• International Journal of Railway
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• v.7 no.2
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• pp.57-63
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• 2014

This paper presents the optimization of suspension characteristics under the condition of curved track railway vehicles. Reducing lateral acceleration on curved track is an issue for high-speed railway vehicles. In terms of curved track running environments, reducing the lateral vibration of railway vehicles is critical to safety and curving performance. The properties of lateral damping and stiffness of both primary and secondary suspension show effect on wheel-set, bogie and car-body. Analysis for reducing the lateral vibration of rail vehicles with respect to the characteristics of both primary and secondary suspension has been developed using ADAMS/Rail. Response Surface Method has been chosen for the purpose of verifying correlation effects among design parameters. Also, this paper suggests the method for designing optimal suspension of railway vehicles on curved track. The optimization result indicates decrement of lateral acceleration on wheel-set by 3% and bogie by 1% on curved track. Finally, this paper comes to the conclusion that suspension system of railway vehicle (KTX I) is properly designed when regarding lateral vibration of railway vehicle on diverse curved track condition.

• Bulletin of the Korean Chemical Society
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• v.25 no.3
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• pp.377-381
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• 2004

Chiral separation of aryalcohols such as 1-phenyl-propanol, 1-phenyl-2-proanol, and 2-phenyl-1-propanol by capillary electrophoresis has been optimized using the overlapping resolution mapping (ORM) scheme. Three critical parameters of the electrophoretic media, i.e. phosphate concentration, sulfated ${\beta}$-cyclodextrin (CD) concentration and pH, were chosen for optimization. The working ranges were initially presumed by 7 preexperiments. Further optimization was carried out by another seven experiments within the narrow working ranges. From the final overlapping resolution mapping all peak pairs, the area of maximum separations were located. Using the conditions of a point in this area, we found that the target compounds were a baseline separated within 30 min. The maximum separation conditions of arylalcohols were a chiral selector concentration of 5.4%, a phosphate concentration of 28 mM, and a pH of 5.0.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.645-653
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• 2017

Thermal and flow modeling and fin structure optimization were performed to reduce the weight of an electrical device with a staggered fin. First, a numerical model for thermal and flow characteristics was suggested, and then, the model was verified experimentally. Using the verified model, improvement in cooling performance of the cooling system through the staggered fins was predicted. As a result, 87.5% of total heat generated was dissipated through the cooling fins, and a thermal island was observed in the rotor because of low velocity of the internal air flow through the air gap. In addition, it was confirmed that the staggered fin improves the cooling performance but it also increases the total pressure drop within the cooling system, by maximizing the leading edge effect. Based on this analysis result, the effect of each design parameter on the thermal and flow characteristics was analyzed to select the main optimal design parameters, and multi-objective optimization was performed by considering the cooling performance and the fin weight. In conclusion, the optimized fin structure improved the cooling performance by 7% and reduced the fin weight by 28% without any compromise of the pressure drop.

• Journal of Navigation and Port Research
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• v.33 no.9
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• pp.635-644
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• 2009

The optimum design of power yacht belongs to the nonlinear constrained optimization problems. The determination of scantlings for the bow structure is a very important issue with in the whole structural design process. The derived design results are obtained by the use of real-coded micro-genetic algorithm including evaluation from Lloyd's Register small craft guideline, so that the nominal limiting stress requirement can be satisfied. In this study, the minimum volume design of bow structure on the power yacht was carried out based on the finite element analysis. The target model for optimum design and local structural analysis is the bow structure of a power yacht. The volume of bow structure and the main dimensions of structural members are chosen as an objective function and design variable, respectively. During optimization procedure, finite element analysis was performed to determine the constraint parameters at each iteration step of the optimization loop. optimization results were compared with a pre-existing design and it was possible to reduce approximately 19 percents of the total steel volume of bow structure from the previous design for the power yacht.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.183-188
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• 2005

Although it is widely used to find an optimum setting of manufacturing process parameters in a variety of engineering fields, the Taguchi method has a difficulty in dealing with multi-response situations in which several response variables should be considered at the same time. For example, electrode wear, surface roughness, and material removal rate are important process response variables in an electrical discharge machining (EDM) process. A simultaneous optimization should be accomplished. Many researches from various disciplines have been conducted for such multi-response optimizations. One of them is a fuzzy logic approach presented by Lin et al. [1]. They showed that two response characteristics are converted into a single performance index based upon fuzzy logic. However, it is pointed out that information regarding relative importance of response variables is not considered in that method. In order to overcome this problem, a desirability function can be adopted, which frequently appears in the statistical literature. In this paper, we propose a novel approach for the multi-response optimization by incorporating fuzzy logic into desirability function. The present method is illustrated by an EDM data of Lin and Lin [2].

