• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2262-2267
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• 2018

In electric machine design, there is a large computation cost for finite element analyses (FEA) when analyzing nonlinear characteristics in the machine Therefore, for the optimal design of an electric machine, designers commonly use an optimization algorithm capable of excellent convergence performance. However, robustness consideration, as this factor can guarantee machine performances capabilities within design uncertainties such as the manufacturing tolerance or external perturbations, is essential during the machine design process. Moreover, additional FEA is required to search robust optimum. To address this issue, this paper proposes a computationally efficient robust optimization algorithm. To reduce the computational burden of the FEA, the proposed algorithm employs a useful technique which termed static analysis assisted technique (SAAT). The proposed method is verified via the effective robust optimal design of electric machine to reduce cogging torque at a reasonable computational cost.

• The Journal of the Acoustical Society of Korea
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• v.1 no.1
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• pp.19-26
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• 1982

n optimization technique is adapted to determine the stage enclosure configuration preferred by performers. The merit function which quantifies the ease of ensemble among the performers is derived from a set of qualitative conditions recommended by researchers of hall acoustics. The ray path tracing technique based on the modified method of images is used to analyze acoustical characteristics at any locations of performers in stage enclosure. The gradient search technique is employed to find the geometric parameters which maximmize the merit function. As an example, optimum stage enclosure configuration of the trio chamber music is obtained using the computer program developed. The developed technique can be used in the design of concert hall stage and also in forming a special enclosure with movable reflecting surfaces.

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1121-1130
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• 2004

The Genetic Algorithm (GA), an optimization technique based on the theory of natural selection, has proven to be a relatively robust means of searching for global optimum. It converges to the global optimum point without auxiliary information such as differentiation of function. In the case of a complex problem, the GA involves a large population number and requires a lot of computing time. To improve the process, this research used parallel processing with several personal computers. Parallel process technique is classified into two methods according to subpopulation's size and number. One is the fine-grained method (FGM), and the other is the coarse-grained method (CGM). This study selected the CGM as a parallel process technique because the load is equally divided among several computers. The given design domain should be reduced according to the degree of feasibility, because mechanical system problems have constraints. The reduced domain is used as an initial design domain. It is consistent with the feasible domain and the infeasible domain around feasible domain boundary. This parallel process used the Message Passing Interface library.

• Journal of KSNVE
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• v.7 no.4
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• pp.645-653
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• 1997

For high performance rotating machinery, unstable vibrations may occur caused by hydrodynamic forces such as oil film forces, clearance excitation forces generated by the working fluid, and etc. In order to improve the availability one has to take into account the vibrations very accurately. When designing a rotating machinery, the stability behavior and the resonance response can be obtained by calculation of the complex eigenvalues. A suitable modifications of seal and/or bearing design may effectively improve the stability and the response of a rotor system. This paper deals with the optimum length and clearance of seals and bearings to minimize the resonance response(Q factor) and to maximize the logarithmic decrement in the operating speed under the constraints of design variables. Also, for an avoidance of resonance region from the operating speed, an optimization technique has been used to yield the critical speeds as far from the operating speed as possible. The optimization method is used by the genetic algorithm, which is a search algorithm based on the mechanics of natural selection and natural genetics. The results show that the optimum design of seals and bearings can significantly improve the resonance and the stability of the pump rotor system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.11
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• pp.1889-1896
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• 2003

In the microfluidic applications, viscous-driven pumping mechanism is a promising one since the viscous effect increases significantly as the size of device decreases, relative to the inertial effect. However, there exist a few drawbacks we have to improve such as low efficiency and small volume flow rate. In the present study, an optimum design synthesis is proposed to enhance the performance characteristics of the micropump with single rotating cylinder. First, the unstructured grid CFD method is described and validated by comparing its results to the previous results. Next, an automated optimum design synthesis tool is constructed by combining the aforementioned CFD analysis model with the mathematical optimization model. This technique is used to improve the performance characteristics of newly designed viscous-driven pump. The presented results show that the fluid dynamic optimization tool is robust and may be applied to other microfluidic device design applications.

• Computational Structural Engineering
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• v.10 no.4
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• pp.349-358
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• 1997

The present paper describes an investigation into the application of the genetic algorithm (GA) in the optimum design of composite laminated structure. Stochastic processes generate an initial population of designs and then apply principles of natural selection/survival of the fittest to improve the designs. The five test functions are used to verify the robustness and reliability of the GA, and as a numerical example, minimum weight of a cantilever composite laminated beam with a mix of continuous, integer and discrete design variables is obtained by using the GA with exterior penalty function method. The design problem has constraints on strength, displacements, and natural frequencies, and is formulated to a multidimensional nonlinear form. From the results, it is found that the GA search technique is very effective to find the good optimum solution as well as has higher robustness.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.12 s.243
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• pp.1629-1637
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• 2005

Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.464-469
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• 2005

Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1774-1779
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• 2005

Most of materials receive force in using, therefore, the characteristics of materials must be considered in system design not to occur deformation or destruction. Mechanical properties about materials can be expressed as responsible level of material itself under the exterior operation. Main mechanical properties is strength, hardness, ductility and stiffness etc. Currently, among major measure facilities to measure such mechanical properties, advanced indentation technique has focused in industrial areas as reason of nondestructive and easy applications for mechanical tensile properties and evaluation of residual stress of materials. This study is to find the optimum experimental condition about residual stress advanced indentation technique for accurate analysis of the welded joint of steel materials through indentation load-depth curve obtained from cruciform specimen experiment. Optimum selection was applied to the welded joint of real steel materials to give non-equi-biaxial stress state and compared with general residual stress analyzing method for verification.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.232-238
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• 2011

In the present study, Taguchi method is used to determine the rough region first, followed by RSM technique to determine the exact optimum value during milling on a machining center. A region reducing algorithm is applied to narrow down the region of the Taguchi method for RSM. The result from the Taguchi method is fed to train the artificial neural network (ANN), whose optimum value is used to drive the region reducing algorithm. The proposed algorithm is tested under different cutting condition and results show that the introduced algorithm works well during milling process. It is also shown that theoretically obtained optimal cutting condition is very close to experimentally obtained result.