• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.12-19
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• 2004

An aerodynamic design optimization system for three-dimensional wing was developed as a part of the future MDO framework. The present design optimization system includes four modules such as geometry design, grid generation, flow solver and optimizer. All modules were based on commercial softwares and programmed to have automated execution capability in batch mode utilizing built-in script and journaling. The integration of all modules into the system was accomplished through programming using Visual Basic language. The distributed computational environment based on network communication was established to save computational time especially for time-consuming aerodynamic analyses. The distributed aerodynamic computations were performed in conjunction with the global optimization algorithm of response surface method, instead of using usual parallel computation based on domain decomposition. The application of the design system in the drag minimization problem demonstrated considerably enhanced efficiency of the design process while the final design showed reasonable results of reduced drag.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.449-457
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• 2000

The paper describes the study of global approximate optimization utilizing soft computing techniques such as genetic algorithms (GA's), neural networks (NN's), and fuzzy inference systems(FIS). GA's provide the increasing probability of locating a global optimum over the entire design space associated with multimodality and nonlinearity. NN's can be used as a tool for function approximations, a rapid reanalysis model for subsequent use in design optimization. FIS facilitates to handle the quantitative design information under the case where the training data samples are not sufficiently provided or uncertain information is included in design modeling. Properties of soft computing techniques affect the quality of global approximate model. Evolutionary fuzzy modeling (EFM) and adaptive neuro-fuzzy inference system (ANFIS) are briefly introduced for structural optimization problem in this context. The paper presents the success of EFM depends on how optimally the fuzzy membership parameters are selected and how fuzzy rules are generated.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.4
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• pp.317-326
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• 2008

The main purpose of the present study is to perform shape optimizations of transonic compressor blade in order to enhance its performance. In this study, the Latin hypercube sampling of design of experiments and the weighted average surrogate model with the help of a gradient based optimization algorithm are used within design space by the lower and upper limits of each design variable and for finding optimum designs, respectively. 3-D Reynolds-averaged Navier-Stokes solver is used to evaluate the objective functions of adiabatic efficiency and pressure ratio. Six variables from lean and airfoil thickness profile are selected as design variables. The results show that the adiabatic efficiency is enhanced by 1.43% by efficiency optimization while the pressure ratio is increased very small, and pressure ratio is increased by 0.24% by pressure ratio optimization.

• 한국전산유체공학회:학술대회논문집
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• 2000.05a
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• pp.159-165
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• 2000

In this paper, numerical study has been done for the improvement of the superdetonative ram accelerator performance and for the design optimization of the system. The objective function to optimize the premixture composition is the ram tube length required to accelerate projectile from initial velocity $V_o$ 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 at design variables. RSM(Response Surface Methodology) which is widely used for the complex optimization problems is selected as the optimization technique. In particular, to improve the non-linearity of the response and to consider the accuracy and efficiency of the solution, design space stretching technique has been applied. Separate sub-optimization routine is introduced to determine the stretching position and clustering parameters which construct the optimum regression model. Two step optimization technique has been applied to obtain the optimal system. With the application of stretching technique, we can perform system optimization with a small number of experimental points, and construct precise regression model for highly non-linear domain. The error to compared with analysis result is only $0.01\%$ and it is demonstrated that present method can be applied more practical design optimization problems with many design variables.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.572-577
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• 2007

The paper presents design optimization of an automobile body for dynamic stiffness improvement. The thicknesses of plates making-up the monocoque body of an automobile were employed as design variables for optimization and the objective was to increase the first torsional and bending natural frequencies. By allotting one design variable to each plate of the body, compared to previous works based on element-wise design variables, design space of optimization was reduced to a large extent and numerical instabilities such as checkerboard pattern was efficiently evaded. The method resulted to a considerable amount of increase in the automobile body's torsional and bending natural frequencies. Considering manufacturability of the optimized result, the converged values of plate thicknesses were approximated to commercially-available values by appropriately reflecting their design sensitivities.

