MKMinjin Kim
Minjin Kim
*This is an algorithmically generated author record based on publicly available information.
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Minjin Kim has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Chonghun Han
Pohang University of Science and Technology
2 shared publications Byungwoo Lee
1 shared publicationJinsuk Lee
1 shared publicationKun Lo
1 shared publicationWoo Kyoung Kim
1 shared publication- Young-Hak Lee
Postdoctoral Researcher, Automation and Systems Research Institute and School of Chemical and Biological Engineering, Seoul National Univ., San 56-1, Shillim-dong, Kwanak-gu, Seoul 151-742, Korea
1 shared publication
Latest Publications
- 1 June 2005
- Published by American Society of Civil Engineers (ASCE) in Journal of Environmental Engineering
- Vol. 131 (6) , 961-970
Application of Multivariate Statistical Models to Prediction of NOx Emissions from Complex Industrial Heater Systems
Industrial fired heaters are a major source of nitrogen oxides ( ). On-line analyzers, kinetic models with computational fluid dynamics, and empirical predictive models have been developed to monitor emissions and analyze excessive emissions. However, previous approaches have been applied only to single heater systems, not to large-scale multiheater systems. This paper proposes a hierarchical monitoring and diagnosis procedure to monitor emissions from large-scale multiheater systems and to identify the root causes of excessive emissions as well as heater malfunctions. The procedure provides a functional three-layer hierarchy: (1) prediction of concentrations; (2) estimation of the influence of individual heaters on the predicted ; and (3) identification of the root causes by examining the detailed contributions of process variables to variations of the heater identified in step 2 as being the principal source of . An integrated multiblock partial least-squares (PLS) model, created by combining standard PLS and multiblock PLS, is employed to predict the emissions and estimate the influences of the heaters on the emissions. The validity of the proposed method is demonstrated through its application in two case studies.- 1 June 2005
- Published by American Society of Civil Engineers (ASCE) in Journal of Environmental Engineering
- Vol. 131 (6) , 961-970
Application of Multivariate Statistical Models to Prediction of NOx Emissions from Complex Industrial Heater Systems
Industrial fired heaters are a major source of nitrogen oxides ( ). On-line analyzers, kinetic models with computational fluid dynamics, and empirical predictive models have been developed to monitor emissions and analyze excessive emissions. However, previous approaches have been applied only to single heater systems, not to large-scale multiheater systems. This paper proposes a hierarchical monitoring and diagnosis procedure to monitor emissions from large-scale multiheater systems and to identify the root causes of excessive emissions as well as heater malfunctions. The procedure provides a functional three-layer hierarchy: (1) prediction of concentrations; (2) estimation of the influence of individual heaters on the predicted ; and (3) identification of the root causes by examining the detailed contributions of process variables to variations of the heater identified in step 2 as being the principal source of . An integrated multiblock partial least-squares (PLS) model, created by combining standard PLS and multiblock PLS, is employed to predict the emissions and estimate the influences of the heaters on the emissions. The validity of the proposed method is demonstrated through its application in two case studies.- 1 June 2001
- Published by Elsevier in IFAC Proceedings Volumes
- Vol. 34 (25) , 359-364
Soft sensor design for melt index estimation of a polypropylene process with multiple operation modes
- 1 June 2001
- Published by Elsevier in IFAC Proceedings Volumes
- Vol. 34 (25) , 359-364
Soft sensor design for melt index estimation of a polypropylene process with multiple operation modes