• Smart Structures and Systems
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• v.6 no.7
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• pp.767-792
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• 2010

In this paper, the optimal design of vibration control system for smart structures has been investigated semi-analytically via the optimization of geometric parameters like the placements and sizes of piezoelectric sensors and actuators (S/As) bonded on the structures. The criterion based on the maximization of energy dissipation was adopted for the optimization of the control system. Based on the sensing and actuating equations, the total energy stored in the system which is used as the objective function was analytically derived with design variables explicitly presented. Two cases of single and combined vibration modes were addressed for a simply supported beam and a simply supported cylindrical shell. For single vibration mode, the optimal distributions of the piezoelectric S/As could be obtained analytically. However, the Sequential Quadratic Programming (SQP) method has to be employed to solve those which violated the prescribed constraints and to solve the case of combined vibration modes. The results of three examples, which include a simply supported beam, a simply supported cylindrical shell and a simply supported plate, showed good agreement with those obtained by the Genetic Algorithm (GA) method. Moreover, in comparison with the GA method, the proposed method is more effective in obtaining better optimization results and is much more efficient in terms of computation time.

• Geotechnical Engineering
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• v.13 no.1
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• pp.47-58
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• 1997

The predicted consolidation behavior of in-situ soft clay is quite different from the meas ureal one mainly due to the approximate numerical modelling techniques as well as the uncertainties involved in soil properties and geological configurations. In order to improve the prediction, this paper takes the following pinto consideration : an optimization technique should be adopted for characterizing the in-situ properties from measurements and also an equivalent and efficient model be considered to incorporate the actual 3-D effects. The soil parameters used be the modified Camflay model, which have an effect on the process of consolidation, were back-analyzed by BFGS scheme on the basis of settlements and pore pressures measured in real sites. The optimization technique was implemented in a general consolidation analysis program SPINED. By using the program, one may be able to appropriately analyze the timetependent consolidation behavior of soft deposits.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.923-928
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• 1993

Genetic algorithms are powerful optimization methods based on the mechanism of natural genetics and natural selection. Genetic algorithms reduce chance of searching local optima unlike most conventional search algorithms and especially show good performances in complex nonlinear optimization problems because they do not require any information except objective function value. This paper presents a new model based on sexual reproduction in nature. In the proposed Sexual Reproduction model(SR model), individuals consist of the diploid of chromosomes, which are artificially coded as binary string in computer program. The meiosis is modeled to produce the sexual cell(gamete). In the artificial meiosis, crossover between homologous chromosomes plays an essential role for exchanging genetic informations. We apply proposed SR model to optimization of the design parameters of Single-sided Linear Induction Motor(SLIM). Sequential Unconstrained Minimization Technique(SUMT) is used to transform the nonlinear optimization problem with many constraints of SLIM to a simple unconstrained problem, We perform optimal design of SLIM available to FA conveyer systems and discuss its results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.135-142
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• 2012

In this paper, we proposed a new architecture called radial basis function-based polynomial neural networks classifier that consists of heterogeneous neural networks such as radial basis function neural networks and polynomial neural networks. The underlying architecture of the proposed model equals to polynomial neural networks(PNNs) while polynomial neurons in PNNs are composed of Fuzzy-c means-based radial basis function neural networks(FCM-based RBFNNs) instead of the conventional polynomial function. We consider PNNs to find the optimal local models and use RBFNNs to cover the high dimensionality problems. Also, in the hidden layer of RBFNNs, FCM algorithm is used to produce some clusters based on the similarity of given dataset. The proposed model depends on some parameters such as the number of input variables in PNNs, the number of clusters and fuzzification coefficient in FCM and polynomial type in RBFNNs. A multiobjective particle swarm optimization using crowding distance (MoPSO-CD) is exploited in order to carry out both structural and parametric optimization of the proposed networks. MoPSO is introduced for not only the performance of model but also complexity and interpretability. The usefulness of the proposed model as a classifier is evaluated with the aid of some benchmark datasets such as iris and liver.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.10
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• pp.1031-1039
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• 2013

This paper presents gain optimization of a 6-DOF underwater robotic platform with 4 rotatable thrusters. To stabilize the 6-DOF motion of the underwater robotic platform, a back-stepping controller is designed with 6 proportional gains and 6 derivative gains. The 12 gains of the backstepping controller are optimized to decrease settling time in step response in 6-DOF motion independently. Stability criterion and overshoots are used as a constraint of the optimization problem. Trust-region algorithm and hybrid Taguchi-Random order Coordinate search algorithm are used to determine the optimal parameters, and the results by two methods are analyzed. Additionally, the resulting controller shows improved performance under disturbances.