Optimization of Biomass Vacuum Pyrolysis Process Based on GRNN

Abstract:

Biomass pyrolysis for preparing bio-oil was studied on the vacuum pyrolysis system, where rape straw was chosen as the raw material. The experiment was designed by orthogonal method. And pyrolysis temperature, system pressure, heating rate and holding time were chosen as input variables to establish the prediction models about bio-oil yields and energy transformation ratio based on Generalized Regression Neural Network. The parameters of vacuum pyrolysis system were optimized for maximizing bio-oil yields and energy transformation ratio, and the optimization result was verified by experiment. The results of research show that the predicted values are fit well with the experimental values, which verifies the effectiveness of the prediction models. When pyrolysis temperature is 486.8°C, system pressure is 5.0kPa, heating rate is 18.1°C/min and holding time is 55.0min, bio-oil yield is 43.6% and energy transformation ratio is 35.5%. Both are close to the maximum, and the result is accurate by experimental verification.

• Periodical: Applied Mechanics and Materials (Volumes 411-414)
• Pages: 3016-3022
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.411-414.3016
• Online since: September 2013
• Authors: Xiao Hua Li, Yong Sheng Fan, Yi Xi Cai, Wei Dong Zhao, Hai Yun Yin
• Keywords: Biomass, Bio-Oil Yields, Energy Transformation Ratio, GRNN, Vacuum Pyrolysis

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