• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.156-159
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• 1996

An adaptive predictive control for steam-reforming plant which consist of a steam-gas reformer and a waste heat steam-boiler was studied by using MIMO bilinear model. The simulation experiments of the process identification were performed by using linear and bilinear models. From the simulation results it was found that the bilinear model represented the dynamic behavior of a steam-reforming plant very well. ARMA model was used in the process identification and the adaptive predictive control. To verify the performance and effectiveness of the adaptive predictive controller proposed in this study the simulation results of steam-reforming plant control based on bilinear model were compared to those of linear model. The simulation results showed that the adaptive predictive controller based on bilinear model provides better performance than those of linear model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.203-203
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• 2000

The P&S(Power Plant Simulation System) is a powerful simulation software system for the dynamic behavior of power plants. The P&S module libraries provide plant models with higher flexibility of dynamic simulations for process and control designs. The P&S software was effectively available for PCS based on Linux and modem workstations based on Unix. The P&S was applied for simulating the dynamic behaviors of the SOVR(Supercritical Once-Through Variable Pressure Reheater) according to the operations such as stan-up, shutdown, load following, load change and trip in order to obtain an optimal operation procedure for Unit 5/6 of Taeahn fossil power plant consisted of SOVRs and steam turbines.

• 전기학회논문지
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• 제57권12호
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• pp.2285-2290
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• 2008

Even though efficiency of coal-fired power plant is proportional to operating temperature, increasement of operating temperature is limited by a technological level of each power plant component. It is an alternative plan to increase operating pressure up to ultra super critical point for efficiency enhancement. It is difficult to control process of power plant in ultra super critical point because that point has highly nonlinear characteristics. In this paper, new control logic, Unit Response Optimizer Controller(URO Controller) which is based on Fuzzy logic and Model Predictive Controller, is introduced for better performance. Then its performance is tested and analyzed with design guideline.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2006년도 춘계학술대회
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• pp.576-579
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• 2006

This paper describes characteristics and procedure of the basic design of large scale solar thermal power plant system. The evaluation is based on the operating data of CESA-I, solar central receiver plant. In order to evaluate the solar irradiation on the receiver, it is necessary to calculate the amount of thermal energy consumption at steam turbine and storage system in the STPPS. Especially, it is need to take into account of the storage and operating time to design a plant efficiently. In addition, basic design is performed for the CESA-I using the software tool of THERMOFLEX program. Based on the results, It is at lowed to use the program to investigate detail performance of each units of the STPPS by varying the operating conditions.

• 한국추진공학회지
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• 제26권6호
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• pp.28-33
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• 2022

본 연구에서는 일반적으로 사용하는 Hydroxyl terminated polybutadiene(HTPB)계 고체 추진제의 경화 온도와 당량비 변경에 따른 경화 특성을 고찰하였다. 또한, Triphenyl bismuth(TPB), Maleic anhydride(MA) 그리고 Magnesium oxide(MgO) 촉매 시스템에서 이들의 비율 및 함량에 따른 경화 반응 영향도 확인하였다. 마지막으로 추진제 혼화 시 각 공정 별 수분을 투입하여 수분이 추진제 경화에 끼치는 영향을 확인하였다.

• International Journal of Computer Science & Network Security
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• 제24권8호
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• pp.72-84
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• 2024

Plant leaf classification is an imperative task when their use in real world is considered either for medicinal purposes or in agricultural sector. Accurate identification of plants is, therefore, quite important, since there are numerous poisonous plants which if by mistake consumed or used by humans can prove fatal to their lives. Furthermore, in agriculture, detection of certain kinds of weeds can prove to be quite significant for saving crops against such unwanted plants. In general, Artificial Neural Networks (ANN) are a suitable candidate for classification of images when small datasets are available. However, these suffer from local minima problems which can be effectively resolved using some global optimization techniques. Considering this issue, the present research paper presents an automated plant leaf classification system using optimized soft computing models in which ANNs are optimized using Grasshopper Optimization algorithm (GOA). In addition, the proposed model outperformed the state-of-the-art techniques when compared with simple ANN and particle swarm optimization based ANN. Results show that proposed GOA-ANN based plant leaf classification system is a promising technique for small image datasets.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.598-603
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• 2003

During the last ten years, the need has been increased for reducing maintenance cost for aged equipments and ensuring safety, efficiency and profitability of petrochemical and refinery plants. RBI (Risk Based Inspection) methodology is one of the most promising technologies satisfying the need in the field of integrity management. In this study, a user-friendly software, realRBI for RBI based on the API 581 code was developed and a quantitative analysis was performed for over 500 equipments in a domestic plant whose operating time reaches about 13 years. Current risks for each equipment parts were evaluated and risk based prioritization were determined as a conclusion.

• Corrosion Science and Technology
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• 제11권5호
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• pp.179-183
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• 2012

As one of promising solutions to overcome high oil price and energy crisis, the construction market of high value-added LNG plants is spotlighted world widely. The purpose of this study is to introduce LNG-RBI system to develop risk assessment technology with RAM(Reliability, Availability, Maintainability) modules against overseas monopolization. After analyzing relevant specific features and their technical levels, risk assessment program, non-destructive reliability evaluation strategy and safety criteria unification class are derived as core technologies. These IT-based convergence technologies can be used for enhancement of LNG plant efficiency, in which the modular parts are related to a system with artificial optimized algorithms as well as diverse databases of facility inspection and diagnosis fields.

• 한국산학기술학회논문지
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• 제16권9호
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• pp.6297-6304
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• 2015

우리나라 최초의 원자력발전소인 고리 원전 1호기의 폐쇄가 결정됨에 따라 원전 해체가 화두가 되고 있다. 원전 해체는 우리나라에서 한번도 경험해 보지 못한 일로 해체 과정도 어렵고 시간도 많이 소요된다. 그 일부분인 해체물량 또한 파악이 어렵다. 본 연구에서는 최근 건설산업에 많이 활용되고 있는 BIM 기술을 원전 해체 물량산출에 활용할 수 있는 방안을 제시하였다. 그 결과, 원전 해체 공법선정 및 공정 확립, BIM 모델링 환경 준비, 작업분류체계 구축, 객체분류체계 구축, BIM 통합모델 작성, BIM 객체에 물량 속성 배분 등의 방안을 제시하였다. 제시한 방안은 영구정지 대상 원전이 집중적으로 발생하는 시기부터 유용하게 활용될 수 있다. 이에 기반한 기술확보를 통해 나아가 해외 원전 해체 사업 수주에도 유리하게 작용할 것으로 기대된다.

• 식물조직배양학회지
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• 제27권5호
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• pp.387-393
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• 2000

The process by which Agrobacterium tumefaciens genetically transforms plants involves a complex series of reactions communicated between the pathogen and the plants. To identify plant factors involved in agrobacterium-mediated plant transformation, a large number of T-DNA inserted Arabidopsis thaliana mutant lines were investigated for susceptibility to Agrobacterium infection by using an in vitro root inoculation assay. Based on the phenotype of tumorigenesis, twelve T-DNA inserted Arabidopsis mutants(rat) that were resistant to Agrobacterium transformation were found. Three mutants, rat1, rat3, and rat4 were characterized in detail. They showed low transient GUS activity and very low stable transformation efficiency compared to the wild-type plant. The resistance phenotype of rat1 and rats resulted from decreased attachment of Agrobacterium tumefaciens to inoculated root explants. They may be deficient in plant actors that are necessary for bacterial attachment to plant cells. The disrupted genes in rat1, rat3, and rat4 mutants were coding a arabinogalactan protein, a likely cell wall protein and a cellulose synthase-like protein, respectively.