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Multiple linear regression modelling of pulp and handsheet properties based on fiber morphology measurements and process data
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Chemical Sciences (from 2013).
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Chemical Sciences (from 2013).ORCID iD: 0000-0002-5864-4576
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Chemical Sciences (from 2013).
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Health Sciences (from 2013).ORCID iD: 0000-0002-9739-7184
2020 (English)In: BioResources, ISSN 1930-2126, E-ISSN 1930-2126, Vol. 15, no 1, p. 654-676Article in journal (Refereed) Published
Abstract [en]

A multiple regression model was evaluated to predict pulp and handsheet properties including z-directional tensile strength (z-strength) and Scott bond values. One hypothesis that was central for the model evaluation was that the crill content, as measured with ultraviolet and infrared lights, would improve the statistical models. A chemi-thermomechanical pulp (CTMP) mill designed with two parallel primary refining lines and a reject refiner was the basis for this study, and all process data and pulp samples were gathered from the specific process. Pulp was extracted from the process for an extended period from a position after the latency chest (primary refined pulp) and from the pulp-stream exiting the mill to the board machine (accept pulp). The crill content was positively correlated to the z-strength of the accept pulp, explaining 55% of the variance with a linear regression model with the drill content as the sole predictor. The estimation model of the z-strength of accept pulp was based on a combination of the crill content, freeness, fibril perimeter for longer fibers, and mean kink angle, and resulted in an R-2 of 0.79. When applying cross-validation to determine the predictive model performance, the highest R-2 obtained was 0.67. This latter model included the crill content, fibril perimeter, and mean kink angle as predictors.

Place, publisher, year, edition, pages
NORTH CAROLINA STATE UNIV DEPT WOOD & PAPER SCI , 2020. Vol. 15, no 1, p. 654-676
Keywords [en]
CTMP, Fiber morphology, Multiple regression modelling, Handsheet, Z-strength, Scott bond, Crill
National Category
Chemical Engineering
Research subject
Chemical Engineering; Public Health Science
Identifiers
URN: urn:nbn:se:kau:diva-77086DOI: 10.15376/biores.15.1.654-676ISI: 000511129100050OAI: oai:DiVA.org:kau-77086DiVA, id: diva2:1397166
Funder
Stora EnsoAvailable from: 2020-02-27 Created: 2020-02-27 Last updated: 2020-03-05

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Ekbåge, DanielNilsson, LarsHåkansson, HelenaLin, Ping-I

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