• Transactions of the Korean hydrogen and new energy society
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• v.24 no.1
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• pp.50-60
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• 2013

High temperature proton exchange membrane fuel cells (PEMFCs) using phosphoric acid (PA) doped polybenzimidazole (PBI) membranes have been concentrated as one of solutions to the limits with traditional low temperature PEMFCs. However, the amount of reported experimental data is not enough to catch the operational characteristics correlated with cell performance and durability. In this study, design of experiments (DOE) based operational optimization method for high temperature PEMFCs has been proposed. Response surface method (RSM) is very useful to effectively analyze target system's characteristics and to optimize operating conditions for a short time. Thus RSM using central composite design (CCD) as one of methodologies for design of experiments (DOE) was adopted. For this work, the statistic models which predict the performance and degradation rate with respect to the operating conditions have been developed. The developed performance and degradation models exhibit a good agreement with experimental data. Compared to the existing arbitrary operation, the expected cell lifetime and average cell performance during whole operation could be improved by optimizing operating conditions. Furthermore, the proposed optimization method could find different new optimal solutions for operating conditions if the target lifetime of the fuel cell system is changed. It is expected that the proposed method is very useful to find optimal operating conditions and enhance performance and durability for many other types of fuel cell systems.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.4
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• pp.120-127
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• 2009

Spindle units of machine tool are very important part in the manufacturing area. Recently high speed machining has become the main issue of metal cutting. To develop high speed machine tools, a lot of studies have been carried out for high speed spindle. Due to increase of the rotational speed of the spindle, there has been renewal of interest in vibration of spindle. This paper concerns the improvement of spindle design using design of experiments. To improve the design of critical speed and weight of spindle, the experiments using central composite method have been carried out. The targets are critical speed and weight of spindle. For optimization of critical speed and weight and optimization of only critical speed by operation of all area search through response optimizer, the result of analysis has improved design of each factor. Finite element analyses are performed by using the commercial codes ARMD, CATIA V5 and ANSYS workbench. From the results, it has been shown that the proposed method is effective for modification of spindle design to improve critical speed and weight.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.5
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• pp.575-582
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• 2011

A cleaning blade is an attachment installed in the toner cartridge of a laser printer for removing the residual toner from an organic photo-conductive drum. There have been many studies on the performance and life of the rubber blade. We focus on optimally designing the blade shape parameters to minimize the maximum stress of the blade while satisfying design constraints on the cleaning performance and part interference. The blade is optimally designed using a design of experiments, meta-models and an optimization algorithm implemented in PIAnO (process integration, automation, and optimization), a commercial PIDO (process integration and design optimization) tool. We integrate the CAE tools necessary for the structural analysis of the cleaning blade, automate the analysis procedure, and optimize the solution using PIAnO. We decreased the maximum stress by 32.6% in comparison with that of the initial design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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• pp.1097-1103
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• 2010

Injection pressure, an important factor in the filling procedure, should be minimized to enhance injection molding quality. In addition, warping deformation and weld lines, which are representative failures, should be avoided to enhance injection molding quality. To improve injection molding quality, the design procedure for an automotive fog blank cover is divided into two stages. In the first stage, we optimally obtain injection molding process variables that minimize injection pressure and warping deformation by using design of experiments, approximation and optimization techniques equipped in PIAnO (Process Integration, Automation and Optimization), a commercial PIDO (Process Integration and Design Optimization) tool. Then, we determine the thickness of the automotive fog blank cover that enables us to avoid generating weld lines. The design results we obtain in this study are found far better than those of the initial design, which demonstrates the effectiveness of our design method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.2
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• pp.223-233
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• 2011

A design optimization problem was formulated to minimize the volume of an RC building structure while satisfying design constraints on structural displacements under vertical, wind and seismic loads. We employed metamodel-based design optimization using design of experiments, metamodeling and optimization algorithm to circumvent the difficulty of the automation of structural analysis procedure. Especially, we proposed a design approach of repetitive design optimizations by stages with changing the side constraint values on design variables and limit values on design constraints until a satisfactory design result was obtained. Using the proposed design approach, the volume of the RC building structure has been reduced by 53.3 % compared to the initial one while satisfying all the design constraints. This design result clearly shows the validity of the proposed design approach.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2125-2138
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• 2023

The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1243-1252
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• 2005

A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.3
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• pp.339-348
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• 2001

More often a commercial package for the structural analysis is necessary in the structural optimum design. In this case the task of combining the package with an optimization program must be required, hut it is not so simple because interchanging some data between them is difficult. Sequential approximate optimization is currently used as a natural way to overcome the hard task. If sequential approximate optimization has wide side constraints that the lower limit of design variables is very small and their upper limit is very large, it is not so easy to obtain approximated functions accurately for the whole design domain. This paper proposes a sequential design domain method, which is very useful to carry out sequential approximate optimization in this case. In this paper, the response surface methodology is used to obtain approximated functions and the orthogonal array is used for design of experiments. The sequential approximate optimization of 3-bar and 10-bar trusses is demonstrated to verify the reliability of the sequential design domain method.

• Journal of Plant Biotechnology
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• v.2 no.3
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• pp.157-163
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• 2000

Optimization of chemicals in the large scale sea water medium and inoculum for biomass and natural colourants production in the marine cyanobacteria, Phomidium tenue BDU 46241 (phycoerythrin producer) and P.valderianum BDU 30501 (phycocyanin producer) was carried out by experiments in L8 orthogonal array. Mathematical analysis revealed the significance of these factors. The factor(s) that critically control the yield varied with the organism and the end-product further, the desirable level of these factors between the normal and a higher level tested was identified and improved media were evolved. In both cyanobacteria, higher level of $K_2$$HPO_4$, $NaNO_3$ and inoculum with normal level of ferric ammonium citrate was found to be desirable for biomass production and additionally, higher level of $MgSO_4$ for pigment production. The level of other factors varied with the organism and the end-product. Confirmation experiments showed that the clues obtained based on mathematical experimentation are valid. In P.tenue, the medium optimized for biomass production increased the yield of biomass by 495% and the medium optimized for phycoerythrin production increased the yield of biomass by 408% with 30% increase in phycoerythrin content of the biomass. Similarly in P.valderianum, the medium optimized for biomass production increased the yield of biomass by 224% and the medium optimized for phycocyanin production increased the yield of biomass by 143% with 44% increase in phycocyanin content of the biomass.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.125-136
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• 2008

In many practical engineering design problems, the form of objective functions is not given explicitly in terms of design variables. Given the value of design variables, under this circumstance, the value of objective functions is obtained by real/computational experiments such as structural analysis, fluid mechanic analysis, thermodynamic analysis, and so on. These experiments are, in general, considerably expensive. In order to make the number of these experiments as few as possible, optimization is performed in parallel with predicting the form of objective functions. Response Surface Methods (RSM) are well known along this approach. This paper suggests to apply Support Vector Machines (SVM) for predicting the objective functions. One of most important tasks in this approach is to allocate sample data moderately in order to make the number of experiments as small as possible. It will be shown that the information of support vector can be used effectively to this aim. The effectiveness of our suggested method will be shown through numerical example which is well known in design of engineering.