• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.109-116
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• 2002

The solution of the aircraft wing spar cross-section area optimization problem is obtained by the response surface method. The object function of the problem is wing total weight, design variables are spar cross-section areas, constraints are the conditions that the stresses at the each spar is less than the allowable stress. D-Optimal condition is utilized to obtain the experimental points to construct the response surfaces. D-Optimal experimental points are obtained by the commercial software "Deign-Expert". Response values for the object function and constraints for each experimental point are calculated by the NASTRAN. Response surfaces for object function and constraints are approximated from the response values by the least square method. The optimization solution is obtained by the DOT for the response surfaces of object function and constraints. The optimization results obtained from the response surface are compared with the results obtained by the NASTRAN SOL200.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.10
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• pp.659-664
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• 2000

This paper presents a new design method for improving the torque performance of a switched reluctance motor (SRM) for high speed applications. The drawback of the conventional design method based on the overall static average torque maximization is that the torque control performance is degraded at high speed. On the other hand, the proposed method optimizes the torque profile by diving it into several regions so that it is suitable for high speed operation. This multi-objective optimization problem is solved by using a fuzzy optimization algorithm which incorporates a finite element method. The torque performance of the motor for various speed ranges is investigated and the optimally designed motor show a better performance at high speed.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.83.4-83
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• 2002

$\bullet$ We present a state-feedback RHC for discrete-time TS fuzzy systems with input constriants. $\bullet$ The controller employ the current and one-step past information on the fuzzy weighting functions. $\bullet$ It is obtained from the finite horizon optimization problem with the invariant ellipsoid constraint $\bullet$ Under parameterized LMI conditions on the terminal weighting matrix $\bullet$ The closed-loop system stability is guaranteed. $\bullet$ The parameterized linear matrix inequalities are relaxed to a finite number of solvable LMIs.

• The KSFM Journal of Fluid Machinery
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• v.5 no.3 s.16
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• pp.40-45
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• 2002

Since the previous cut-and-try design algorithm requires much cost and time, the automated design technique with the CFD and optimum design algorithm has recently been concerned. In this work, the Navier-Stokes equation was solved to gain more detailed viscous flow information of cascade with rotor-stator interactions. The H-grid embedded by O-grid was generated to obtain more accurate solution by eliminating the branch cut of H-grid near airfoil surface. To handle the relative motion of the rotor to the stationary stator, the sliding multiblock method was applied and the cubic-spline interpolation was used on the block interface boundary. To validate present procedure, the time-averaged aerodynamic loads were compared with experimeatal data. A good agreement was obtained. The Modified Method of Feasible Direction (MMFD) was used to carry out the sensitivity analysis of the change of aerodynamic performance by the changes of the cascade geometry. The present optimization of the cascade gave a dramatic reduction of the drag while the lift maintains at the value within the user-specified tolerance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.805-811
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• 2012

The reliability based design optimization (RBDO) approach requires high computing cost to consider uncertainties. In order to reduce the design cost, the single loop single vector (SLSV) approach has been developed for RBDO. This method can reduce the cost in calculating deign sensitivity by elimination of the nested optimization process. However, this process causes the increment of the instability or inaccuracy of the method according to the problem characteristics. Therefore, the method may not give accurate solution or the robustness of the solution is not guaranteed. Especially, when the function is concave, the process frequently diverges. In this research, the concept of the conjugate gradient method for unconstrained optimization is utilized to develop a new single loop single vector method. The conjugate gradient is calculated with gradient directions at the most probable points (MPP) of previous cycles. Mathematical examples are solved for the verification of the proposed method. The numeri cal performances of the obtained results are compared to those of other RBDO methods. The SLSV approach using conjugate gradient is not greatly influenced by the problem characteristics and improves its convergence capability.