A simulation study on the process design and optimization pressure swing separation of azeotropic mixture methanol and toluene

Pressure Swing Distillation (PSD) is the only advanced technology that does not require the addition of third components to the system to enhance the separation of azeotropic mixtures. It outperforms homogeneous distillation for separating pressure-sensitive azeotropic mixtures. In this study, we aimed to separate methanol and toluene using the Non-Random Two-Liquid (NRTL) and Aspen Plus thermodynamic calculation models to simulate a binary homogeneous azeotropic system. The standard PSD process was employed to separate methanol and toluene. Furthermore, multiple optimization sequences were utilized to sequentially optimize the process for obtaining higher purities of methanol and toluene while reducing the Total Annual Cost (TAC) and heat energy consumption. The effects of the optimization sequence on the TAC were investigated. The best optimization sequences for graphing in Origin or Aspen Plus were found to be RR1, NR, NF1, NF2, NT1, and NT2. Additionally, the Double-Effect Distillation (DED) optimization sequence is similar, with TAC as the primary function in the simulation and methanol and toluene purities up to 99.99%. In the DED simulation, the feed position and tray number were found to be sensitive to TAC by the order NR > NF1 > NF2 and NT1 > NT2. This study simulated PSD using the NRTL thermodynamic calculation model in Aspen Plus and generated visualizations using Origin software.

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Publication Details

Journal
PLoS ONE
Published
2024-12-23
DOI
https://doi.org/10.1371/journal.pone.0310541
Citations
2
Primary Topic
Process Optimization and Integration
Type
article
Field-Weighted Citation Impact
0.66

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article

A simulation study on the process design and optimization pressure swing separation of azeotropic mixture methanol and toluene

Junning Li, Zengxiang Jiao, Abdulmoseen Segun Giwa, Ndungutse Jean Maurice et al.
2 citations
PLoS ONE
Process Optimization and Integration
0.66
article

A simulation study on the process design and optimization pressure swing separation of azeotropic mixture methanol and toluene

Junning Li, Zengxiang Jiao, Abdulmoseen Segun Giwa, Ndungutse Jean Maurice, Mugabekazi Joie Claire, Xinxin Liu, Bigirimana Gentil
article en
2 citations

Abstract

Pressure Swing Distillation (PSD) is the only advanced technology that does not require the addition of third components to the system to enhance the separation of azeotropic mixtures. It outperforms homogeneous distillation for separating pressure-sensitive azeotropic mixtures. In this study, we aimed to separate methanol and toluene using the Non-Random Two-Liquid (NRTL) and Aspen Plus thermodynamic calculation models to simulate a binary homogeneous azeotropic system. The standard PSD process was employed to separate methanol and toluene. Furthermore, multiple optimization sequences were utilized to sequentially optimize the process for obtaining higher purities of methanol and toluene while reducing the Total Annual Cost (TAC) and heat energy consumption. The effects of the optimization sequence on the TAC were investigated. The best optimization sequences for graphing in Origin or Aspen Plus were found to be RR1, NR, NF1, NF2, NT1, and NT2. Additionally, the Double-Effect Distillation (DED) optimization sequence is similar, with TAC as the primary function in the simulation and methanol and toluene purities up to 99.99%. In the DED simulation, the feed position and tray number were found to be sensitive to TAC by the order NR > NF1 > NF2 and NT1 > NT2. This study simulated PSD using the NRTL thermodynamic calculation model in Aspen Plus and generated visualizations using Origin software.

PLoS ONEVol. 19(12)
Xi'an University of Science and Technology (CN), Jiangxi University of Water Resources and Electric Power (CN), Southwest University (CN), Shanxi University (CN), Nanchang Institute of Science & