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Mathematical and Computer Modelling of Dynamical Systems
Methods, Tools and Applications in Engineering and Related Sciences
Volume 15, 2009 - Issue 5: Selected Papers from the 5th Mathmod Conference, February 7th-10th 2006 at Vienna University of Technology
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Articles

Use of modelling and simulation in the pulp and paper industry

A. Blanco Chemical Engineering Department, Complutense University of Madrid, SpainCorrespondence[email protected]
,
E. Dahlquist Department of Public Technology, Mälardalen University, Vasteras, Sweden
,
J. Kappen Simulation and Sensor Technology, PTS, Munich, Germany
,
J. Manninen Process Chemistry, VTT, Espoo, Finland
,
C. Negro Chemical Engineering Department, Complutense University of Madrid, Spain
&
R. Ritala Automation Sciences and Engineering, Tampere University of Technology, Finland
Pages 409-423 | Accepted 09 Sep 2009, Published online: 12 Nov 2009

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B. Talebjedi, T. Laukkanen, H. Holmberg, E. Vakkilainen & S. Syri. (2021) Energy simulation and variable analysis of refining process in thermo-mechanical pulp mill using machine learning approach. Mathematical and Computer Modelling of Dynamical Systems 27:1, pages 562-585.
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Articles from other publishers (14)

Lorenzo Tuissi, Daniele Ravasio, Stefano Spinelli & Andrea Ballarino. (2023) Neural Network Modeling of the Refining Motor Load for Medium-Density Fibreboard Production. Neural Network Modeling of the Refining Motor Load for Medium-Density Fibreboard Production.
M. Alquraish. (2022) Modeling and Simulation of Manufacturing Processes and Systems: Overview of Tools, Challenges, and Future Opportunities. Engineering, Technology & Applied Science Research 12:6, pages 9779-9786.
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Dong Gu Han & Jung Myoung Lee. (2022) Optimization of a Multiple-Effect Evaporator Process by Simulation. Journal of Korea Technical Association of The Pulp and Paper Industry 54:3, pages 12-22.
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V. V. S. Vijaya Krishna, N. Pappa & S. P. Joy Vasantharani. (2022) Realization of Deep Learning Based Embedded Soft Sensor for Bioprocess Application. Intelligent Automation & Soft Computing 32:2, pages 781-794.
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Robert Pujan & Heinz A. Preisig. 2022. 32nd European Symposium on Computer Aided Process Engineering. 32nd European Symposium on Computer Aided Process Engineering 295 300 .
Fredrik Bengtsson, Anders Karlström & Torsten Wik. (2021) On the modeling of pulp properties in CTMP processes. Nordic Pulp & Paper Research Journal 36:2, pages 234-248.
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Seppo Sierla, Lotta Sorsamäki, Mohammad Azangoo, Antti Villberg, Eemeli Hytönen & Valeriy Vyatkin. (2020) Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant. Applied Sciences 10:19, pages 6959.
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Om Prakash Verma, Gaurav Manik & Sushant Kumar Sethi. (2019) A comprehensive review of renewable energy source on energy optimization of black liquor in MSE using steady and dynamic state modeling, simulation and control. Renewable and Sustainable Energy Reviews 100, pages 90-109.
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Mika Liukkonen, Jukka Silvennoinen & Yrjö Hiltunen. (2018) Toward better control of water-intensive processes: Case study in fluting manufacturing. IFAC-PapersOnLine 51:2, pages 683-688.
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E. Dahlquist. 2015. Reference Module in Earth Systems and Environmental Sciences. Reference Module in Earth Systems and Environmental Sciences.
Mika Strömman, Ilkka Seilonen & Kari Koskinen. 2014. Simulation and Modeling Methodologies, Technologies and Applications. Simulation and Modeling Methodologies, Technologies and Applications 291 303 .
Xiaoyan Ji, Joakim Lundgren, Chuan Wang, Jan Dahl & Carl-Erik Grip. (2012) Simulation and energy optimization of a pulp and paper mill ? Evaporation plant and digester. Applied Energy 97, pages 30-37.
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Xiaoyan Ji, Joakim Lundgren, Chuan Wang, Jan Dahl & Carl-Erik Grip. Simulation and Optimization of Steam Generation in a Pulp and Paper Mill. Simulation and Optimization of Steam Generation in a Pulp and Paper Mill.
Helene Lidestam & Mikael Rönnqvist. (2011) Use of Lagrangian decomposition in supply chain planning. Mathematical and Computer Modelling 54:9-10, pages 2428-2442.
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