• Journal of Korean Association for Spatial Structures
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• v.1 no.1 s.1
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• pp.143-155
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• 2001

Generally, truss design has been determined by the designer's experience and intuition. But if we perform the most economical structural design we must consider not only cross-sections of members but also configurations(howe, warren and pratt types etc.) of single truss as the number of panel and truss height. The purpose of this study is to develope automated optimum design techniques for steel truss structures considering cross-sections of members and shape of trusses simultaneously. As the results, it could be possible to find easily the optimum solutions subject to design conditions at the preliminary structural design stage of the steel truss structures. In this study, the objective function is expressed as the whole member weight of trusses, and the applied constraints are as stresses, slenderness ratio, local buckling, deflection, member cross-sectional dimensions and truss height etc. The automated optimum design algorithm of this study is divided into three-level procedures. The first level on member cross-sectional optimization is performed by the sequential unconstrained minimization technique(SUMT) using dynamic programming method. And the second level about truss height optimization is applied for obtaining the optimum truss height by three-equal interval search method. The last level of optimization is applied for obtaining the optimum panel number of truss by integer programming method. The algorithm of multi-level optimization programming technique proposed in this study is more helpful for the economical design of plane trusses as well as space trusses.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.3
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• pp.173-184
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• 2013

A multi-level design optimization framework for aerodynamic design of rotary wing such as propeller and helicopter rotor blades is presented in this study. Strategy of the proposed framework is to enhance aerodynamic performance by sequentially applying the planform and sectional design optimization. In the first level of a planform design, we used a genetic algorithm and blade element momentum theory (BEMT) based on two-dimensional aerodynamic database to find optimal planform variables. After an initial planform design, local flow conditions of blade sections are analyzed using high-fidelity CFD methods. During the next level, a sectional design optimization is conducted using two dimensional Navier-Stokes analysis and a gradient based optimization algorithm. When optimal airfoil shape is determined at the several spanwise locations, a planform design is performed again. Through this iterative design process, not only an optimal flow condition but also an optimal shape of an EAV propeller blade is obtained. To validate the optimized propeller-blade design, it is tested in wind-tunnel facility with different flow conditions. An efficiency, which is slightly less than the expected improvement of 7% predicted by our proposed design framework but is still satisfactory to enhance the aerodynamic performance of EAV system.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.141-148
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• 2000

In system design, it is not always possible that all decision makers can cooperate fully and thus avoid conflict. They each control a specified subset of design variables and seek to minimize their own cost functions subject to their individual constraints. However, a system management team makes every effort to coordinate multiple disciplines and overcome such noncooperative environment. Although full cooperation is difficult to achieve, noncooperation also should be avoided as possible. Our approach is to predict the results of their cooperation and generate approximate Pareto set for their multiple objectives. The Pareto set can be obtained according to the degree of one's conceding coupling variables in the other's favor. We employ approximation concept for modelling this coordination and the mutiobjective genetic algorithm for exploring the coupling variable space for obtaining an approximate Pareto set. The approximation management concept is also used for improving the accuracy of the Pareto set. The exploration for the coupling variable space is more efficient because of its smaller dimension than the design variable space. Also, our approach doesn't force the disciplines to change their own way of running analysis and synthesis tools. Since the decision making process is not sequential, the required time can be reduced comparing to the existing multidisciplinary optimization techniques. This approach is applied to some mathematical examples and structural optimization problems.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.4
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• pp.566-576
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• 1995

A Computational code has been developed in order to design axial fans by the numerical optimization techniques incorporated with flow analysis code solving three-dimensional Navier-Stokes equation. The steepest descent method and the conjugate gradient method are used to look for the search direction in the design space, and the golden section method is used for one-dimensional search. To solve the constrained optimization problem, sequential unconstrained minimization technique, SUMT, is used with imposed quadratic extended interior penalty functions. In the optimization of two-dimensional cascade design, the ratio of drag coefficient to lift coefficient is minimized by the design variables such as maximum thickness, maximum ordinate of camber and chord wise position of maximum ordinate. In the application of this numerical optimization technique to the design of an axial fan, the efficiency is maximized by the design variables related to the sweep angle distributed by quadratic function along the hub to tip of fan.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.42-48
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• 2006

In this study, a repetitive response surface enhancement technique (RRSET) is proposed as a new system approximation method for the efficient multidisciplinary design and optimization (MDO). In order to represent the highly nonlinear behavior of the response with second order polynomials, RRSET introduces a design space transformation using stretching functions and repetitive response surface improvement. The tentative optimal point is repetitively included to the set of experimental points to better approximate the response surface of the system especially near the optimal point, hence a response surface with significantly improved accuracy can be generated with very small experimental points and system iterations. As a system optimizer, the simulated annealing, which generates a global design solution is utilized. The proposed technique is applied to several numerical examples, and demonstrates the validity and efficiency of the method. With its improved approximation accuracy, the RRSET can contribute to resolve large and complex system design problems under MDO environment.