• Journal of computational fluids engineering
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• v.11 no.2 s.33
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• pp.19-24
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• 2006

A research to evaluate the efficiency of design optimization was carried out for aerodynamic design optimization problem in distributed computing environment. The aerodynamic analyses which take most of computational work during design optimization were divided into several jobs and allocated to associated PC clients through network. This is not a parallel process based on domain decomposition in a single analysis rather than a simultaneous distributed-analyses using network-distributed computers. GBOM(gradient-based optimization method), SAO(Sequential Approximate Optimization) and RSM(Response Surface Method) were implemented to perform design optimization of transonic airfoils and evaluate their efficiencies. dimensional minimization followed by direction search involved in the GBOM was found an obstacle against improving efficiency of the design process in the present distributed computing system. The SAO was found fairly suitable for the distributed computing environment even it has a handicap of local search. The RSM is apparently the most efficient algorithm in the present distributed computing environment, but additional trial and error works needed to enhance the reliability of the approximation model deteriorate its efficiency from the practical point of view.

• Journal of the Korean Society of Food Culture
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• v.26 no.6
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• pp.717-726
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• 2011

Response surface methodology (RSM) was performed in order to determine the optimal mixing conditions of different amounts of egg and sugar for the preparation of soybean pudding. The experiments were designed according to a central composite design by designating whole egg and sugar content as independent variables. Meanwhile, sweetness, Commission Internationale de I'Eclairage (CIE) color parameters (L*, a* and b* values), hardness, cohesiveness, springiness, and gumminess were response variables. Overall optimization, conducted by overlaying the contour plots under investigation, was able to determine the optimal range of dependent variables within which the 14 responses were simultaneously optimized. The point chosen as a representative of this optimal region corresponded to 50.00 g of whole egg and 31.66 g of sugar. Under these conditions, the model predicted L* value=80.03, a* value=-5.44, b* value=27.86, sweetness=21.23 ($^{\circ}Brix$), hardness=$25.45{\times}10^5$ (dyne/$cm^2$), cohesiveness=67.90 (%), springiness=46.20 (%), and gumminess=12.71 (g).

• The KSFM Journal of Fluid Machinery
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• v.18 no.4
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• pp.43-48
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• 2015

In this study, a method for optimal design of impeller shroud for centrifugal compressor using response surface method (RSM) and multi-objective genetic algorithm (MOGA) was studied. Numerical simulation was conducted using ANSYS CFX with various configurations of shroud. Each of the design parameters was divided into 3 levels. Total 15 design points were planned by central composite design (CCD) method, which is one of the design of experiment (DOE) techniques. Response surfaces based on the results of DOE were used to find the optimal shape of impeller shroud for high aerodynamic performance. The whole process of optimization was conducted using ANSYS Design Xplorer (DX). Results showed that the isentropic efficiency, which is the main performance parameter of the centrifugal compressor, was increased 0.4% through the optimization.

• The KSFM Journal of Fluid Machinery
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• v.7 no.3 s.24
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• pp.32-38
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• 2004

Shape of a multi-blades centrifugal fan is optimized by response surface method based on three-dimensional Navier-Stokes analysis. For numerical analysis, Reynolds-averaged Navier-Stokes equations with standard $k-{epsilon}$ turbulence model are transformed into non-orthogonal curvilinear coordinate system, and are discretized with finite volume approximations. Due to the large number of blades in this centrifugal fan, the flow inside of the fan is regarded as steady flow by introducing the impeller force models for economic calculations. Optimizations with and without constraints are carried out. Design variables, location of cur off, radius of cut off, expansion angle of scroll and width of impeller were selected to optimize the shapes of scroll and blades. Data points for response evaluations were selected by D-optimal design, and linear programming method was used for the optimization on the response surface. As a main result of the optimization, the efficiency was successfully improved. The correlation of efficiency with relative size of inactive zone at the exit of impeller is discussed as well as with average momentum fluxes in the scroll.

• Korean Journal of Computational Design and Engineering
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• v.5 no.2
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• pp.127-135
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• 2000

Emergent computing paradigms such as genetic algorithms have found increased use in problems in engineering design. These computational tools have been shown to be applicable in the solution of generically difficult design optimization problems characterized by nonconvexities in the design space and the presence of discrete and integer design variables. Another aspect of these computational paradigms that have been lumped under the bread subject category of soft computing, is the domain of artificial intelligence, knowledge-based expert system, and machine learning. The paper explores a machine learning paradigm referred to as teaming classifier systems to construct the high-quality global function approximations between the design variables and a response function for subsequent use in design optimization. A classifier system is a machine teaming system which learns syntactically simple string rules, called classifiers for guiding the system's performance in an arbitrary environment. The capability of a learning classifier system facilitates the adaptive selection of the optimal number of training data according to the noise and multimodality in the design space of interest. The present study used the polynomial based response surface as global function approximation tools and showed its effectiveness in the improvement on the approximation performance.

