• Proceedings of the KIPE Conference
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• 2003.07a
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• pp.10-14
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• 2003

This paper deals with the design of heat dissipation system using the forced air cooling method. It suggests the method of appropriately dividing the whole thermodynamic system into analytical subsystems and also presents the correspondent analytic or experimental equations to subsystems. The experimental results on the designed thermodynamic system for 400kw 1GBT inverter show the validity of the proposed design method in the steady state.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1029-1038
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• 2014

Bayesian experimental design is a useful concept in applied statistics for the design of efficient experiments especially if prior knowledge in the experiment is available. However, a theoretical or numerical approach is not simple to implement. We review the concept of a Bayesian experiment approach for linear and nonlinear statistical models. We investigate relationships between prior knowledge and optimal design to identify Bayesian experimental design process characteristics. A balanced design is important if we do not have prior knowledge; however, prior knowledge is important in design and expert opinions should reflect an efficient analysis. Care should be taken if we set a small sample size with a vague improper prior since both Bayesian design and non-Bayesian design provide incorrect solutions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.755-756
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• 2013

• Environmental Engineering Research
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• v.15 no.3
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• pp.129-134
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• 2010

The optimization of experimental parameters, such as catalyst type, catalyst concentration, molar ratio of alcohol to oil and reaction temperature, on the transesterification for the production of rapeseed methyl ester has been studied. The Taguchi approach (Taguchi method) was adopted as the experimental design methodology, which was adequate for understanding the effects of the control parameters and to optimize the experimental conditions from a limited number of experiments. The optimal experimental conditions obtained from this study were potassium hydroxide as the catalyst, at a concentration of 1.5 wt %, and a reaction temperature of $60^{\circ}C$. According to Taguchi method, the catalyst concentration played the most important role in the yield of rapeseed methyl ester. Finally, the yield of rapeseed methyl ester was improved to 96.7% with the by optimal conditions of the control parameters which were obtained by Taguchi method.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.852-857
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• 2004

A new and efficient method for estimating the statistical moments of a system performance function has been developed. The method consists of two steps: (1) An approximate response surface is generated by a quadratic regression model, and (2) the statistical moments of the regression model are then calculated by experimental design techniques proposed by Seo and $Kwak^{(4)}$. In this approach, the size of experimental region affects the accuracy of the statistical moments. Therefore, the region size should be selected suitably. The D-optimal design and the central composite design are adopted over the selected experimental region for the regression model. Finally, the Pearson system is adopted to decide the distribution type of the system performance function and to analyze structural reliability.

• Journal of the Korea Society for Simulation
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• v.11 no.3
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• pp.1-12
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• 2002

Experimental design in simulation provides an efficient way of economizing simulation runs since a considerable number of simulation runs that originally were planned can be reduced by this approach. This experimental design method is an active area of research together with the output analysis and so no single panacea seems to exist so far. Thus, selection of techniques of experimental design and output analysis more likely depends upon the objective of simulation analysis, budget constraint and sometimes the analyst's subjective judgment. This paper attempts to describe an experimental design methodology for port investment analysis using a case study in a bulk terminal in Korea. Detailed display will be focused on simulation period, warm-up period, the number of replications needed in production runs after brief explanation on the system configuration.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.327-332
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• 2001

An experimental design technique is developed for estimating the moments of system response functions. It is easy to implement and provides accurate results compared with other traditional methods. It is based on the work of Taguchi, later improved by D'Errico and Zaino. The existing experimental techniques, however, is applicable only for normally distributed cases. In this article the three-level Taguchi method is extended to obtain optimum choice for levels and weights to handle nonnormal distributions. A systematic procedure for reliability analysis is then proposed by using the Pearson system and the narrow system reliability bounds. Illustrative examples including a tolerance optimization problem are shown very accurate comparing with those by Monte-Carlo simulations and the first-order reliability method.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1111-1113
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• 2005

This paper deals with optimal design technique to reduce torque of IPM BLDC motor having concentrated winding. Optimization process using experimental design method which is one of the design technique is explained. Finally, the validity of experimental design method is proved by the results between prototype and optimization model.

• Structural Engineering and Mechanics
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• v.27 no.6
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• pp.741-771
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• 2007

Tests were conducted on two partially pre-stressed concrete solid beams subjected to combined loading of bending, shear and torsion. The beams were designed using the Direct Design Method which is based on the Lower Bound Theorem of the Theory of Plasticity. Both beams were of $300{\times}300mm$ cross-section and 3.8 m length. The two main variables studied were the ratio of the maximum shear stress due to the twisting moment, to the shear stress arising from the shear force, which was varied between 0.69 and 3.04, and the ratio of the maximum twisting moment to the maximum bending moment which was varied between 0.26 and 1.19. The required reinforcement from the Direct Design Method was compared with requirements from the ACI and the BSI codes. It was found that, in the case of bending dominance, the required longitudinal reinforcements from all methods were close to each other while the BSI required much larger transverse reinforcement. In the case of torsion dominance, the BSI method required much larger longitudinal and transverse reinforcement than the both the ACI and the DDM methods. The difference in the transverse reinforcement is more pronounce. Experimental investigation showed good agreement between design and experimental failure loads of the beams designed using the Direct Design Method. Both beams failed within an acceptable range of the design loads and underwent ductile behaviour up to failure. The results indicate that the Direct Design Method can be successfully used to design partially prestressed concrete solid beams which cater for the combined effect of bending, shear and torsion loads.

• IE interfaces
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• v.23 no.2
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• pp.118-125
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• 2010

The determination of a regression model is important in using statistical designs of experiments. Generally, the exact regression model is not known, and experimenters suppose that a certain model form will be fit. Then an experimental design suitable for that predetermined model form is selected and the experiment is conducted. However, the initially chosen regression model may not be correct, and this can result in undesirable statistical properties. We develop model-robust experimental designs that have stable prediction variance for a family of candidate regression models over a cuboidal region by using genetic algorithms and the desirability function method. We then compare the stability of prediction variance of model-robust experimental designs with those of the 3-level face centered cube. These model-robust experimental designs have moderately high G-efficiencies for all candidate models that the experimenter may potentially wish to fit, and outperform the cuboidal design for the second-order model. The G-efficiencies are provided for the model-robust experimental designs and the face centered cube.