• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.8
• /
• pp.1353-1362
• /
• 2003

This paper considers a simultaneous optimization problem of structure and control systems. The problem is generally formulated as a non-convex optimization problem for the design parameters of mechanical structure and controller. Therefore, it is not easy to obtain the global solutions for practical problems. In this paper, we parameterize all design parameters of the mechanical structure such that the parameters work in the control system as decentralized static output feedback gains. Using this parameterization, we have formulated a simultaneous optimization problem in which the design specification is defined by the Η$_2$and Η$\_$$\infty$/ norms of the closed loop transfer function. So as to lead to a convex problem we approximate the nonlinear terms of design parameters to the linear terms. Then, we propose a convex optimization method that is based on linear matrix inequality (LMI). Using this method, we can surely obtain suboptimal solution for the design specification. A numerical example is given to illustrate the effectiveness of the proposed method.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.14 no.1
• /
• pp.36-42
• /
• 2006

Kriging has been effectively used to approximate for optimization. This study has been devised to improve efficiency and accuracy of approximate optimal design using Kriging. The design of experiments (DOE), the classical design and space-filling design, are used to provide maximum information using minimum number of design of experiments. The proposed methodology is applied to the designs of 3-bar truss and Sandgren's pressure vessel.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
• /
• 2003.09a
• /
• pp.15-15
• /
• 2003

We provide some recent results of approximation algorithms for solving Markov Games and discuss their applications to problems that arise in Computer Science. We consider a receding horizon approach as an approximate solution to two-person zero-sum Markov games with an infinite horizon discounted cost criterion. We present error bounds from the optimal equilibrium value of the game when both players take “correlated” receding horizon policies that are based on exact or approximate solutions of receding finite horizon subgames. Motivated by the worst-case optimal control of queueing systems by Altman, we then analyze error bounds when the minimizer plays the (approximate) receding horizon control and the maximizer plays the worst case policy. We give two heuristic examples of the approximate receding horizon control. We extend “parallel rollout” and “hindsight optimization” into the Markov game setting within the framework of the approximate receding horizon approach and analyze their performances. From the parallel rollout approach, the minimizing player seeks to combine dynamically multiple heuristic policies in a set to improve the performances of all of the heuristic policies simultaneously under the guess that the maximizing player has chosen a fixed worst-case policy. Given $\varepsilon$>0, we give the value of the receding horizon which guarantees that the parallel rollout policy with the horizon played by the minimizer “dominates” any heuristic policy in the set by $\varepsilon$, From the hindsight optimization approach, the minimizing player makes a decision based on his expected optimal hindsight performance over a finite horizon. We finally discuss practical implementations of the receding horizon approaches via simulation and applications.

• Proceedings of the KSME Conference
• /
• 2004.11a
• /
• pp.1022-1027
• /
• 2004

In this study, the shape of plate-fin type heat sink is numerically optimized to acquire the minimum pressure drop under the required temperature rise. To do this, a new sequential approximate optimization (SAO) is proposed and it is integrated with the computational fluid dynamics (CFD). In thermal/fluid systems for constrained nonlinear optimization problems, three fundamental difficulties such as high cost for function evaluations (i.e., pressure drop and thermal resistance), the absence of design sensitivity information, and the occurrence of numerical noise are confronted. To overcome these problems, the progressive quadratic response surface method (PQRSM), which is one of the sequential approximate optimization algorithms, is proposed and the heat sink is optimize by means of the PQRSM.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.29 no.10 s.241
• /
• pp.1139-1147
• /
• 2005

The shape optimal design of the plate-fin type heat sink with vortex generator is performed to minimize the pressure loss subjected to the desired maximum temperature numerically. Evaluation of the performance function, in general, is required much computational cost in fluid/thermal systems. Thus, global approximate optimization techniques have been introduced into the optimization of fluid/thermal systems. In this study, Kriging method Is used to obtain the optimal solutions associated with the computational fluid dynamics (CFD). The results show that when the temperature .rise is less than 40 K, the optimal design variables are $B_1=2.44\;mm,\;B_2=2.09\;mm$, and t=7.58 mm. Kriging method can dramatically reduce computational time by 1/6 times compared to SQP method so that the efficiency of Kriging method can be validated.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.2E
• /
• pp.63-70
• /
• 2002

In this paper, an optimization technique for thin walled beams of vehicle body structure is proposed. Stiffness of thin walled beam structure is characterized by the thickness and typical section shape of the beam structure. Approximate functions for the section properties such as area, area moment of inertia, and torsional constant are derived by using the response surface method. The approximate functions can be used for the optimal design of the vehicle body that consists of complicated thin walled beams. A passenger car body structure is optimized to demonstrate the proposed technique.

• Journal of Mechanical Science and Technology
• /
• v.15 no.8
• /
• pp.1132-1142
• /
• 2001

The paper describes the construction of global function approximation models for use in design optimization via global search techniques such as genetic algorithms. Two different approximation methods referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the training data is not sufficiently provided or uncertain information may be included in design process. Fuzzy inference system is the central system for of identifying the input/output relationship in both methods. The paper introduces the general procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and presents their generalization capabilities in terms of a number of fuzzy rules and training data with application to a three-bar truss optimization.

• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.1023-1028
• /
• 2004

A micro-pressure wave is generated by the high-speed train which enters a tunnel, and it causes explosive noise and vibration at the exit. It is known that train speed, train-tunnel area ratio, nose slenderness and nose shape mainly influence on generating micro-pressure wave. So it is required to minimize it by searching optimal values of such train shape factors and tunnel condition. In this study, response surface model, one of approximation models, is used to perform optimization effectively and analyze sensitivity of design variables. Owen's randomized orthogonal array and D-optimal Design are used to construct response surface model. In order to increase accuracy of model, stepwise regression is selected. Finally SQP(Sequential Quadratic Programming) optimization algorithm is used to minimize the maximum micro-pressure wave by using built approximation model.

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

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.8
• /
• pp.1059-1067
• /
• 2013

Automotive fuel tank is generally divided into two parts: main frame and assembly parts. While the car is running, valves are used to prevent liquid carry over and to discharge evaporated gas from the fuel tank. However, current fuel tank designs focus on the gas ventilation or secured location. In this study, the location of the parts used to prevent liquid carry over within the fuel tank is evaluated during an optimal design process. To develop this design process, an approximate optimization is applied. Through the optimal design process, the optimal valve location in fuel tank is determined and the approximate optimization is validated by the Taguchi method. Finally, the optimized valve location is used to reduce the development cost and time and to contribute toward improved automobile quality owing to enhanced reliability.