• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.33-44
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• 2012

In this study, the optimal operating conditions for the dual mixed refrigerant(DMR) cycle were determined by considering the power efficiency. The DMR cycle consists of compressors, heat exchangers, seawater coolers, valves, phase separators, tees, and common headers, and the operating conditions include the equipment's flow rate, pressure, temperature, and refrigerant composition per flow. First, a mathematical model of the DMR cycle was formulated in this study by referring to the results of a past study that formulated a mathematical model of the single mixed refrigerant(SMR) cycle, which consists of compressors, heat exchangers, seawater coolers, and valves, and by considering as well the tees, phase separators, and common headers. Finally, in this study, the optimal operating conditions from the formulated mathematical model was obtained using a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP). Moreover, the required power at the obtained conditions was decreased by 1.4% compared with the corresponding value from the past relevant study of Venkatarathnam.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.68-78
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• 2012

A layout of an LNG FPSO should be elaborately determined as compared with that of an onshore plant because many topside process systems are installed on the limited area; the deck of the LNG FPSO. Especially, the layout should be made as multi-deck, not single-deck and have a minimum area. In this study, a multi-floor layout for the liquefaction process, the dual mixed refrigerant(DMR) cycle, of LNG FPSO was determined by using the optimization technique. For this, an optimization problem for the multi-floor layout was mathematically formulated. The problem consists of 589 design variables representing the positions of topside process systems, 125 equality constraints and 2,315 inequality constraints representing limitations on the layout of them, and an objective function representing the total layout cost. To solve the problem, a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP) was used in this study. As a result, we can obtain a multi-floor layout for the liquefaction process of the LNG FPSO which satisfies all constraints related to limitations on the layout.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.4
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• pp.268-274
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• 2013

In this paper, objective functions are defined for optimization of radar absorbing structures (RAS) on the aircraft wing leading edge. RAS is regarded as a single layer structure made of dielectrics. Design variables are the real and imaginary parts of complex permittivity. Reflection coefficient(RC) and radar cross section(RCS) are used in the objective function respectively. Transmission line theory is employed to calculate the RC. The RCS is evaluated by using physical optics(PO) for a leading edge part model. Genetic algorithm(GA) is used to perform optimization procedures. The radar absorbing performance of designed RAS is assessed by the RCS of a wing which has RAS on the leading edge.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.4
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• pp.46-51
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• 2012

Injection pressure, an important factor in filling process, should be minimized to enhance injection molding quality. Injection pressure can be controlled by valve gate open timing. In this work, we decided the valve gate open timing to minimize the injection pressure. To solve this design problem, we integrated MAPS-3D (Mold Analysis and Plastic Solution-3Dimension), a commercial injection molding CAE tool, to PIAnO (Process Integration, Automation and Optimization), a commercial PIDO (Process Integration, and Design Optimization) tool using the file parsing method. In order to reduce computational cost, we performed an approximate optimization using meta-models that replaced expensive computer simulations. At first, we carried out DOE (Design of Experiments) using OLHD (Optimal Latin Hypercube Design) available in PIAnO. Then, we built Kriging models using the simulation results at the sampling points. Finally, we used micro GA (Genetic Algorithm) available in PIAnO. Using the proposed design approach, the injection pressure has been reduced by 13.7% compared to the initial one. This design result clearly shows the validity of the proposed design approach.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1930-1939
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• 2015

Wind power planning aims to locate and size wind farms optimally. Traditionally, wind power planners tend to choose the wind farms with the richest wind resources to maximize the energy benefit. However, the capacity benefit of wind power should also be considered in large-scale clustered wind farm planning because the correlation among the wind farms exerts an obvious influence on the capacity benefit brought about by the combined wind power. This paper proposes a planning model considering both the energy and the capacity benefit of the wind farms. The capacity benefit is evaluated by the wind power capacity credit. The Ordinal Optimization (OO) Theory, capable of handling problems with non-analytical forms, is applied to address the model. To verify the feasibility and advantages of the model, the proposed model is compared with a widely used genetic algorithm (GA) via a modified IEEE RTS-79 system and the real world case of Ningxia, China. The results show that the diversity of the wind farm enhances the capacity credit of wind power.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.5
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• pp.59-68
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• 2005

