An artificial neural network framework for gasification of liquid fuels under oxy-fuel conditions. (17th January 2019)

• Record Type: Journal Article
• Authors: Qiao, Haiye; Zeng, Shaoyin
• Is Part Of: Petroleum science and technology. Volume 37:Number 2(2019)
• Page Start: 215
• Page End: 219
• Publication Date: 2019-01-17
• Subjects: ANN -- gasification -- heavy oil -- HHV -- syngas; Liquid fuels -- Periodicals; Petroleum -- Periodicals; 665.505
• DOI: 10.1080/10916466.2018.1533866
• Languages: English
• ISSNs: 1091-6466

Abstract

Abstract: Gasification is a clean thermochemical process which converts carbon-based fuels into syngas. In this work, an artificial neural network model of heavy oil gasification under different gasifying agents was developed. Model was validated with the experimental data from literature. Effect of important parameters such as equivalence ratio and oxygen ratio (OR) on the higher heating value (HHV) of the produced syngas, gasification efficiency (GE), carbon conversion efficiency (CCE) was studied. With OR increasing from 0.366 to 0.41, GE and syngas HHV decreased, but CCE increased.