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MATERIALS:

WOOD and PAPER

Artículos científicos

UNIVERSIDAD POLITÉCNICA DE MADRID © 2017

59 artículos

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Sorption/desorption hysteresis revisited. Sorption properties of Pinus pinea L. analysed by the parallel exponential kinetics and Kelvin-Voigt models. Holzforschung . 71(2):171-177



Abstract:   The hygroscopic properties of Pinus pinea L. wood at 35 and 50ºC were investigated by the dynamic vapour sorption (DVS) technique. The sorption kinetic behaviour was studied through the parallel exponential kinetics (PEK) model, which is subdivided into a fast and a slow process. The parameters obtained by PEK were interpreted based on the Kelvin-Voigt (KV) model to determine elasticity and viscosity values of the wood cell wall. The PEK data perfectly fit the experimental data. The temperature dependent transition between the fast and slow processes is fluent. The slow process contributes more to the total hysteresis of sorption. The kinetic properties varied in relation to the type of cycle and the temperature. The moduli of elasticity and viscosity were higher in the slow process than in the fast one. In both processes, the moduli showed a decreasing tendency in relation to relative humidity.

 


Simón, C.

Esteban, L.G.

de Palacios, P.

García Fernández, F.

García-Iruela, A.


2017

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Application of artificial neural networks as a predictive method to differentiate the wood of Pinus sylvestris L. and Pinus nigra Arn subsp. salzmannii (Dunal) Franco. Wood Science and Technology. 51(3):517-534. doi:10.1007/s00226-017-0932-7



Abstract:   The wood structure of conifers in general and the Pinus genus in particular makes species differentiation by traditional qualitative or quantitative methods complicated or even impossible at times. Pinus sylvestris L. and Pinus nigra Arn subsp. salzmannii (Dunal) Franco are a clear example of this because they cannot be differentiated by traditional methods. However, correctly identifying these species is very important in some cases as they are extensively used in a large variety of fields because of their wide distribution range in the forests of Europe and Asia. Using trees selected from the same forest to minimise the influence of site and performing a biometric study of 10 growth rings from the same climate period, a feedforward multilayer perceptron network trained by the resilient backpropagation algorithm was designed to determine whether the network could be used to differentiate these species with a high degree of probability. The artificial neural network achieved 90.4% accuracy in the training set, 81.6% in the validation set and 81.2% in the testing set. This result justifies the use of this tool for wood identification at anatomical level.

 


Esteban, L.G.

de Palacios, P.

Conde, M.

García Fernández, F.

García-Iruela, A.

González-Alonso, M.


2017


58

Sorption and thermodynamic properties of wood of Pinus canariensis C. Sm. ex DC.

buried in volcanic ash during eruption. Wood Science and Technology. 51:517–534.



Abstract:    The hygroscopicity and thermodynamic properties of Pinus canariensis wood buried in volcanic ash, dating from 1100 BC, were studied and compared with recently felled juvenile and mature wood of the same species. The sorption isotherms were obtained by the saturated salt method at 35 and 50 ºC. The isotherms were fitted using the Guggenheim–Anderson–de Boer model. The thermodynamic parameters were determined following the Clausius–Clapeyron integration method. To understand the behaviour of each type of wood, the chemical composition, infrared spectra and X-ray diffractograms were determined for each sample. The mature wood has a higher sugar content and lower extractive content than the juvenile and the buried wood. For both temperatures, the isotherm of the mature wood is above the isotherm of the juvenile wood and this, in turn, is above the isotherm of the buried wood, primarily influenced by the higher cellulose and hemicellulose contents and lower extractives content in the mature wood, resulting in a higher number of accessible –OH groups. Degradation of the buried wood due to high temperatures explains why its isotherms are below the isotherms of the recent wood. The energy involved in the desorption process is greater than in adsorption. Similarly, more energy is involved in the mature wood than in the juvenile wood, and the energy involved in the juvenile wood is greater than in the buried wood.

 


Simón, C.

Esteban, L.G.

de Palacios, P.

García Fernández, F.

García-Iruela, A.

Martín Sampedro, R.

Eugenio, M.E.


2017


59

Study of the influence of the physical properties of particleboard type P2 on the internal bond of panels using artificial neural networks. Computers and Electronics in Agriculture 155:142–149.



Abstract: Particleboard panels are normally manufactured in three layers of different sized particles of wood. One of the most important properties of particleboard is internal bond. This study determined the thickness and the physical properties of swelling, water absorption and density of 300 type P2 particleboards, as well as tensile strength perpendicular to the plane of the board, to examine the influence of these physical properties on internal bond of panels. To study the influence on internal bond, a multilayer perceptron artificial neural network was designed using the hyperbolic tangent sigmoid as the transfer function. The artificial neural network designed is capable of explaining at least 82% of the variability of the samples, with no significant differences between the experimental values and those obtained through the network for a significance level of 95%. The neural network proposed is suitable for studying the influence of the physical properties on internal bond, revealing a decrease in internal bond as panel thickness increases. A slight increase in internal bond was observed as swelling and absorption increase to values close to the mean, followed by a decrease. In relation to density, internal bond increases to values of about 700 kg/m3, then decreases.

 


de Palacios, P.

García Fernández, F.

García-Iruela, A.

González-Rodrigo, B.

Esteban, L.G.


2018