대기오염에 있어서 오존형성에 관한 모사 및 모델인식

여영구,오세천 漢陽大學校 環境工學硏究所 1998 環境科學論文集 Vol.19 No.-

광화학적 대기오염에 있어서의 오존형성을 규명하기 위하여 빛의 강도, 반응물의 초기 농도 그리고 온도 및 습도의 영향을 고려한 반응 모델식을 이용하여 ?? 시스템에 대한 모사연구를 수행하였으며 습도의 영향을 고려하기 위하여 H₂O에 의한 N₂O5의 손실반응을 고려하였다. 모사결과는 smog-chamber 실험결과와 잘 일치하였다. 또한 본 연구에서는 오존 발생 예측 시스템의 개발에 있어서 쌍일차 모델의 성능 및 효용성을 확인하기 위하여 오존 발생량에 대하여 쌍일차 모델 및 선형 모델을 이용한 모델인식 모사실험을 하였다. 모델인식에 있어서는 ARMA 모델을 사용하였으며 모델의 파라미터를 평가하기 위하여 방정식 오차법에 근거한 연속 파라미터 평가 알고리즘을 적용하였다. 모델인식 실험결과로부터 쌍일차 모델을 이용한 오존 발생량과 본 연구에서 개발한 모사기로부터 얻은 오존 발생량이 거의 일치함을 알 수 있었다. The simulation of ?? system was performed by using a detailed reaction model in order to characterize ozone formation in photochemical air pollution. To consider the effect of humidity the loss reactions of ?? by H₂O were included in the model developed in the present study. The results of simulations showed a good agreement with smog-chamber experimental data. To verify the performance and effectiveness of bilinear model for the development of ozone prediction system the simulation experiments of the model identification for ozone formation were performed by using bilinear and linear models ARMA model was used in the model identification. A recursive parameter estimation algorithm based on an equation error method was used to estimate parameters of model. From the results of model identification experiment, the ozone formation by bilinear model showed good agreement with the ozone formation from the simulator developed in this study.

통계적 방법을 이용한 오존 형성의 예측

여영구,손상현,오세천 漢陽大學校 環境工學硏究所 1999 環境科學論文集 Vol.20 No.-

통계적 방법을 이용하여 오존 형성의 예측에 관한 연구를 수행하였다. 통계적 방법으로는 파라미터 평가 방법과 인공신경 회로망 방법이 적용되었다. 파라미터 평가 방법에는 실시간 파라미터를 평가하기 위하여 ELS 및 RML 방법이 사용되었으며 오존 형성의 모델로는 ARMAX 모델을 사용하였다. 또한 3층 구조를 갖는 인공신경 회로망 방법을 이용하여 오존 형성의 예측 시험을 수행하였으며 본 연구에 사용된 통계적 방법의 성능을 평가하기 위하여 오존 형성의 예측결과를 실제자료와 비교 분석을 하였다. 실제 자료와의 비교를 통하여 파라미터 평가 방법 및 인공신경 회로망 방법에 근거한 예측방법이 제한된 예측 구간 내에서 만족할 만한 성능을 보임을 확인할 수 있었다. The prediction of ozone formation was studied using the stochastic method, Parameter estimation method and artificial neural network(ANN) method were employed in the stochastic scheme. In the parameter estimation method, extended least squares(ELS) method and recursive maximum likelihood(RML) were used to achieve the real time parameter estimation. Autoregressive moving average model with external input(ARMAX)was used as the ozone formation model for the parameter estimation method, ANN with 3 layers was also tested to predict the ozone formation. To demonstrate the performance of the ozone formation prediction schemes used in this work, the prediction results of ozone formation were compared to the real data. From the comparison it was found that the prediction schemes based on the parameter estimation method and ANN method show an acceptable accuracy with limited prediction horizon.

Failure Cost와 Life Cycle Cost를 고려한 연속시스템에 대한 최적 장치 선택에 관한 연구

진상화,김용하,송희열,여영구,김인원 한국안전학회 2004 한국안전학회지 Vol.19 No.4

In this study, the required life cycle cost is evaluated in consideration of the equipment's availability during its life cycle. In order to meet the maximum availability required by the process, the failure cost and life cycle cost is assessed, The optimal equipment selection method is presented according to the analysis of the failure cost and life cycle cost. For the systems in which equipments are connected serially, the optimal equipments are selected by minimizing the life cycle cost and satisfying the required system availability goal. In addition, the selection methods and life cycle cost are analyzed according to the cost variation of the equipment. By using the life cycle evaluation procedure, the failure cost and maintenance cost needed during the life cycle of the equipment can be presented.

