• Journal of the Korean Society for Precision Engineering
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• v.25 no.9
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• pp.59-70
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• 2008

Polynomial is used to optimize crown bowl shape of a marine medium speed diesel engine piston. The primary goal of this paper is that it's for an original design through a thermal stress and highest temperature minimum. Piston is modeled using solid element with 6 design variables defined the positional coordinate value. Global optimum of design variables are found and evaluated as developed and integrated with the optimum algorithm combining genetic algorithm(GA) and tabu search(TS). Iteration for optimization is performed based on the result of finite element analysis. After optimization, thermal stress and highest temperature reduced 0.68% and 1.42% more than initial geometry.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.4
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• pp.29-35
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• 2007

The main objective of this paper is to propose the optimal design method of forging process using genetic algorithm. Design optimization of forging process was doing about one stage and multi stage. The objective function is considered the filling of die. The chosen design variables are die geometry in multi stage and initial billet shape in one stage. We performed FE analysis to simulated forging process. The optimized preform and initial billet shape was obtained by genetic algorithm and FE analysis. To show the efficiency of GA method in forging problem are solved and compared with published results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4216-4227
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• 2015

In this study, a model is developed based on Life Cycle Energy Analysis (LCEA) method with Genetic Algorithm (GA) to determine optimal diameter of Water Distribution System (WDS). For hydraulic analysis the EPANET2.0 program is linked with developed model, pipe-aging equation and pipe-breakage equation are built in to developed model to simulate pipe change through life cycle. The model is then applied to two sample WDSs for optimal energy design. After determining optimal diameter for each WDS, the total cost is calculated based on determined diameter and compared with well-known optimal diameter set of each WDS. Results show that optimal energy design of WDSs through the developed model can be an alternative option for optimal design of WDSs for reducing energy with lower in cost.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1007-1014
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• 2015

An optimally designed six-phase induction motor (6PIM) is compared with an initial design induction motor having the same ratings. The Genetic Algorithm (GA) method is used for optimization and multi objective function is considered. Comparison of the optimum design with the initial design reveals that better performance can be obtained by a simple optimization method. Also in this paper each design of 6PIM, is simulated by MAXWELL_2D. The obtained simulation results are compared in order to find the most suitable solution for the specified application, considering the influence of each design upon the motor performance. Construction a 6PIM based on the information obtained from GA method has been done. Quality parameters of the designed motors, such as: efficiency, power losses and power factor measured and optimal design has been evaluated. Laboratory tests have proven the correctness of optimal design.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2115-2123
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• 2006

The paper deals with the identification of Pareto optimal solutions using GA based coevolution in the context of multiobjective optimization. Coevolution is a genetic process by which several species work with different types of individuals in parallel. The concept of cooperative coevolution is adopted to compensate for each of single objective optimal solutions during genetic evolution. The present study explores the GA based coevolution, and develops prescribed and adaptive scheduling schemes to reflect design characteristics among single objective optimization. In the paper, non-dominated Pareto optimal solutions are obtained by controlling scheduling schemes and comparing each of single objective optimal solutions. The proposed strategies are subsequently applied to a three-bar planar truss design and an energy preserving flywheel design to support proposed strategies.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.10a
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• pp.18-23
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• 2003

The Objective of this research is to find the optimal design of the Noise Reduction Interference Model (NRIM) which is recently invented. Without optimization, the NRIM has been successful to reduce the urban noise induced by trains and automobiles. While it is used with the barrier on the road, there is a strong desire to reduce noise more. Yet the only remedy is to make the barrier higher with cost increase. Therefore, the optimal design is necessary to reduce noise while maintaining the barrier height. More efficient Genetic Algorithm is used to find the optimal shape of NRIM with the reduction of noise lever up to 15 dB. also BEM is used to verify the optimal design results.

• Structural Engineering and Mechanics
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• v.50 no.3
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• pp.323-347
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• 2014

This paper proposes a Particle Swarm Optimization (PSO) algorithm, which is improved by making use of the Harmony Search (HS) approach and called HS-PSO algorithm. A computer code is developed for optimal sizing design of non-linear steel frames with various semi-rigid and rigid beam-to-column connections based on the HS-PSO algorithm. The developed code selects suitable sections for beams and columns, from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange W-shapes, such that the minimum total cost, which comprises total member plus connection costs, is obtained. Stress and displacement constraints of AISC-LRFD code together with the size constraints are imposed on the frame in the optimal design procedure. The nonlinear moment-rotation behavior of connections is modeled using the Frye-Morris polynomial model. Moreover, the P-${\Delta}$ effects of beam-column members are taken into account in the non-linear structural analysis. Three benchmark design examples with several types of connections are presented and the results are compared with those of standard PSO and of other researches as well. The comparison shows that the proposed HS-PSO algorithm performs better both than the PSO and the Big Bang-Big Crunch (BB-BC) methods.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.466-473
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• 2000

Optimality Criteria algorithm based on the derivation of reciprocal approximations has been applied to structural optimization of large-scale structures. However, required computational cost for the serial analysis algorithm of large-scale structures consisting of a large number of degrees of freedom and members is too high to be adopted in the solution process of O.C. algorithm Thus, parallel version of O.C. algorithm on the network of personal computers is presented in this Paper. Parallelism in O.C. algorithm may be classified into two regions such as analysis and optimizer part As the first step of development of parallel algorithm, parallel structural analysis algorithm is developed and used in O.C. algorithm The algorithm is applied to optimal design of a 54-story plane frame structure

• Geomechanics and Engineering
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• v.14 no.1
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• pp.91-98
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• 2018

Length of a vehicle is an important variation to generate different variants of an automotive platform. This parameter is usually adjusted by embedding dimensional flexibility into different components of the Body in White (BIW) including the floor pan. Due to future uncertainties, it is not necessarily possible to define certain values of wheelbase for the future products of a platform. This work is performed to add flexibility into the design process of a length-variable floor pan. By means of this analysis, the cost and time consuming process of optimization is not necessary to be performed for designing the different variants of a product family. Stiffness and mass of the floor pan are two important functional requirements of this component which directly affect the occupant comfort, dynamic characteristics, fuel economy and environmental protection of the vehicle. A combination of Genetic algorithm, GMDH-type of artificial neural networks and TOPSIS methods is used to optimally design the floor pan associated with arbitrary length of the variant in the defined system range. The correlation between the optimal results shows that for a constant mass of the floor pan, the first natural frequency decreases by increasing the length of this component.