• Computational Structural Engineering
• /
• v.8 no.2
• /
• pp.123-132
• /
• 1995

Genetic Algorithms(GA), which are based on the theory of natural evolution, have been evaluated highly for their robust performances. Traditional GA has mostly used binary code for representing design variable. The binary code GA has many difficulties to solve optimization problems with continuous design variables because of its large computer core memory size, inefficiency of its computing time, and its bad performance on local search. In this paper, a real code GA is proposed for dealing with the above problems. So, new crossover and mutation processes of GA are developed to use continuous design variables directly. The results of read code GA are compared with those of binary code GA for several single and multiple objective optimization problems. As a result of comparisons, it is found that the performance of the real code GA is better than that of the binary code GA, and concluded that the real code GA developed here can be used for the general optimization problem.

• Korean Journal of Optics and Photonics
• /
• v.27 no.6
• /
• pp.203-211
• /
• 2016

We have studied the hybrid method for reconstructing apodized chirped fiber Bragg gratings, using both an analytic estimation of grating parameters and an optimization algorithm. The Hilbert transform of the reflection spectrum was utilized to estimate grating parameters, and then the layer-peeling algorithm was used to obtain refined parameter values by the differential-evolution optimization process. Calculations for a fiber Bragg grating with wavelength chirp rate 2 nm/cm were obtained with an accuracy of $6{\times}10^{-5}nm/cm$ for the chirp rate and $3{\times}10^{-9}nm/cm$ for the index modulation, with much improved calculation speed and high reliability.

• Journal of Korea Water Resources Association
• /
• v.55 no.11
• /
• pp.887-901
• /
• 2022

Estimation of the parameters for individual rainfall-rainfall events can lead to a different set of parameters for each event which result in lack of parameter identifiability. Moreover, it becomes even more ambiguous to determine a representative set of parameters for the watershed due to enhanced variability exceeding the range of model parameters. To reduce the variability of estimated parameters, this study proposed a parameter optimization framework with the simultaneous use of multiple rainfall-runoff events based on NSE as an objective function. It was found that the proposed optimization framework could effectively estimate the representative set of parameters pertained to their physical range over the entire watershed. It is found that the difference in NSE value of optimization when it performed individual and multiple rainfall events, is 0.08. Furthermore, In terms of estimating the observed floods, the representative parameters showed a more improved (or similar) performance compared to the results obtained from the single-event optimization process on an NSE basis.

• Journal of the Korea Society for Simulation
• /
• v.26 no.4
• /
• pp.11-21
• /
• 2017

This paper discusses the design parameter sensitivity analysis and multi-objective function optimization for improving the impact performance of an auto-sensing breaker based on the analytical model of the same, which secured reliability in a previous research. The study aims to improve both impact power and stability by complementing the existing research that only improved the impact power. The study sequence is as follows: first, the analysis scenarios for the accurate sensitivity analysis and optimization are set up. Second, the sensitivity of the design parameter of the auto-sensing breaker is analyzed, and the variables with high sensitivity are extracted. Third, the extracted variables are used to optimize the multi-objective functions, and the optimized performance is compared with the initial performance to see how the impact performance on the existing auto-sensing breaker has improved. This study is based on domestic technology, and will allow the development of products with a better blowing performance than their existing overseas counterparts.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.34 no.7
• /
• pp.28-34
• /
• 2006

In general engineering problems, the purpose of an optimization is to get optimal design variables. It is the same problem to fix the total amount of the design variables and to judge the optimal mixing proportions of the design variables. That is to say, we can recompose the engineering problems in the concepts of the mixture amount experiments. The goal of mixture amount method is to get the response surfaces of varying both the mixing proportion of component and the total amount of the mixture. The solution of the aircraft fuselage optimization problem is obtained by the mixture amount method and genetic algorithm. In this study, it is shown that the mixture amount method can be utilized for the aircraft structural optimization problem. Also, this method in this study can be applied for the optimization problems over 12 design variables which is impossible for D-optimal design.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.34 no.9
• /
• pp.1-10
• /
• 2006

