ANN modeling of fuel gas production from low-grade residual oil

Abstract

The aim of this work is to develop an artificial neural network model to simulate fuel gas production from low-grade residual oil. Effect of operating conditions on the fuel gas composition and performance parameters was studied. The model was validated against the experimental data and found to be in a good agreement. Since oxygen ratio increase improves the nature of water-gas reaction, increased oxygen content moved the reaction toward products and as a result CO and H₂ increased. Increased ER highly increased the CO₂ and highly decreased CH₄, CO and H₂ because increased ER means the movement of the process towards combustion.

Keywords:

• fuel oil
• gasification
• model
• experimental
• syngas

Additional information

Funding

This work is supported by Scientific Research Projects of Universities in Shandong province No. J16LN52.