Professional paper

https://doi.org/10.5552/drind.2015.1434

Modeling of Compressive Strength Parallel to Grain of Heat Treated Scotch Pine (Pinus sylvestris L.) Wood by Using Artificial Neural Network

Fatih Yapıcı ; Ondokuz Mayıs University, Engineering Faculty, Department of Industrial Engineering, Samsun, Turkey
Raşit Esen ; Karabük University, Technical Education Faculty, Department of Furniture and Decoration Education, Karabük, Turkey
Okan Erkaymaz ; Karabük University, Technical Education Faculty, Department of Furniture and Decoration Education, Karabük, Turkey
Hasan Baş ; Sveučilište Bülent Ecevit, Fakultet inženjerstva, Odjel za računalno inženjerstvo, Zonguldak, Turska

Abstract

In this study, the compressive strength of heat treated Scotch Pine was modeled using artificial neural network. The compressive strength (CS) value parallel to grain was determined after exposing the wood to heat treatment at temperature of 130, 145, 160, 175, 190 and 205ºC for 3, 6, 9, 12 hours. The experimental data was evaluated by using multiple variance analysis. Secondly, the effect of heat treatment on the CS of samples was modeled by using artificial neural network (ANN).

Keywords

wood; heat treatment; Artificial Neural Network; compressive strength

Hrčak ID:

150815

URI

https://hrcak.srce.hr/150815

Publication date:

7.1.2016.

Article data in other languages: croatian

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