An optimization study on a small turbopump impeller operating at the low specific speed is conducted to obtain high output head at the impeller exit. Its specific speed in SI unit (RPM, m3/sec, m) is 4.0, and the outer diameter is 56mm. On the optimization, the outer diameter of the impeller is maintained constant to restrict the pump size, and an objective function of pressure head is maximized with eight design variables, which are related with designing an impeller shape. The response surface method is used to the optimization scheme, and the commercial code CFX-10 is applied for numerical analysis. The pressure head of the objective function obtained with an optimized impeller is increased by 9.7% compared with that obtained on an impeller designed with typically recommended design parameters. This increment is caused by reducing the recirculation region within the impeller passage.

• Korean Chemical Engineering Research
• /
• v.56 no.1
• /
• pp.29-41
• /
• 2018

Separating a mixture having an azeotrope or low relative volatility with single distillation column is difficult. Separating water-acetic acid mixture and water-ethanol mixture with a distillation column consumes a lot of energy. Pervaporation membrane can be used to separate the mixture in the concentration region where separation is difficult with distillation. We simulated a distillation-membrane hybrid process where membrane is located on the head of the distillation column for efficient separation of water-acetic acid and water-ethanol mixture. Permeability data were obtained from experiments and literature. We formulated an optimization problem for the process with total annual cost (TAC) as an objective function and major design variables as optimization variables. Major optimization variable affecting TAC of the hybrid process was shown to be distillate concentration. We also suggested a simplified optimization procedure to get a close-to-optimal solution.

• Journal of Wetlands Research
• /
• v.22 no.1
• /
• pp.15-23
• /
• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1-2
• /
• 2011

온라인 전기자동차에 적용된 무선전력전송 시스템의 자기장 설계 기술은 전송되는 전력의 용량, 효율, 누설자기장 세기 등 전기적인 성능변수들을 결정하는 핵심 기술이다. 최대의 전력용랑과 효율을 만들어내면서 동시에 누설 자기장에 대한 전파법의 규격을 만족시켜야 한다. 이를 위해 자기장의 형상화에 영향을 주는 다양한 설계변수를 찾아내고, 변수들의 최적화에 대한 체계적인 접근이 필요한 시점이다. 본 논문에서는 온라인 전기자동차의 자기장 설계에 영향을 주는 설계변수의 특성과, 성능변수에 미치는 영향을 분석하고, 최적의 성능변수를 만들어 내기 위한 방법을 제시한다.

• Proceedings of the Acoustical Society of Korea Conference
• /
• autumn
• /
• pp.359-362
• /
• 2004

수중에서 사용되는 음향변환기의 성능은 사용환경 뿐만 아니라 많은 설계변수들의 조합에 의해 결정되며, 이들 설계변수들의 영향은 서로 선형 독립적이지 않은 경우가 대부분이다. 따라서 음향변환기의 최적성능을 구현하기 위해서는 각 설계변수들의 개별영향 뿐만 아니라 강호작용에 의한 영향을 동시에 고려하여야 한다. 본 연구에서는 tonpilz 변환기에 대하여 유한 요소 해석을 통하여 설계변수들이 중심 주파수, 대역폭, 음압 및 충격력에 미치는 영향을 파악하였고, 그 결과들의 통계적 다중 회귀분석을 통하여 중심 주파수 대역폭 음압 및 충격력을 이들 설계변수들의 함수로 도출하였다. 나아가 제한 최적화 기법을 이용하여 주어진 사용 환경에서 동작하면서 최대 음압을 구현할 수 있는 변환기의 최적 구조를 자동으로 결정할 수 있는 프로그램을 개발하였다. 본 연구에서 개발된 최적화 프로그램은 다중 설계변수들의 상호효과를 충분히 반영할 수 있으며, 유사한 기능의 여타 음향변환기 설계에 직접 응용이 가능할 것이다.