Modeling the material resistance of wood—part 2: Validation and optimization of the meyer-veltrup model
Number of Authors: 282021 (English)In: Forests, E-ISSN 1999-4907, Vol. 12, no 5, article id 576
Article in journal (Refereed) Published
Abstract [en]
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. © 2021 by the authors.
Place, publisher, year, edition, pages
MDPI AG , 2021. Vol. 12, no 5, article id 576
Keywords [en]
Biological durability, Dose-response model, Fungal decay, Moisture dynamics, Moisture performance, Service life prediction, Water uptake and release, Wetting ability, Decay (organic), Durability, Plants (botany), Wetting, Chemically modified, Comprehensive services, Material resistance, Preservative-treated wood, Protective properties, Resistance modeling, Service life planning, Wood-based materials, Wood, Data, Picea Abies, Resistance, Service Life, Test Methods
National Category
Wood Science
Identifiers
URN: urn:nbn:se:ri:diva-54442DOI: 10.3390/f12050576Scopus ID: 2-s2.0-85105566610OAI: oai:DiVA.org:ri-54442DiVA, id: diva2:1568936
Note
Funding details: Horizon 2020 Framework Programme, H2020, 773324; Funding details: Agence Nationale de la Recherche, ANR; Funding details: Ministry of Education, Culture, Sports, Science and Technology, Monbusho; Funding details: VINNOVA; Funding details: Svenska Forskningsrådet Formas; Funding details: Agence de l'Environnement et de la Maîtrise de l'Energie, ADEME; Funding details: Energimyndigheten; Funding details: Norges Forskningsråd, 297899; Funding details: Bundesministerium für Ernährung und Landwirtschaft, BMEL; Funding details: Fachagentur Nachwachsende Rohstoffe, FNR; Funding details: Ympäristöministeriö; Funding text 1: G.A., C.B., S.F., and E.S. received funding in the frame of the research project CLICKdesign, which is supported under the umbrella of ERA-NET Cofund ForestValue by the Ministry of Education, Science and Sport (MIZS)?Slovenia; the Ministry of the Environment (YM)?Finland; the Forestry Commissioners (FC)?UK; Research Council of Norway (RCN, 297899)?Norway; the French Environment and Energy Management Agency (ADEME) and the French National Research Agency (ANR)?France; the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS), Swedish Energy Agency (SWEA), Swedish Governmental Agency for Innovation Systems (Vinnova)?Sweden; and the Federal Ministry of Food and Agriculture (BMEL) and Agency for Renewable Resources (FNR)?Germany. ForestValue has received funding from the European Union?s Horizon 2020 research and innovation program under grant agreement N? 773324. We acknowledge support by the Open Access Publication Funds of the Goettingen University.
2021-06-182021-06-182024-07-04Bibliographically approved