• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.4
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• pp.326-333
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• 2015

A turbo fan engine performance analysis program combined with a particle swarm optimization(PSO) has been developed to optimize the major design parameters of the combat aircraft gas turbine engine. The optimized parameters includes bypass ratio, fan pressure ratio, high pressure compression ratio and burner exit temperature. The objective parameters have been determined using a multi-objective function consisting of the net thrust and specific fuel consumption along a weight function. The basic model for the combat aircraft gas turbine engine has been selected as the F404 turbofan engine which is widely used in the combat aircraft, F-18 and Korean high level training aircraft, T-50. The optimal conditions of four parameters have been obtained for various design conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4228-4247
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• 2018

Many methods have been developed for the vehicles to create clusters in vehicular ad hoc networks (VANETs). Usually, nodes are vehicles in the VANETs, and they are dynamic in nature. Clusters of vehicles are made for making the communication between the network nodes. Cluster Heads (CHs) are selected in each cluster for managing the whole cluster. This CH maintains the communication in the same cluster and with outside the other cluster. The lifetime of the cluster should be longer for increasing the performance of the network. Meanwhile, lesser the CH's in the network also lead to efficient communication in the VANETs. In this paper, a novel algorithm for clustering which is based on the social behavior of Gray Wolf Optimization (GWO) for VANET named as Intelligent Clustering using Gray Wolf Optimization (ICGWO) is proposed. This clustering based algorithm provides the optimized solution for smooth and robust communication in the VANETs. The key parameters of proposed algorithm are grid size, load balance factor (LBF), the speed of the nodes, directions and transmission range. The ICGWO is compared with the well-known meta-heuristics, Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) for clustering in VANETs. Experiments are performed by varying the key parameters of the ICGWO, for measuring the effectiveness of the proposed algorithm. These parameters include grid sizes, transmission ranges, and a number of nodes. The effectiveness of the proposed algorithm is evaluated in terms of optimization of number of cluster with respect to transmission range, grid size and number of nodes. ICGWO selects the 10% of the nodes as CHs where as CLPSO and MOPSO selects the 13% and 14% respectively.

• Steel and Composite Structures
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• v.12 no.6
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• pp.541-548
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• 2012

This paper deals with the applicability of extended layerwise optimization method (ELOM) for frequency optimization of laminated composite plates. The design objective is the maximization of the fundamental frequency of the laminated plates. The fibre orientations in the layers are considered as design variables. The first order shear deformation theory (FSDT) is used for the finite element solution of the laminates. Finally, the numerical analysis is carried out to show the applicability of extended layerwise optimization algorithm of laminated plates for different parameters such as plate aspect ratios and boundary conditions.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.3
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• pp.8-16
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• 2006

This paper discusses design sensitivity analysis and its application to a structural dynamics modification. Eigenvalue derivatives are determined with respect to the element parameters, which include intrinsic property parameters such as Young's modulus, density of the material, diameter of a beam element, thickness of a plate element, and shape parameters. Derivatives of stiffness and mass matrices are directly calculated by derivatives of element matrices. The first and the second order derivatives of the eigenvalues are then mathematically derived from a dynamic equation of motion of FEM model. The calculation of the second order eigenvalue derivative requires the sensitivity of its corresponding eigenvector, which are developed by Nelson's direct approach. The modified eigenvalue of the structure is then evaluated by the Taylor series expansion with the first and the second derivatives of eigenvalue. Numerical examples for simple beam and plate are presented. First, eigenvalues of the structural system are numerically calculated. Second, the sensitivities of eigenvalues are then evaluated with respect to the element intrinsic parameters. The most effective parameter is determined by comparing sensitivities. Finally, we predict the modified eigenvalue by Taylor series expansion with the derivatives of eigenvalue for single parameter or multi parameters. The examples illustrate the effectiveness of the eigenvalue sensitivity analysis for the optimization of the structures.

• Journal of Power Electronics
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• v.18 no.1
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• pp.92-102
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• 2018

A sliding mode control (SMC) for servo motors based on the differential evolution (DE) algorithm, called DE-SMC, is proposed in this study. The parameters of SMC should be designed exactly to improve the robustness, realize the precision positioning, and reduce the steady-state speed error of the servo drive. The main parameters of SMC are optimized using the DE algorithm according to the speed feedback information of the servo motor. The most significant influence factor of the DE algorithm is optimization iteration. A suitable iteration can be achieved by the tested optimization process profile of the main parameters of SMC. Once the parameters of SMC are optimized under a convergent iteration, the system realizes the given performance indices within the shortest time. The experiment indicates that the robustness of the system is improved, and the dynamic and steady performance achieves the given performance indices under a convergent iteration when motor parameters mismatch and load disturbance is added. Moreover, the suitable iteration effectively mitigates the low-speed crawling phenomenon in the system. The correctness and effectiveness of DE-SMC are verified through the experiment.