Application of Partitioning and Tearing Techniques to Sulfolane Extraction Plant

Yeo, Yeong Koo,Cho, Ki Won,Kim, Myung Kil 한국화학공학회 1999 Korean Journal of Chemical Engineering Vol.16 No.4

For effective flowsheet-level calculation of a complex chemical plant, the use of suitable partitioning and tearing techniques is inevitable. The partitioning and tearing techniques based on the reachability matrix and the decomposition algorithm were applied to model and simulate a sulfolane extraction plant. Basic concepts were first exploited towards a general representation for the modeling and simulation of the sulfolane extraction process. Six process units, which consist of the sulfolane extraction plant, were modeled first and partitioning and tearing techniques were employed to model and simulate the whole extraction plant. The Inside-Out method and the sequential-modular approach were used in the modeling and simulation. Results of simulations showed good agreement with plant operation data.

Prediction of Air Pollutants by Using an Artifical Neural Network

Yeo, Yeong Koo,Oh, Sea Cheon,Sohn, Sang Hyun 한국화학공학회 1999 Korean Journal of Chemical Engineering Vol.16 No.3

The purpose of this study is to predict the amount of primary air pollution substances in Seoul, Korea. An artificial neural network (ANN) was used as a prediction method. The ANN with three layers is learned with past data, and the concentrations of air pollutants are predicted based on the pre-learned weights. The error back propagation method that has a powerful application to various fields was adopted as the learning rule. The concentrations of air pollutants from one to six hours in the future were predicted with the ANN. To verify the performance of the prediction method used in the present study, the predicted concentrations of air pollutants were compared with the measured data. From the comparison, it was found that the prediction method based on the ANN gives an acceptable accuracy for the limited prediction horizon.

Bilinear Model Predictive Control Methods for Chemical Processes

Yeong-Koo Yeo,Sea Cheon Oh,Dennis C. Williams 제어로봇시스템학회 1996 제어로봇시스템학회지 Vol.2 No.1

A Study on the Adaptive Predictive Control Method for Multivariable Bilinear Processes

Yeo, Yeong Koo,Oh, Sea Cheon 한국화학공학회 1995 NICE Vol.13 No.6

A predictive control method for multivariable bilinear processes is derived based on ARMA model to identify bilinear process models, we use simple equaticm error method extended to multivariable system. We can obtain the adaptive predictive controller for mutivariable bilinear processes by incorporation of the identification algorithm. Offset compensator is provided to correct reef far the effects of unmeasured disturbances and model inaccuracies. A filter with singled parameter is used to correct fur the effects of an incorrect model. Results of simulation on multivariable bilinear processes show that the proposed control method has satisfactory performance.

Control of pH Processes Based on the Genetic Algorithm

Yeo, Yeong-Koo,Kwon, Tae-In 한국화학공학회 2004 Korean Journal of Chemical Engineering Vol.21 No.1

In this work, we propose a PID control strategy based on the genetic algorithm coupled with cubic spline interpolation method for the control of pH processes. The control scheme proposed in the present work consists of closed-loop identification based on the genetic algorithm and cubic spline method. First, we compute the parameters (K_(?), τ_(?), τ_(?)) of the PID controller using relay feedback and apply these parameters to control the pH Process. Then approximate linear models corresponding to each pH range are obtained by the close-loop identification based on closed-loop operation data. The optimal parameters of the PID controller at each pH region are then computed by using the genetic algorithm. From numerical simulations and control experiments we could achieve better control performance compared to the conventional fixed gain PID control method.

Modeling and Simulation of Wet-end White Water System in the Paper Mill

Yeo, Yeong-Koo,Yi, Sung Chul,Ryu, Jae Yong,Kang, Hong 한국화학공학회 2004 Korean Journal of Chemical Engineering Vol.21 No.2

A dynamic model representing the wet-end of a paper mill is developed to characterize its dynamic behavior. The model is based on the mass balance relationships written for the simplified wet-end white water network. The dynamic response of the wet-end is influenced both by the white water volume and by the level of wire retention. Effects of key manipulated variables such as the thick stock flow rate, the ash flow rate and the retention aid rate on the major controlled variables are analyzed numerical simulations. It can be said that the consistency of the model with plant data seems to be reasonably good and can be used as a tool for plant analysis and control.

Modeling and Simulation of a Nitric Acid Recovery Process

Yeo, Yeong Koo,Oh, Sea Cheon,Oh, Young Se 한국화학공학회 1995 NICE Vol.13 No.5

A nitric acid recovery process using composite distillation columns was modeled and simulated. The composite distillation columns consist of a multistage vacuum tower and an atmospheric pressure tower half of which consists of packed bed. The vacuum tower and the atmospheric pressure tower were modeled by using equilibrium stage method and non-equilibrium stage method respectively. The required thermodynamic properties for nitric acid solution were obtained from correlations based on experimental data. Results of simulations showed good agreement with actual plant data. From the results of simulations it was found that the upper half of the atmospheric pressure column and the vacuum column, consisting of plate column, can be modeled using equilibrium model, but the lower half of the atmospheric pressure column, which are packed parts, can be modeled effectively using non-equilibrium model. The non-equilibrium model developed in the present study showed good agreement with actual operation data.