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Use of combined physical and statistical models for online applications in the pulp and paper industry
Mälardalens högskola, Akademin för ekonomi, samhälle och teknik.ORCID-id: 0000-0001-8191-4901
Mälardalens högskola, Akademin för ekonomi, samhälle och teknik.
Mälardalens högskola, Akademin för ekonomi, samhälle och teknik.ORCID-id: 0000-0001-9230-1596
Mälardalens högskola, Akademin för ekonomi, samhälle och teknik.ORCID-id: 0000-0002-7233-6916
2009 (engelsk)Inngår i: Mathematical and Computer Modelling of Dynamical Systems, ISSN 1387-3954, E-ISSN 1744-5051, Vol. 15, nr 5, s. 425-434Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

This paper discusses the accuracy of different types of models. Statistical models are based on process data and/or observations from lab measurements. This class of models are called black box models. Physical models use physical relationships to describe a process. These are called white box models or first principle models. The third group is sometimes called grey box models, being a combination of black box and white box models. Here we discuss two examples of model types. One is a statistical model where an artificial neural network is used to predict NOx in the exhaust gases from a boiler at Mälarenergi AB in Västerås, Sweden. The second example is a grey box model of a continuous digester. The digester model includes mass balances, energy balances, chemical reactions and physical geometrical constraints to simulate the real digester. We also propose that a more sophisticated model is not required to increase the accuracy of the predicted measurements.

sted, utgiver, år, opplag, sider
Taylor & Francis , 2009. Vol. 15, nr 5, s. 425-434
Emneord [en]
statistical models; physical models; pulp digester
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Identifikatorer
URN: urn:nbn:se:hig:diva-38264DOI: 10.1080/13873950903375403ISI: 000274741800003Scopus ID: 2-s2.0-75349089565OAI: oai:DiVA.org:hig-38264DiVA, id: diva2:1649113
Tilgjengelig fra: 2009-11-29 Laget: 2022-04-03bibliografisk kontrollert

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Avelin, AndersDotzauer, ErikDahlquist, Erik

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Mathematical and Computer Modelling of Dynamical Systems

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