Modeling the Material Resistance of Wood—Part 2: Validation and Optimization of the Meyer-Veltrup Model. 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. Forests, 12(5):576, May, 2021.
Modeling the Material Resistance of Wood—Part 2: Validation and Optimization of the Meyer-Veltrup Model [link]Paper  doi  abstract   bibtex   1 download  
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.
@article{brischke_modeling_2021-1,
	title = {Modeling the {Material} {Resistance} of {Wood}—{Part} 2: {Validation} and {Optimization} of the {Meyer}-{Veltrup} {Model}},
	volume = {12},
	issn = {1999-4907},
	shorttitle = {Modeling the {Material} {Resistance} of {Wood}—{Part} 2},
	url = {https://www.mdpi.com/1999-4907/12/5/576},
	doi = {10.3390/f12050576},
	abstract = {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.},
	language = {en},
	number = {5},
	urldate = {2021-05-18},
	journal = {Forests},
	author = {Brischke, Christian and Alfredsen, Gry and Humar, Miha and Conti, Elena and Cookson, Laurie and Emmerich, Lukas and Flæte, Per Otto and Fortino, Stefania and Francis, Lesley and Hundhausen, Ulrich and Irbe, Ilze and Jacobs, Kordula and Klamer, Morten and Kržišnik, Davor and Lesar, Boštjan and Melcher, Eckhard and Meyer-Veltrup, Linda and Morrell, Jeffrey J. and Norton, Jack and Palanti, Sabrina and Presley, Gerald and Reinprecht, Ladislav and Singh, Tripti and Stirling, Rod and Venäläinen, Martti and Westin, Mats and Wong, Andrew H. H. and Suttie, Ed},
	month = may,
	year = {2021},
	pages = {576},
	file = {Brischke et al. - 2021 - Modeling the Material Resistance of Wood—Part 2 V.pdf:C\:\\Users\\maicher\\Zotero\\storage\\APG4279F\\Brischke et al. - 2021 - Modeling the Material Resistance of Wood—Part 2 V.pdf:application/pdf},
}

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