Modeling of an Industrial Incinerator for Refinery Wastes and Investigating the Effective Parameters for Performance Improvement

Document Type : Chemistry Article

Authors

1 MSc, Department of Chemical Engineering, Shahid Nikbakht Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran

2 Assistant Professor, Department of Chemical Engineering, Shahid Nikbakht Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran

3 Professor, Department of Chemical Engineering, Shahid Nikbakht Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran

Abstract

Industrial waste incinerators in gas refineries or sulfur recovery units are responsible for eliminating the waste gases such as hydrogen sulfide (H2S) and carbon dioxide (CO2) produced in the process. Most of these units are facing problems such as incomplete combustion, lack of proper control systems for measurement, and the presence of pollutants such as carbon monoxide and nitrogen oxides, etc. Therefore, in this research, to improve the performance of the waste incinerator of Fajr Jam Refinery, furnace modeling was done by computational fluid dynamics (CFD). The software Fluent 6.3 is used for the modeling of the incinerator. To achieve this goal, parameters such as the ratio of fuel to air in the inlet duct of main air, the amount and role of the additional air inlet at the bottom of the chimney, the installation of the additional air inlet duct at the end of the furnace for mixing more oxygen and H2S, air injection into the inlet duct of acid gas and the feasibility of preheating the incoming air and its effect on the combustion efficiency was investigated. The modeling results showed that increasing the airflow can reduce the amount of CO and H2S, but the amount of NOx compounds increases. To establish a balance between the output of pollutants from the furnace, solutions to improve the unit performance were presented, and the appropriate flow range of excess air in the furnace was determined.
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Keywords

Main Subjects

References

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Journal of Modeling in Engineering
Volume 22, Issue 78
October 2024
Pages 103-122

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History

  • Receive Date: 03 August 2023
  • Revise Date: 28 March 2024
  • Accept Date: 28 May 2024

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