• 유공압시스템학회논문집
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• 제2권4호
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• pp.1-6
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• 2005

This paper presents optimization of a pneumatic control system whose design parameters have been optimized so that the desired dynamic characteristics of cylinder position was obtained. The pneumatic system is used as transferring and stacking equipment for solid freeform fabrication system which has been widely used in design verification applications. The pneumatic system mainly consists of pneumatic control valves and cylinders. The system was modeled by using several principles for pneumatic components. The system was optimized to obtain dynamic performance with enough damping to reduce cylinder vibration. A fuzzy controller has been applied to fulfill the dynamic performance requirements of the pneumatic system. The simulation results show that the fuzzy controller is more effective than a PD controller.

• 한국유체기계학회 논문집
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• 제15권3호
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• pp.39-45
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• 2012

In this study, optimization of the impeller and design of volute were carried out in order to improve the performance of a centrifugal pump. Design parameters from vane plane development for impeller design were selected, and effect of the design parameters on the performance of the pump was analyzed by using Response Surface Methodology(RSM) to optimized impeller. In addition, total pump design method was suggested by designing volute which was suitable for the optimized impeller through volute design where Stepanoff theory was applied and numerical analysis.

• 대한기계학회논문집A
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• 제26권8호
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• pp.1719-1726
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• 2002

Design variables and design parameters are rarely deterministic in practice. Robust optimal design takes into consideration of the uncertainties in the design variables and parameters. Robust optimization methodology with probability constraints requires a lot of system analyses fer calculating failure probability of each constraint. By introducing an envelope function to reduce the number of constraints, efficiency of robust optimization techniques can be considerably improved. Through four illustrative examples, it is shown that the number of system analyses is greatly decreased while little differences in the optimum results are observed.

• Industrial Engineering and Management Systems
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• 제10권2호
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• pp.128-133
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• 2011

This paper presents a study on product design optimization to reduce the environmental impact of machining. The objective is to analyze the effect of changing the product design parameters such as its dimensions, and basic features on the environmental impact of machining process in terms of its energy consumption, waste produced and the chemicals and other consumables used up during the process. To realize this objective, we used a CAD model of a product with different design scenarios, and analyze their energy consumption using an environmental impact calculator method developed. The waste produced, and the consumables used up, such as lubricants and coolants were analyzed using environmental emission factors. Optimization methods using Genetic Algorithm and Goal Programming are applied to the product design parameters in order to get the best possible product dimensions with the least environmental impact of the machining process.

• 한국정밀공학회지
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• 제16권1호통권94호
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• pp.116-124
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• 1999

In most conventional design optimization of dynamic system, design sensitivities are utilized. However, design sensitivities based optimization method has numbers of drawback. First, computing design sensitivities for dynamic system is mathematically difficult, and almost impossible for many complex problems as well. Second, local optimum is obtained. On the other hand, Genetic Algorithm is the search technique based on the performance of system, not on the design sensitivities. It is the search algorithm based on the mechanics of natural selection and natural genetics. GA search, differing from conventional search techniques, starts with an initial set of random solutions called a population. Each individual in the population is called a chromosome, representing a solution to the problem at hand. The chromosomes evolve through successive iterations, called generations. As the generation is repeated, the fitness values of chromosomes were maximized, and design parameters converge to the optimal. In this study, Genetic Algorithm is applied to the actual dynamic optimization problems, to determine the optimal design parameters of the dynamic system.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2016년도 춘계학술대회
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• pp.305-307
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• 2016

The purpose of this paper is to determine the optimal values of the gain parameters used in the tracking module for a highly dynamic warship. The algorithm of the tracking module uses the ${\alpha}-{\beta}-{\gamma}$ filter to compute accurate estimates and update the state variables, that is, positions, velocity and acceleration. The filtering coefficients ${\alpha}$, ${\beta}$ and ${\gamma}$ are determined from set values of the damping parameter, ${\xi}$. Optimization is achieved by plotting a range of the damping parameter ${\xi}$ against the corresponding residual error and then selecting the best value of ${\xi}$ with the minimum residual error. Optimal values of the smoothing coefficients are subsequently computed from the selected damping parameter, ${\xi}$.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.1350-1354
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• 2007

As the importance of low power design is emphasized, power consumption became one of the standards that represent the performance of the system. The purpose of this study is to decide design variable that minimize power consumption for the oxygen concentrator in two bed-one compressor 8 step PSA process that has above 90% purity at 3lpm by using given constants and selected parameters. Setting selected parameters as cycle time and equalization time, optimization for PSA process in the oxygen concentrator is progressed. For this, we need to know the features and basic principals of PSA process and to deduce objective function of performance analysis. Validations for objective function and lots of experiments are needed too. By using the characteristic curve of the compressor and the pressure curve of the process for 1 cycle, objective function was set. After theoretical 2 dimensional optimized paths was obtained. And then, by experiment, theoretical optimized path was verified.

• Food Science and Biotechnology
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• 제18권4호
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• pp.867-871
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• 2009

Response surface methodology (RSM) was used for the optimization of antioxidant capacity in gardenia extracts. The antioxidant capacities of gardenia fruit extracts were investigated by ferric reducing ability (FRA) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging activity (RSA) assays. The optimum extraction parameters for the strongest antioxidant capacity were the ethanol concentration (EtOH) of 48.9%, extraction temperature of $72.9^{\circ}C$, and extraction time of 29.9 min. Analysis of variance (ANOVA) showed that the quadratics of EtOH and extraction temperature had highly significant effect on the antioxidant capacity (p<0.001). The antioxidant capacity was correlated with contents of bioactive components [crocin, geniposide, and total phenolic (TP) compounds] in gardenia extracts and mainly attributed to the content of the TP compounds.

• Smart Structures and Systems
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• 제12권6호
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• pp.641-659
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• 2013

In this paper is studied the influence of the uncertain mass distribution over the floors on the choice of the optimal parameters of a hybrid control system for tall buildings subjected to wind load. In particular, an optimization procedure is developed for the robust design of a hybrid control system that is based on an enhanced Monte Carlo simulation technique and the genetic algorithm. The large computational effort inherent in the use of a MC-based procedure is reduced by the employment of the Latin Hypercube Sampling. With reference to a tall building modeled as a multi degrees of freedom system, several numerical analyses are carried out varying the parameters influencing the floors' masses, like the coefficient of variation of the distribution and the correlation between the floors' masses. The procedure allows to obtain optimal designs of the control system that are robust with respect to the uncertainties on the distribution of the dead and live loads.

• 유공압시스템학회논문집
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• 제7권1호
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• pp.11-19
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• 2010

A gas-assisted hydraulic breaker uses both hydraulic and pneumatic energies and the appropriate balance between them mostly effects its performance. Mathematical modeling of the breaker is established and verified by experiment. Through sensitivity analysis using AMESim, the key design parameters are selected, which mostly affect the performance of the breaker. Taguchi method is used to optimize the key design parameters to maximize the output power for long and short strokes through simulation. As the result, the output power as well as the impact energy are increased significantly compared with the existing design. The pressure pulsation in the supply line is reduced to a tolerable level and the dynamic characteristics of the piston displacement is also improved by the optimization.