• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.490-495
• /
• 1992

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming cooperates with neural identification network is used to generate the optimum control law for the complicate continuous/batch chemical reactor systems that have inherent nonlinear dynamics. Based on our approach, we developed a neural model predictive controller(NMPC) which shows excellent performances on nonlinear, model-plant mismatch cases of chemical reactor systems.

• Biotechnology and Bioprocess Engineering:BBE
• /
• 제8권4호
• /
• pp.257-262
• /
• 2003

A straightforward and effective method is presented for immobilizing enzymes on a microchip platform without chemically modifying a micro-channel or technically microfabricating a column reactor and fluid channel network. The proposed method consists of three steps: the reconstitution of a nitrocellulose (NC) membrane on a plane substrate without a channel network, enzyme immobilization on the NC membrane, and the assembly of another substrate with a fabricated channel network. As a result, enzymes can be stably and efficiently immobilized on a microchip. To evaluate the proposed method, two kinds of enzymatic reaction are applied: a sequential two-step reaction by one enzyme, alkaline phosphatase, and a coupled reaction by two enzymes, glucose oxidase and peroxidase, for a glucose assay.

• 대한기계학회논문집B
• /
• 제36권2호
• /
• pp.225-232
• /
• 2012

희박 예혼합 가스터빈 연소기에서 배출되는 NOx, CO 와 같은 오염물질을 예측하기 위해서 화학반응기 네트워크 모델을 개발했다. 본 연구에서는 CHEMKIN 코드와 4 가지 NO 생성 메커니즘을 포함한 GRI 3.0 메탄-공기 연소 메커니즘을 이용해서 가스터빈의 부하조건을 변화시키며 NOx 및 CO 배출의 예측을 수행하였다. 모델의 검증을 위해서 계산된 결과를 모사연소기의 실험 데이터와 비교하였다. 여러부하조건에 따른 4 가지 NO 경로의 기여도를 조사하였다. 또한 인젝터의 질량유동 및 당량비의 불균일성이 NOx 배출이 끼치는 영향을 고찰하고 10ppm 이하의 저 NOx 연소기 개발을 위한 저감 방법을 제안했다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
• /
• pp.899-902
• /
• 1993

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming combined with neural identification network is used to generate the optimum control law for complex continuous chemical reactor systems that have inherent nonlinear dynamics. The neural model predictive controller (MNPC) shows good performances and robustness. To whom all correspondence should be addressed.

• 대한기계학회논문집B
• /
• 제35권12호
• /
• pp.1257-1264
• /
• 2011

희박예혼합 가스터빈 연소기에 대한 3 차원 RANS 해석을 수행하였으며 PCFM(Partially Premixed Coherent Flame Model) 화염면적밀도 생성항 상수의 보정을 통하여 희박연소조건을 모사하였다. PCFM 에서 계산된 화염면적밀도에 의해 층류 예혼합 화염의 전파를 예측하고 불균일하게 분포한 기연 가스의 물성을 평형 가정에 따라 예측하였다. 복사와 대류 열전달을 모사하기 위해 냉각 조건으로서 실험과의 비교를 통해 결정된 열유속을 적용하였다. 이러한 3 차원 해석 결과를 바탕으로 파일럿 노즐과 메인 노즐에 분배되는 연료량 비에 대한 민감도 조사를 수행하였으며 CRN(Chemical Reactor Network)을 구성하여 NOx 배출량을 예측하고 측정값과 비교 분석하였다.

• Korean Chemical Engineering Research
• /
• 제61권2호
• /
• pp.328-339
• /
• 2023

Methanol steam reforming (MSR) is a promising method for hydrogen supplying as a critical step in hydrogen fuel cell commercialization in mobile applications. Modelling and understanding of the reactor behavior is an attractive research field to develop an efficient reformer. Three-layer feed-forward artificial neural network (ANN) and Box-Behnken design (BBD) were used to modelling of MSR process using the Cu-SiO₂ aerogel catalyst. Furthermore, impacts of the basic operational variables and their mutual interactions were studied. The results showed that the most affecting parameters were the reaction temperature (56%) and its quadratic term (20.5%). In addition, it was also found that the interaction between temperature and Steam/Methanol ratio is important on the MSR performance. These models precisely predict MSR performance and have great agreement with experimental results. However, on the basis of statistical criteria the ANN technique showed the greater modelling ability as compared with statistical BBD approach.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2003년도 추계학술대회
• /
• pp.1174-1179
• /
• 2003

