• Advances in aircraft and spacecraft science
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• v.4 no.6
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• pp.701-709
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• 2017

One of the components that used in the satellite thermal control subsystem is the Mechanically Pumped Fluid Loop (MPFL) system; this system mostly used in geosynchronous orbit (GEO) satellites, and can transfer heat from a hot point to a cold point using the fluid which circulated in a closed loop. Heat radiates to the deep space at the cold plate to cool down the fluid temperature. In this research, the radiative heatexchanger (RHX) for a MPFL system is optimized. The genetic algorithm has been used for minimizing the total mass and pressure drop by considering a constant transferred heat rate at the heat exchanger. The optimization has been done in two cases. In case I, two parameters are considered as a goal function, so optimization is performed using NSGA-II method. Results of optimization are shown in the pareto diagram. In case II, the diameter of pipe is considered constant, so the optimized value for distances of the parallel pipes is obtained by using the genetic algorithm, in which the system has the least total mass. Results show that in the RHX, by increasing the pipe diameter, pressure drop decreases and total mass increases. Also by considering a constant value for pipe diameter, an optimum distance between pipes and pipe length are obtained in which the system has a minimum mass.

• Food Science and Biotechnology
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• v.17 no.5
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• pp.904-911
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• 2008

Covalent cross-links between a number of proteins and peptides explain why transglutaminase may be widely used by food processing industries. The objective of this work was optimization of the fermentation process to produce transglutaminase from a new microbial source, the Streptomyces sp. P20. The strategy adopted to modify the usual literature media was: (1) fractional factorial design (FFD) to elucidate the key medium ingredients, (2) central composite design (CCD) to optimise the concentration of the key components. Optimization of the medium resulted in not only an 86% increase in microbial transglutaminase activity as compared to the media cited in the literature, but also a reduction in the production cost. Optimal fermentation conditions - namely temperature and agitation rate - were also studied, using CCD methodology. Usual conditions of $30^{\circ}C$ and 100 rpm were within the optimal area. All other parameters for enzyme production were experimentally proven to be optimum fermentation conditions.

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.34-39
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• 2017

Vapor-liquid equilibrium calculation is required to properly design and operation of distillation process. The general calculation method is to use binary interaction parameter. Lower flash points of cyclohexanol+aniline and cyclohexanol+cyclohexanone were measured by using Seta-flash closed cup apparatus. The measured flash points were compared with those calculated by the method based on Raoult's law and the optimization method using Wilson equation. The absolute average errors(A.A.E.) of the results calculated by Raout's law are $0.25^{\circ}C$ and $1.07^{\circ}C$ for cyclohexanol+aniline and cyclohexanol+cyclohexanone, respectively. The absolute average errors of the results calculated by the optimization method are $0.22^{\circ}C$ and $0.65^{\circ}C$ for cyclohexanol+aniline and cyclohexanol+cyclohexanone, respectively. As can be seen from A.A.E., the calculated values based on the optimization method were found to be better than those based on the Raoult's law. The binary interaction parameters calculated by the optimization method are used to predict the dew points of cyclohexanol+aniline and cyclohexanol+cyclohexanone. The A.A.E. for these mixtures show that there is an acceptable agreement between experimental and calculated dew poins.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.144-151
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• 2003

In this paper, an optimum design problem for endosseous implant in dentistry is studied to find best implant design. An optimum design problem is formulated to reduce stresses arising at the cortical as well as cancellous bones, in which sufficient design parameters are chosen fur design definition that encompasses major implants in popular use. Optimization at once (OAO) with the large number of design variables, however, causes too costly solution or even failure to converge. A concept of multilevel optimization (MLO) is employed to this end, which is to group the design variables of similar nature, solve the sub-problem of smaller size fur each group in sequence, and this is iterated until convergence. Each sub-problem is solved based on the response surface method (RSM) due to its efficiency for small sized problem. Favorable solution is obtained by the MLO, which is compared to both solutions made by RSM and sequential quadratic programming (SQP) in the OAO problem.

