• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.39 no.5
• /
• pp.535-541
• /
• 2015

In this study, an approximate multi-objective optimization of a wall-mounted monitor bracket arm was performed. The rotation angle of the bracket arm was determined considering the inplane degree of freedom. We then formulated an optimization problem on maximum stress and deflection. Analyses of mean and design parameters were conducted for sensitivity regarding performance with orthogonal array and response surface method (RSM). RSM models of objective and constraint functions were generated using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by non-dominant sorting genetic algorithm (NSGA-II) were validated through the finite element analysis and we compared the obtained optimal solution by CCD and D-optimal design.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.4 s.175
• /
• pp.894-900
• /
• 2000

Optimization of chassis frame is performed according to the minimization of eleven responses representing one total frame weight, three natural frequencies and seven strength limits of chassis frame that are analyzed by using each response surface model from D-optimal design of experiments. After each response surface model is constructed form D-optimal design and random orthogonal array, the main effect and sensitivity analyses are successfully carried out by using this approximated regression model and the optimal solutions are obtained by using a nonlinear programming method. The response surface models and the optimization algorithms are used together to obtain the optimal design of chassis frame. The eleven-polynomial response surface models of the thirteen frame members (design factors) are constructed by using D-optimal Design and the multi-disciplinary design optimization is also performed by applying dual response analysis.

• Journal of the Korean Society for Precision Engineering
• /
• v.32 no.9
• /
• pp.815-824
• /
• 2015

In this study, we conducted the approximate multi-objective optimization of gap sizes of pressurized-water reactor (PWR) annular fuels. To determine the contacting tendency of the inner-outer gaps between the annular fuel pellets and cladding, thermoelastic-plastic-creep (TEPC)analysis of PWR annular fuels was performed, using in-house FE code. For the efficient heat transfer at certain levels of stress, we investigated the tensile, compressive hoop stress and temperature, and optimized the gap sizes using the non-dominant sorting genetic algorithm (NSGA-II). For this, response surface models of objective and constraint functions were generated, using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by NSGA-II were verified through the TEPC analysis, and we compared the obtained optimum solutions and generated errors from the CCD and D-optimal design. We observed that optimum solutions differ, according to design of experiments (DOE) method.

• Water for future
• /
• v.14 no.2
• /
• pp.63-69
• /
• 1981

This Study is aimed at optimal sequencing of water supply projects for water demand from the application in water resources field of dynamic programming because a minimum present cost strategy for investment in water supply projects plays an important part of installation of some projects. In analysis, the relationships of the future water demand and numerous possible independent projects that are expected to meet water requirements up to some future data in Daegu city were used and future water demand were estimated from the exponential function method, the method used by the Water Works Bureau of Daegu City government which is a kind of geometric progression method and the mean value of these two methods. The results showed that the optimal sequencing of water supply projects using Dynamic Programming was reasonable and the changing of the estimation method of future water demand made a difference among optimal sequence of projects while the changing of annual rate of interest had influenced on present value cost only. In general, the best sequence for constructing the seven projects was the order of D-E-G-F-C-B-A, with the corresponding period for 33-38 years.

• The Korean Journal of Applied Statistics
• /
• v.4 no.2
• /
• pp.195-207
• /
• 1991

We consider the development of simple regression-like diagnostics for assessing the sensitivity of an optimal design to deviations from the assumptions of constant error variance. This contains a review of Cook's local influence approach and an application of local influence aproach to D-optimal experimental design. The method is applied in a number of simple examples in Section 3. Conclusions and directions for further research follow in Section 4.

• The Korean Journal of Applied Statistics
• /
• v.13 no.2
• /
• pp.393-405
• /
• 2000

Box and Draper( 19(5) listed some properties of a design that should be considered in design selection. But it is impossible that one design criterion from optimal experimental design theory reflects many potential objectives of an experiment, because the theory was originally based on the underlying model and its strict assumption about the error structure. Therefore, when it is neces::;ary to implement multi-objective experimental design. it is common practice to balance out the several optimal design criteria so that each design criterion involved benefits in terms of its relative "high" efficiency. In this study, we proposed several composite design criteria taking the case of heteroscedastic model. WVhen the heteroscedasticity is present in the model. the well known equivalence theorem between 1)- and C-optimality no longer exists and furthermore their design characteristics are sometimes drastically different. We introduced three different design criteria for this purpose: constrained design, combined design, and minimax design criteria. While the first two methods do reflect the prior belief of experimenter, the last one does not take it into account. which is sometimes desirable. Also we extended this method to the case when there are uncertainties concerning the error structure in the model. A simple algorithm and concluslOn follow.On follow.

• The Korean Journal of Applied Statistics
• /
• v.6 no.2
• /
• pp.303-309
• /
• 1993

In this paper we have defined two approaches to be error-robust when the precise form of error-structure is unknown. An experiment is optimal by the first criterion if it maximizes the minimum effciency over all candidates of error structure and is optimal by the second if it maximizes the minimum average of the efficiency over all candidates of error structure. In order to appreciate the basic implications of each design criterion, these approaches are applied to two different experimental situations, D- and heteroscedastic G-optimalities.

• Proceedings of the KSME Conference
• /
• 2005.11a
• /
• pp.137.2-137.2
• /
• 2005

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.35 no.9
• /
• pp.1007-1013
• /
• 2011

Because of their high flexibility and durability, multilayer bellows are manufactured for use in commercial vehicles, while single-layer bellows are manufactured for use in passenger vehicles. A study based on the finite element method (FEM) and shape optimization for the single-layer bellows has been actively performed; however, until now, a study based on the FEM has rarely been performed for the multilayer bellows with gaps between the layers. This paper presents a finite-element modeling scheme for the multilayer bellows to improve simulation reliability during the evaluation of stress and flexibility. For performing shape optimization for the multilayer bellows, DOE (design of experiment) and the Kriging metamodel followed by the D-optimal method are used.