A novel immunotronic approach to fault detection in hardware based on symbiotic evolution is proposed in this paper. In the immunotronic system, the generation of tolerance conditions corresponds to the generation of antibodies in the biological immune system. In this paper, the principle of antibody diversity, one of the most important concepts in the biological immune system, is employed and it is realized through symbiotic evolution. Symbiotic evolution imitates the generation of antibodies in the biological immune system morethan the traditional GA does. It is demonstrated that the suggested method outperforms the previous immunotronic methods with less running time. The suggested method is applied to fault detection in a decade counter (typical example of finite state machines) and MCNC finite state machines and its effectiveness is demonstrated by the computer simulation.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.759-764
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• 2004

본 연구는 Deng(1989)이 제시한 Grey 모형을 이용하여 성진강댐의 월유입량을 예측하였고 그 방법을 제시하였다. Grey 모형은 시계열모형이나 다른 모형에 비해 비교적 적은 수의 자료를 이용하고, 간단할 수식으로 구성되어 있는 장점이 있으나, 적은 수의 자료로 인해 입력자료가 가지는 증감의 경향(trend)으로 오차가 발생하기 쉽다. 그러므로 예측오차를 극복하기 위해서 Fuzzy 시스템을 결합한 Fuzzy-Grey 모형을 구성하였고 Fuzzy 시스템에 필요한 매개변수를 추정하기 위해 최적화기법인 유전자 알고리즘(GA; Genetic Algorithm)을 이용하였다. Grey 모형과 결합된 Fuzzy 시스템은 현재의 입력자료가 가지는 패턴과 가장 유사한 패턴의 과거자료를 이용하여 현재의 입력자료의 예측오차를 추론해내는 기능을 가진다. 오차를 추론하기 위해서 과거 월유입량 자료중 현재 입력 자료와 유사한 패턴을 Grey 상관도를 이용하여 검색하고, 보다 높은 유사성을 가지는 패턴을 선별하고자 노름(norm)을 사용하였고, 유전자 알고리즘의 탐색공간을 제한하였다. 이렇게 구성한 Fuzzy-Grey 모형을 이용하여 전국적인 가뭄년도였던 1992년, 1988년, 2001년에 대해 섬진강댐의 월유입량을 예측하였다. 오차는 1982년, 2001년, 1988년 순으로 비슷한 크기의 오차가 발생하였는데 결과를 분석하여 보면, 급격한 월유입량의 변화가 있었던 경우에 오차가 크게 발생하였으나 가뭄년도에 대해 월유입량의 불확실성이 큼에도 불구하고 비교적 월유입량의 추세를 잘 예측한 것으로 판단된다. 본 연구에서 적용한 Fuzzy-Grey 모형은 적은 수의 자료를 이용하여 예측하고 예측결과를 다시 입력자료로 사용하는 업데이트 방식을 사용하기 때문에 예측결과의 오차가 완전하게 보정되지 않으면 다음 결과에 역시 오차를 주게 되어 오차보정이 상당히 중요하다는 것을 알 수 있었다. 오차를 보다 효과적으로 보정하기 위해서는 퍼지제어에 사용되는 퍼지규칙의 수를 늘리고, 유입량에 직접적인 영향을 주는 강우량과 연계한 2변수의 Fuzzy-Grey 모형을 이용한다면 보다 정확한 유입량 예측이 가능할 것으로 사료된다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.9
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• pp.787-798
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• 2015

The emergence of mid-to-small satellites has created a need for rapid development with a relatively low cost. However, the development of mid-to-small satellites requires considerable time and cost in early phase, in particular, during the development of mission and system requirements through iterations of conceptual design and mission design. In this research, Spacecraft Conceptual Design Tool(SCDT) which is based on Graphical User Interface(GUI) was developed to reduce the time and cost for early phase development. Furthermore, GUI-based software can make the input values to be editable easily and show users design results in various way. In this paper, the development results of MATLAB GUI-based SCDT are introduced.

• Journal of Drive and Control
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• v.17 no.3
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• pp.26-32
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• 2020

In modern society, the energy-saving problem of industrial vehicles is economically and environmentally critical. Energy savings using the potential energy of forklifts are one of the viable solutions to resolving this problem. The basic concept of this study is to operate the hydraulic motor and recharge the battery using the flow rate from the cylinder when loading heavy objects and lowering the fork. To save energy, the torque and rotational speed of the generator should be optimized according to the load and descent speed to increase efficiency. To this end, we propose a system that optimizes energy saving efficiency by controlling the swashplate angle of the variable hydraulic motor through the GA(Genetic-Algorithm). The results were verified by building and comparing fixed motor models and variable motor models using the AMEsim. The results of the study show that the proposed optimized swashplate angle increases the energy saving efficiency by approximately 6%-8%, depending on the working conditions.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.11-20
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• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).