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Modelling the Material Resistance of Wood—Part 1: Utilizing Durability Test Data Based on Different Reference Wood Species
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Modelling the Material Resistance of Wood—Part 2: Validation and Optimization of the Meyer-Veltrup Model

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Wood Biology and Wood Products, University of Goettingen, 37077 Goettingen, Germany
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Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forests and Forest Resources, Wood Technology, 1431 Ås, Norway
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Department of Wood Science and Technology, Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia
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CATAS, 33048 San Giovanni al Natisone, Italy
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LJ Cookson Consulting, Warrandyte, VIC 3113, Australia
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Norwegian Institute of Wood Technology (NTI), 0314 Oslo, Norway
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VTT Technical Research Centre of Finland, 02044 Espoo, Finland
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Department of Agriculture and Fisheries, Forestry Science, Ecosciences Precinct, Brisbane, QLD 4102, Australia
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Latvian State Institute of Wood Chemistry, 1006 Riga, Latvia
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Institut für Holztechnologie Dresden (IHD), 01217 Dresden, Germany
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Danish Technological Institute (DTI), 2630 Taastrup, Denmark
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Thuenen Institute of Wood Research, 21031 Hamburg, Germany
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Heinz-Piest-Institute of Craftsmen Techniques, 30167 Hannover, Germany
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National Centre for Timber Durability and Design Life (USC), University of the Sunshine Coast, Brisbane, QLD 4102, Australia
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CNR IBE, Italian National Research Council, Institute of Bioeconomy, 50019 Sesto Fiorentino, Italy
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Department of Wood Science and Engineering, Oregon State University, Corvallis, OR 97331, USA
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Faculty of Wood Sciences and Technology, Technical University in Zvolen, 96001 Zvolen, Slovakia
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SCION, Rotorua 3010, New Zealand
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FP Innovations, Vancouver, BC V6T 1Z4, Canada
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Natural Resources Institute Finland (LUKE), 57200 Savonlinna, Finland
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Research Institute of Sweden (RISE), 50462 Borås, Sweden
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Faculty of Resource Science & Technology, Universiti Malaysia Sarawak (Unimas), Kota Samarahan Sarawak 94300, Malaysia
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Building Research Establishment, Garston, Watford WD25 9XX, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Angela Lo Monaco
Forests 2021, 12(5), 576; https://doi.org/10.3390/f12050576
Received: 29 March 2021 / Revised: 15 April 2021 / Accepted: 16 April 2021 / Published: 6 May 2021
(This article belongs to the Special Issue Modeling the Performance of Wood and Wood Products)
Service life planning with timber requires reliable models for quantifying the effects of exposure-related parameters and the material-inherent resistance of wood against biotic agents. The Meyer-Veltrup model was the first attempt to account for inherent protective properties and the wetting ability of wood to quantify resistance of wood in a quantitative manner. Based on test data on brown, white, and soft rot as well as moisture dynamics, the decay rates of different untreated wood species were predicted relative to the reference species of Norway spruce (Picea abies). The present study aimed to validate and optimize the resistance model for a wider range of wood species including very durable species, thermally and chemically modified wood, and preservative treated wood. The general model structure was shown to also be suitable for highly durable materials, but previously defined maximum thresholds had to be adjusted (i.e., maximum values of factors accounting for wetting ability and inherent protective properties) to 18 instead of 5 compared to Norway spruce. As expected, both the enlarged span in durability and the use of numerous and partly very divergent data sources (i.e., test methods, test locations, and types of data presentation) led to a decrease in the predictive power of the model compared to the original. In addition to the need to enlarge the database quantity and improve its quality, in particular for treated wood, it might be advantageous to use separate models for untreated and treated wood as long as the effect of additional impact variables (e.g., treatment quality) can be accounted for. Nevertheless, the adapted Meyer-Veltrup model will serve as an instrument to quantify material resistance for a wide range of wood-based materials as an input for comprehensive service life prediction software. View Full-Text
Keywords: biological durability; dose-response model; fungal decay; moisture dynamics; moisture performance; service life prediction; water uptake and release; wetting ability biological durability; dose-response model; fungal decay; moisture dynamics; moisture performance; service life prediction; water uptake and release; wetting ability
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MDPI and ACS Style

Brischke, C.; Alfredsen, G.; Humar, M.; Conti, E.; Cookson, L.; Emmerich, L.; Flæte, P.O.; Fortino, S.; Francis, L.; Hundhausen, U.; Irbe, I.; Jacobs, K.; Klamer, M.; Kržišnik, D.; Lesar, B.; Melcher, E.; Meyer-Veltrup, L.; Morrell, J.J.; Norton, J.; Palanti, S.; Presley, G.; Reinprecht, L.; Singh, T.; Stirling, R.; Venäläinen, M.; Westin, M.; Wong, A.H.H.; Suttie, E. Modelling the Material Resistance of Wood—Part 2: Validation and Optimization of the Meyer-Veltrup Model. Forests 2021, 12, 576. https://doi.org/10.3390/f12050576

AMA Style

Brischke C, Alfredsen G, Humar M, Conti E, Cookson L, Emmerich L, Flæte PO, Fortino S, Francis L, Hundhausen U, Irbe I, Jacobs K, Klamer M, Kržišnik D, Lesar B, Melcher E, Meyer-Veltrup L, Morrell JJ, Norton J, Palanti S, Presley G, Reinprecht L, Singh T, Stirling R, Venäläinen M, Westin M, Wong AHH, Suttie E. Modelling the Material Resistance of Wood—Part 2: Validation and Optimization of the Meyer-Veltrup Model. Forests. 2021; 12(5):576. https://doi.org/10.3390/f12050576

Chicago/Turabian Style

Brischke, Christian, Gry Alfredsen, Miha Humar, Elena Conti, Laurie Cookson, Lukas Emmerich, Per O. Flæte, Stefania Fortino, Lesley Francis, Ulrich Hundhausen, Ilze Irbe, Kordula Jacobs, Morten Klamer, Davor Kržišnik, Boštjan Lesar, Eckhard Melcher, Linda Meyer-Veltrup, Jeffrey J. Morrell, Jack Norton, Sabrina Palanti, Gerald Presley, Ladislav Reinprecht, Tripti Singh, Rod Stirling, Martti Venäläinen, Mats Westin, Andrew H.H. Wong, and Ed Suttie. 2021. "Modelling the Material Resistance of Wood—Part 2: Validation and Optimization of the Meyer-Veltrup Model" Forests 12, no. 5: 576. https://doi.org/10.3390/f12050576

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