• 유체기계공업학회:학술대회논문집
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• 2003.12a
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• pp.385-390
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• 2003

Shape of a multi-blades centrifugal fan is optimized by response surface method based on three-dimensional Navier-Stokes analysis. For numerical analysis, Reynolds-averaged Wavier-Stokes equations with standard $k-{\varepsilon}$ turbulence model are transformed into non-orthogonal curvilinear coordinate system, and are discretized with finite volume approximations. Due to the large number of blades in this centrifugal fan, the flow inside of the fan is regarded as steady flow by introducing the impeller force models for economic calculations. Optimizations with and without constraints are carried out. Design variables, location of cur off, radius of cut off, expansion angle of scroll and width of impeller were selected to optimize the shapes of scroll and blades. Data points for response evaluations were selected by D-optimal design, and linear programming method was used for the optimization on the response surface. As a main result of the optimization, the efficiency was successfully improved. The correlation of efficiency with relative size of inactive zone at the exit of impeller is discussed as well as with average momentum fluxes in the scroll.

• Environmental Engineering Research
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• v.23 no.3
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• pp.309-315
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• 2018

Chlortetracycline (CTC) is one of the most important compounds in antibiotic production, and its distribution has been widely investigated due to health and ecological concerns. This study presents systematic approach to optimize the high-performance liquid chromatography-tandem mass spectrometry for analyzing CTC in a multiple reaction monitoring mode ($479{\rightarrow}462m/z$). One-factor-at-a-time (OFAT) test with response surface analysis (RSA) was used as optimization strategy. In OFAT tests, the fragmentor voltage, collision energy, and ratio of acetonitrile in the mobile phase were selected as major factors for RSA. The experimental conditions were determined using a composite in cube design (CCD) to maximize the peak area. As a result, the partial cubic model precisely predicted the peak area response with high statistical significance. In the model, the (solvent composition) and (collision $energy^2$) terms were statistically significant at the 0.1 ${\alpha}$-level, while the two-way interactions of the independent variables were negligible. By analyzing the model equation, the optimum conditions were derived as 114.9 V, 15.7 eV, and 70.9% for the fragmentor voltage, collision energy, and solvent composition, respectively. The RSA, coupled with the CCD, offered a comprehensive understanding of the peak area that responds to changes in experimental conditions.

• Microbiology and Biotechnology Letters
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• v.51 no.1
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• pp.69-82
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• 2023

Nitrilases are a hydrolase group of enzymes that catalyzes nitrile compounds and produce industrially important organic acids. The current objective is to optimize nitrilase production using statistical methods assisted with artificial intelligence (AI) tool from novel nitrile degrading isolate. A nitrile hydrolyzing bacteria Bacillus subtilis AGAB-2 (GenBank Ascension number- MW857547) was isolated from industrial effluent waste through an enrichment culture technique. The culture conditions were optimized by creating an orthogonal design with 7 variables to investigate the effect of the significant factors on nitrilase activity. On the basis of obtained data, an AI-driven support vector machine was used for the fitted regression, which yielded new sets of predicted responses with zero mean error and reduced root mean square error. The results of the above global optimization were regarded as the theoretical optimal function conditions. Nitrilase activity of 9832 ± 15.3 U/ml was obtained under optimized conditions, which is a 5.3-fold increase in compared to unoptimized (1822 ± 18.42 U/ml). The statistical optimization method involving Plackett Burman Design and Response surface methodology in combination with an AI tool created a better response prediction model with a significant improvement in enzyme production.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.437-442
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• 2004

The optimization of a blade sweep for a transonic axial compressor rotor (NASA rotor 37) has been performed using a response surface method and a Reynolds-averaged Wavier-Stokes (RANS) flow simulation. Two shape variables of the rotor blade, which are used to define a blade sweep, are introduced to increase an adiabatic efficiency. Data points for response evaluations have been selected by D-optimal design, and linear programming method has been used for an optimization on a response surface. The result shows that the adiabatic efficiency is increased to about 1 percent compared to that of the reference shape of the rotor blade. Relatively high increasement of the adiabatic efficiency is obtained between 20 and 60 percent span. In the present study, backward swept blade is more effective to increase the adiabatic efficiency In the axial compressor rotor.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.972-975
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• 2004

In order to reduce the noise of BLDC motor, a systematic optimization procedure for rotor structure is presented. The noise index is defined as the sum of volume velocity of FE-model that are calculated at the dominant frequencies during dehydration process, which is based on the principle of radiation simple volume source. Then, the five design variables are selected to represent the shape and layout or rotor structure. This discrete design optimization problem for minimizing the noise index is solved by 3-level orthogonal array based effect analysis. Finally, the response surface method (RSM) combined optimization approach is employed for more refining the approximate optimum.