Intelligent modeling using fuzzy rule-based technique for evaluating wood carbonization process parameters

The structural changes of the porosity in three wood species in a pyrolysis system at several temperature ranging and time periods were investigated to study the wood carbonization characteristics. Rectangular cuboid wood samples were dried and then carbonized in an inert atmosphere furnace and their mass and dimensional changes were recorded before and after process. SEM observation indicated that anatomical feature of final porous carbon remains unchanged with respect to the initial wood precursor. This research also intends to develop an intelligence model based on fuzzy logic theory. The model considers the final density as the end result of the process and establishes relations with carbonization process parameter (carbonization temperature, carbonization time period, initial density of wood) on the basis of fuzzy linguistic rules. Besides, a regression equation was established between above parameters and afterward, considering the constant of the derived model, significance of each one was identified. The results of the fuzzy model were found to be very close to the experimental data and show the possibility of improving rule-based modeling for such engineering challenges.

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