SciELO - Scientific Electronic Library Online

vol.18 número3Ultrasonido y anisotropía en madera de Thuja plicata y Acer saccharumNIR spectroscopy can evaluate the crystallinity and the tensile and burst strengths of nanocellulosic films índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados




Links relacionados

  • En proceso de indezaciónCitado por Google
  • No hay articulos similaresSimilares en SciELO
  • En proceso de indezaciónSimilares en Google


Maderas. Ciencia y tecnología

versión On-line ISSN 0718-221X


TIRYAKI, Sebahattin; BARDAK, Selahattin; AYDIN, Aytac  y  NEMLI, Gökay. Analysis of volumetric swelling and shrinkage of heat treated woods: Experimental and artificial neural network modeling approach. Maderas, Cienc. tecnol. [online]. 2016, vol.18, n.3, pp.477-492. ISSN 0718-221X.

Shrinkage and swelling characteristics of wood as a hygroscopic material affect negatively its effective utilization for a variety of applications. Heat treatment is widely used for minimizing the negative effects of volumetric swelling and shrinkage of wood. The present study aims to develop artificial neural network (ANN) models for predicting volumetric swelling and shrinkage of heat treated woods. For this purpose, wood samples were subjected to heat treatment at varying temperatures (130, 150, 170 and 190 ºC) for varying durations (2, 4, 6 and 8 h). Experimental results have showed that volumetric swelling and shrinkage of wood decreased by heat treatment. Then, neural networks models capable of predicting the swelling and shrinkage of the treated woods were developed based on the resulting data. It was seen that ANN models allowed volumetric swelling and shrinkage of such woods to predict successfully with a limited set of experimental data. This approach was able to predict volumetric swelling and shrinkage of wood with a mean absolute percentage error equal to 2,599% and 2,647% in test phase, respectively. The developed models might thus serve as a robust tool to predict volumetric swelling and shrinkage with less number of experiments.

Palabras clave : Dimensional stability; heat treatment; hygroscopicity; neural network; swelling; wood properties.

        · texto en Inglés     · Inglés ( pdf )


Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons