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The Topping Unit (U10) at the Skikda refinery (RA1K) is a crude oil processing plant using the atmospheric distillation process, enabling oil to be separated into different hydrocarbon cuts. This study focuses on the prediction and the optimization of density of the atmospheric residue (380 ℃) extracted from the bottom of the 10-C-1 atmospheric distillation column of unit U10. We will use neural networks and Aspen HYSYS V12.1 simulation software to improve the separation process in column 10-C-1 of RA1K. This research showcased the successful use of neural networks in modeling changes in atmospheric residue density, leading to improved efficiency of the distillation column. The findings highlight the accuracy of the neural network employed, confirming its potential for use in the oil industry.

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Coupled Aspen HYSYS/MATLAB Approach for the Optimization of the 10-C-1 Distillation Column of the U10 RA1K Skikda Unit by Neural Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Ibtissam Boussouf,
  • Walida Boussouf,
  • Hamza Haddad,
  • Salah Eddine Mebarek Nacereddine,
  • Mohamed Salah Medjram

摘要

The Topping Unit (U10) at the Skikda refinery (RA1K) is a crude oil processing plant using the atmospheric distillation process, enabling oil to be separated into different hydrocarbon cuts. This study focuses on the prediction and the optimization of density of the atmospheric residue (380 ℃) extracted from the bottom of the 10-C-1 atmospheric distillation column of unit U10. We will use neural networks and Aspen HYSYS V12.1 simulation software to improve the separation process in column 10-C-1 of RA1K. This research showcased the successful use of neural networks in modeling changes in atmospheric residue density, leading to improved efficiency of the distillation column. The findings highlight the accuracy of the neural network employed, confirming its potential for use in the oil industry.