Cast austenitic stainless steel is used for several components, such as primary coolant piping, elbow, pump casing and valve bodies in light water reactors. These components are subject to thermal aging at the reactor operating temperature. Thermal aging results in spinodal decomposition of the delta-ferrite leading to increased strength and decreased toughness. This study shows that ferrite content can be predicted by use of the artificial neural network. The neural network has trained learning data of chemical components and ferrite contents using backpropagation learning process. The predicted results of the ferrite content using trained neural network are in good agreement with experimental ones.

• 대한기계학회논문집A
• /
• 제28권4호
• /
• pp.460-466
• /
• 2004

Cast austenitic stainless steel is used for several components, such as primary coolant piping, elbow, pump casing and valve bodies in light water reactors. These components are subject to thermal aging at the reactor operating temperature. Thermal aging results in spinodal decomposition of the delta-ferrite leading to increased strength and decreased toughness. This study shows that ferrite content can be predicted by use of the artificial neural network. The neural network has trained teaming data of chemical components and ferrite contents using backpropagation learning process. The predicted results of the ferrite content using trained neural network are in good agreement with experimental ones.

• 산업공학
• /
• 제24권2호
• /
• pp.156-163
• /
• 2011

The radiopharmaceutical synthesis for PET (positron emission tomography) is composed of chemical reactions using automated synthetical equipment. Due to the radioactive material, the automated equipment is being frequently developed to replace human operators who conduct dangerous, repetitive and dexterous operations. As to operation, the manipulating program is commonly coded using the spread sheet while the whole actuators are mapped in every step. The process map (program) is changed according to such parameters as temperature of reactor, keeping time, mixture sequence and amount of reagent. In cases of customizing the automated synthetical equipment or developing the new radiopharmaceuticals, lots of experiments should be conducted and the programming mistake is not allowed as it can lead abnormal control of the equipment to leak the radioactive materials. The exact process map has depended on trial and error manner. Thus, this study developed the methodology to tabulate the synthetical process to convert the process map automatically while the synthetical module formation is represented by a network model. The proposed method is validated using the actual radiopharmaceutical synthetical procedure.

• Korean Chemical Engineering Research
• /
• 제52권6호
• /
• pp.720-726
• /
• 2014

PEMFC(Proton Exchange Membrane Fuel Cell) 차량은 미래 청정수송기관으로 각광받고 있지만 수소스테이션의 인프라부족으로 현재는 수소를 공급해주는 연료개질기를 함께 장착하여 구동하여야 한다. 탄화수소연료로부터 수소를 생산하는 연료개질기를 대상으로 다양한 연구가 진행되어왔는데 기존연구에서는 열적중립 조건의 ATR(Auto-Thermal Reformer) 반응기에 대해 집중적으로 분석하거나 공정최적화부문에서 최대수소생산을 목표로 주로 열효율을 목적함수로 설정하여 평가해 왔다. 본 연구에서는 100 kW PEMFC용 연료개질기를 대상으로 간단한 소형시스템을 얻기 위해 외부 유틸리티가 필요없는 단열열교환망으로 구성된 조건에서 기존 열효율이 아닌 수소효율을 새로이 정의하여 가솔린, LPG, 디젤 각 연료에 대해 최적운전조건을 도출하였다. 가솔린의 경우 기존 비교문헌보다 9.43% 연료절감효과를 얻음으로써 제안한 목적함수의 타당성을 입증하였고, 추가적으로 수소효율 및 열교환량, 열교환면적에 대한 민감도 분석을 실시하였다. 마지막으로 제안한 시스템을 한국시장에 적용할 경우 LPG 연료를 사용하는 연료개질기가 가장 경제적임을 알 수 있었다.