Modeling of pyrolysis oil yield from sawdust using fuzzy and Aspen Plus approach
摘要
In this present research, sawdust was pyrolyzed in a laboratory batch pyrolysis setup and the pyrolysis oil yield was determined by varying the pyrolysis temperature, pyrolysis time, and biomass size. The experiments were conducted with different operating parameters such as pyrolysis temperature (350–550 °C), pyrolysis time (30–90 min), and biomass size (150–450 μm). The experimental results show that the pyrolysis temperature of 450 °C, pyrolysis time of 60 min, and biomass particle size of 150 μm give the maximum yield of pyrolysis oil. The experimental techniques are time-consuming, and hence, the modeling approach has been attempted to predict the bio-oil yield of the pyrolysis process. An adaptive neuro-fuzzy inference system (ANFIS) was employed to predict the bio-oil yield. The model is compared with the experimental bio-oil yield obtained from the laboratory pyrolysis experiment and found good agreement with the experimental result. A steady-state simulation of the pyrolysis process using Aspen Plus has been developed to predict the bio-oil yield without kinetics and observed that the Aspen Plus simulation results match well with the experimental pyrolysis bio-oil yield.