Feasibility study of utilization of commercially available polyurethane resins to develop non-biocidal wood preservation treatments

Published Date
Original

First Online: 

12 November 2016

DOI: 10.1007/s00107-016-1128-9

Cite this article as: 

Mubarok, M., Hadi, Y.S., Suryana, J. et al. Eur. J. Wood Prod. (2016). doi:10.1007/s00107-016-1128-9

Author

• Mahdi Mubarok
• Yusuf Sudo Hadi
• Jajang Suryana
• Wayan Darmawan
• Frédéric Simon
• Stéphane Dumarcay
• Christine Gérardin
• Philippe GérardinEmail author

Abstract

Evaluation of commercially available polyurethane resins used up to now for coating applications to develop non-biocidal wood preservation treatments has been conducted. A simple method of vacuum impregnation of these resins into beech wood (Fagus sylvatica L.) and pine wood (Pinus sylvestris L.) samples followed by varied curing processes at ambient temperature, 103, and 200 °C has been performed. Based on the analysis of weight percent gain before and after leaching, treatment resistance to leaching, anti-swelling efficiency, wettability and decay durability measured for treated and untreated blocks after leaching with the white-rot fungus Coriolus versicolor for both wood species and the brown-rot fungi Poria placenta and Gloeophyllum trabeum for pine wood, it can be concluded that such treatment can be considered as potential valuable non-biocidal treatments.

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Deflections in sawn timber beams with stochastic properties

Published Date
Original

First Online: 

14 November 2016

DOI: 10.1007/s00107-016-1124-0

Cite this article as: 

García, D.A. & Rosales, M.B. Eur. J. Wood Prod. (2016). doi:10.1007/s00107-016-1124-0

Author

• Diego A. GarcíaEmail author
• Marta B. Rosales

Abstract

A stochastic model is proposed to study the behavior of structural sawn beams of Argentinean Eucalyptusgrandis with the aim of improving the predictability of the elastic deformations. The enhancement of the mid-span deflection calculation is based on a probabilistic model of the Modulus of Elasticity (MOE) and the representation of its lengthwise variability through a random field. The standard model that uses a MOE variable assumed random from piece to piece but deterministic (constant) within each piece is obtained as a particular case. In order to obtain a statistical representation of the MOE, the Principle of Maximum Entropy (PME) is employed. Experimental data obtained from bending tests are employed to find the parameters of the derived Probability Density Function (PDF). The PDF of the mid-span deformations is numerically obtained through the Stochastic Finite Element Method (SFEM) and Monte Carlo Simulations (MCS). Numerical results are validated with experimental values. Deflections of structural sized beams under usual loads are obtained. Finally, the stochastic model is used to compare with the serviceability requirements established in the Argentinean design code. It is shown that the structural performance of timber beams is found through a more realistic material approach.

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Examples of characteristics of wood that affect mould growth: a meta-analysis

Published Date
Original

First Online: 

15 November 2016

DOI: 10.1007/s00107-016-1127-x

Cite this article as: 

Johansson, P., Mjörnell, K. & Arfvidsson, J. Eur. J. Wood Prod. (2016). doi:10.1007/s00107-016-1127-x

Author

• Pernilla JohanssonEmail author
• Kristina Mjörnell
• Jesper Arfvidsson

Abstract

Building materials differ in their susceptibility to mould growth. Wood is a material often considered to have a low mould resistance. However, wood is not a homogenous material and different characteristics of the material are expected to have an impact on mould growth. In this paper, it was shown that wood species (pine or spruce), sawing pattern (centre-board or side-board) and surface structure (planed or sawn) affected mould growth. In addition, it was indicated that the susceptibility cannot be described by one single parameter, but also depends on other parameters. It is therefore difficult to estimate the susceptibility of wood in general. These conclusions were drawn from a meta-analysis, using data from five separate, previously performed laboratory studies conducted at 90% relative humidity and 22 °C, and from a laboratory study performed at 95% RH and 22 °C.

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