• Journal of Microbiology and Biotechnology
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• v.8 no.1
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• pp.81-88
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• 1998

The determination of appropriate parameters and parameter conditions is very important for the optimization of production of target materials. Taguchi's method has been used widely as the basis for development trials and optimization during industrial process design. Reaction variables which influence product yield are easily determined and their effects are revealed by just a few reactions, negating the need for extensive experimental investigation. There are usually some factors that are responsible for variations in process characteristics, so called noise factors. Controlling noise factors is very costly and difficult or impossible. Taguchi's experimental design method was examined to determine the control factor's level that is less sensitive to the changes in environmental conditions and other noise factors without control of noise factors. In this study, optimization of lipase-catalyzed production of lysophosphatidic acid (LPA) which has various physiological functions was performed by Taguchi's method. We obtained LPA yields ($66.5\%$) with low variance (5.32) at 400 RPM, molar ratio of 40 : 3 (mol) (fatty acid: G-3-P), 48 h, and $50^{\circ}C$. Thus, bioactive LPA with a desired fatty acid moiety could be produced with high yields and low variance despite various environmental noise factors.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.198-200
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• 2006

This paper presents a development of an educational simulator of particle swarm optimization (PSO) and application for solving the test functions and economic dispatch (ED) problems with nonsmooth cost functions. A particle swarm optimization is one of the most powerful methods for solving global optimization problems. It is a population-based search algorithm and searches in parallel using a group of particles similar to other AI-based heuristic optimization techniques. In developed simulator, lecturers and students can select the functions for simulation and set the parameters that have an influence on PSO performance. To improve searching capability for ED problems, a crossover operation is proposed to the position update of each individual (CR-PSO). To verify the feasibility of CR-PSO method, numerical studies have been performed for two different sample systems. The proposed CR-PSO method outperforms other algorithms in solving ED problems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.12
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• pp.3053-3060
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• 2000

Alternative formulation is presented for robust optimization problems and an efficient computational scheme for reliability estimation is proposed. Both design variables and design parameters considered as random variables about their nominal values. To ensure the robustness of objective performance a new cost function bounding the performance and a new constraint limiting the performance variation are introduced. The constraint variations are regulated by considering the probability of feasibility. Each probability constraint is transformed into a sub-optimization problem and then is resolved with the modified advanced first order second moment(AFOSM) method for computational efficiency. The proposed robust optimization method has advantages that the mean value and the variation of the performance function are controlled simultaneously and the second order sensitivity information is not required even in case of gradient based optimization. The suggested method is examined by solving three examples and the results are compared with those for deterministic case and those available in literature.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.1
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• pp.138-145
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• 2009

High-efficiency and high-quality machining has become a fact of life for numerous machine shops in recent years. And high-efficiency machining is the most significant tool to enhance productivity. In this study, to achieve high-efficiency machining in turning process, a spindle speed optimization method was proposed based on a cutting power model. The cutting force and power were estimated from the cutting parameters such as specific cutting force, feed, depth of cut, and spindle speed. The time delay due to the acceleration or deceleration of spindle was considered to predict a more accurate machining time. Especially, the good agreement between the predicted and measured cutting forces showed the reliability of the proposed optimization method, and the effectiveness of the proposed optimization method was demonstrated through the simulation results associated with the productivity enhancement in turning process

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1297-1302
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• 2014

This paper presents modern optimization methods for determining the optimal parameters of proportional-integral-derivative (PID) controller for coupled tank systems. The main objective is to obtain a fast and stable control system for coupled tank systems by tuning of the PID controller using the Particle Swarm Optimization algorithm. The result is compared in terms of system transient characteristics in time domain. The obtained results using the Particle Swarm Optimization algorithm are also compared to conventional PID tuning method like the Ziegler-Nichols tuning method, the Cohen-Coon method and IMC (Internal Model Control). The simulation results have been simulated by MATLAB and show that tuning the PID controller using the Particle Swarm Optimization (PSO) algorithm provides a fast and stable control system with low overshoot, fast rise time and settling time.

• Journal of Power Electronics
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• v.11 no.1
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• pp.105-111
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• 2011

By having accurate knowledge of the magnetic field distribution and the thrust calculation in linear synchronous motors, assessing the performance and optimization of the motor design are possible. In this paper, after carrying out a performance analysis of a single-sided wound secondary linear synchronous motor by varying the motor design parameters in a layer model and a d-q model, machine single- and multi-objective design optimizations are carried out to improve the thrust density of the motor based on the motor weight and the motor efficiency multiplied by its power factor by defining various objective functions including a flexible objective function. A genetic algorithm is employed to search for the optimal design. The results confirm that an overall improvement in the thrust mean, efficiency multiplied by the power factor, and thrust to the motor weight ratio are obtained. Several design conclusions are drawn from the motor analysis and the design optimization. Finally, a finite element analysis is employed to evaluate the effectiveness of the employed machine models and the proposed optimization method.