• Structural Engineering and Mechanics
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• v.88 no.6
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• pp.521-533
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• 2023

In the present study, the finite volume method is applied for the thermal performance prediction of the natural ventilation system using vertical solar chimney whereas, design parameters are optimized through the response surface methodology (RSM). The computational simulations are performed for various parameters of the solar chimney such as absorber temperature (40≤T_abs≤70℃), inlet temperature (20≤T₀≤30℃), inlet height of (0.1≤h≤0.2 m) and chimney width (0.1≤d≤0.2 m). Analysis of variance (ANOVA) was carried out to identify the design parameters that influence the average Nusselt number (Nu) and mass flow rate (ṁ). Then, quadratic polynomial regression models were developed to predict of all the response parameters. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are Nu=25.67 and ṁ=24.68 kg/h·m, corresponding to design parameters h=0.18 m, d=0.2 m, T_abs=46.81℃ and T₀=20℃. The optimal ventilation flow rate is enhanced by about 96.65% compared to the minimum ventilation rate, while solar energy consumption is reduced by 49.54% compared to the maximum ventilation rate.

• The Journal of Korean Academy of Prosthodontics
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• v.44 no.2
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• pp.185-196
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• 2006

Statement of problem: The researches on the influence of design variables on the stress distribution in cortical and trabecular bones and on optimal design for implant system were limited. Purpose: The purpose of this study is to identify the sensitivities of design parameters and to suggest the optimal parameters for designing the onebody type implant system. Material and methods: Stresses arising in the implant system were obtained by finite element analysis using a three dimensional model. An onebody type implant system[Oneplant (Warrantec. Co. Ltd., Korea)] was considered in this study. Vortical load(150 N) was applied on the top of the abutment along the axial direction. The initial design variables set for sensitivity analysis were radius of fixture, numbers of micro thread, numbers of power thread, height of micro thread, future length, tapered angle of future, inclined angle of thread, width of micro thread and width of power thread. The statistical technique of Design of Experiments(DOE) was applied tn the simulation model to deduce effective design parameters on stress distributions in bones. The deduced design parameters were incorporated into a fully automated design tool which is coupled with the finite element analysis and numerical optimization to determine the optimal design parameters. Results: 1. The result of sensitivity analysis showed six design variables - radius of future, tapered angle of fixture, inclined angle of thread, numbers of power thread, numbers of micro thread and height of micro thread - were more influential than the others. 2. The optimal values of design variables can be deduced by coupling finite element analysis (FEA) and design optimization tool(DOT).

• Journal of Welding and Joining
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• v.21 no.7
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• pp.42-48
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• 2003

Welding distortion is a current issue in many industrial parts, especially for heavy industry such as shipbuilding, plant industry. The welding process has many processing parameters influencing welding angular distortion such as heat input power, welding speed, gas flow rate, plate thickness and the welded material properties, etc. In this work, the conventional local minimization concept was applied to find a set of optimum welding process parameters, consisted of welding speed, plate thickness and heat input, for a minimum angular distortion. An analytic solution for welding angular distortion, which is based on laminated plate theory, was also applied to investigate and optimize the welding process parameters. The optimized process parameters and the angular distortion for various parametric conditions could be easily found by using the local minimum concept.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.1
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• pp.63-73
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• 2014

For robust stability analysis of parameters uncertainty missiles, the traditional frequency domain method can only analyze each respective channel at several interval points within uncertain parameter space. Discontinuous calculation and couplings between channels will lead to inaccurate analysis results. A method based on the ${\nu}$-gap metric is proposed, which is able to comprehensively evaluate the robust stability of missiles with uncertain parameters; and then a genetic-simulated annealing hybrid optimization algorithm, which has global and local searching ability, is used to search for a parameters combination that leads to the worst stability within the space of uncertain parameters. Finally, the proposed method is used to analyze the robust stability of a re-entry missile with uncertain parameters; the results verify the feasibility and accuracy of the method.

• Journal of the Korea Society of Computer and Information
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• v.9 no.1
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• pp.87-93
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• 2004

In the design of mobile wireless communication network, BSC(Base Station Location), BSC(Base Station Controller) and MSC(Mobile Switching Center) are the most important parameters. Designing base station location, the cost must be minimized by combining various, complex parameters. We can solve this Problem by combining optimization algorithm, such as Simulated Annealing, Tabu Search, Genetic Algorithm, Random Walk Algorithm that have been used extensively for global optimization. This paper shows the 4 kinds of algorithm to be applied to the optimization of base station location for communication system and then compares, analyzes the results and shows optimization process of algorithm.