasi-Newton formula then uses these linear and quadratic coefficients to progressively update the two-factor interaction effect terms as the sequential approximate optimization progresses. In order to show the numerical performance of the proposed method, a typical unconstrained optimization problem and two dynamic response optimization problems with multiple objective are solved. Finally, their optimization results compared with those of the central composite designs (CCD) or the over-determined D-optimality criterion show that the proposed method gives more efficient results than others.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5614-5633
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• 2018

Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficiency.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.4
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• pp.811-825
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• 1998

An approximate line search is presented for dynamic response optimization with Augmented Lagrange Multiplier(ALM) method. This study empolys the approximate a augmented Lagrangian, which can improve the efficiency of the ALM method, while maintaining the global convergence of the ALM method. Although the approximate augmented Lagragian is composed of only the linearized cost and constraint functions, the quality of this approximation should be good since an approximate penalty term is found to have almost second-order accuracy near the optimum. Typical unconstrained optimization algorithms such as quasi-Newton and conjugate gradient methods are directly used to find exact search directions and a golden section method followed by a cubic polynomial approximation is empolyed for approximate line search since the approximate augmented Lagrangian is a nonlinear function of design variable vector. The numberical performance of the proposed approach is investigated by solving three typical dynamic response optimization problems and comparing the results with those in the literature. This comparison shows that the suggested approach is robust and efficient.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.5
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• pp.26-35
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• 2003

Propellers operating in a given nonuniform ship wake generate unsteady loads leading to undesirable stern vibration problems. The skew is known to be the most proper and effective geometric parameter to control or reduce the fluctuating forces on the shaft. This paper assumes the skew profile as either a quadratic or a cubic function of the radius and determines the coefficients of the polynomial function by applying the simplex method. The method uses the converted unconstrained algorithm to solve the constrained minimization problem of 6-component shaft excitation forces. The propeller excitation was computed either by applying the two-dimensional gust theory for quick estimation or by the fully three-dimensional unsteady lifting surface theory in time domain for an accurate solution. A sample result demonstrates that the shaft forces can be further reduced through optimization from the original design.

• Journal of Power Electronics
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• v.4 no.3
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• pp.127-137
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• 2004

This paper introduces a hybrid induction motor control using a genetically optimized pseudo-on-line method. Optimization results from the use of a look-up table based on genetic algorithms to find the global optimum of an unconstrained optimization problem. The approach to induction motor control includes a pseudo-on-line procedure that optimally estimates parameters of a fuzzy PID (FPID) controller. The proposed hybrid genetic fuzzy PID (GFPID) controller is applied to speed control of a 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed controller performs better than conventional FPID and PID controllers. The contribution of this paper is the introduction of a high performance hybrid form of induction motor control that makes on-line and real-time control of the drive system possible.

• Structural Engineering and Mechanics
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• v.35 no.1
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• pp.83-98
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• 2010

In this paper, the mass optimization of four bar linkages is carried out using genetic algorithms (GA) with single and dual constraints. The single constraint of bending stress and the dual constraints of bending and buckling stresses are imposed. From the movement response of the bar linkage mechanism, the analysis of the mechanism is developed using the combination of kinematics, kinetics, and finite element analysis (FEA). A penalty-based transformation technique is used to convert the constrained problem into an unconstrained one. Lastly, a detailed comparison on the effect of single constraint and of dual constraints is presented.

• Computers and Concrete
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• v.4 no.4
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• pp.317-330
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• 2007

Steel reinforced concrete is perhaps the most versatile and widely used construction material. The versatility is attributed to mouldability of concrete to any conceivable shape. The inherent property of cracking of concrete is the reason for its low tensile strength and hence the design approach of RCC sections in flexure adopts the cracked section theory where in concrete in tension zone is ignored. Means, modes and methods of exploitation of concrete strength by conceiving shapes other than rectangular whereby ineffective concrete in tension zone is reduced and incorporated in compression zone where it is effective needs consideration. Shape optimization of beams is attempted in this analytical investigation employing Sequential Unconstrained Minimization Technique (SUMT). The results clearly show that trapezoidal beams happen to be less costlier than their rectangular counterparts, their usage needs serious reconsideration by the designers.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.725-730
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• 2000

Genetic algorithms based on the theory of natural selection, have been applied to many different fields, and have proven to be relatively robust means to search for global optimum and handle discontinuous or even discrete data. Genetic algorithms are widely used for unconstrained optimization problems. However, their application to constrained optimization problems remains unsettled. The most prevalent technique for coping with infeasible solutions is to penalize a population member for constraint violation. But, the weighting of a penalty for a particular problem constraint is usually determined in the heuristic way. Therefore this paper proposes, the effective technique for handling constraints, the ranking penalty method and hybrid genetic algorithms. And this paper proposes dynamic mutation tate to maintain the diversity in population. The effectiveness of the proposed algorithm is tested on several test problems and results are discussed.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.10
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• pp.860-869
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• 2003

Design optimization of the heat sink with 7${\times}$7 square pin-fins is performed numerically using the Computational Fluid Dynamics (CFD) and the Computer Aided Optimization (CAO). In the pin-fins heat sink, the optimum design variables for fin height (h), fin width (w), and fan-to-heat sink distance (c) can be achieved when the thermal resistance ($\theta$$_{j}$) at the junction and the overall pressure drop ($\Delta$p) are minimized simultaneously. To complete the optimization, the finite volume method for calculating the objective functions, the BFGS method for solving the unconstrained non-linear optimization problem, and the weighting method for predicting the multi-objective problem are used. The results show that the optimum design variable for the weighting coefficient of 0.5 are as follows: w=4.653 mm, h=59.215 mm, and c=2.667 mm. In this case, the objective functions are predicted as 0.56K/W of thermal resistance and 6.91 Pa of pressure drop. The Pareto optimal solutions are also presented.re also presented.d.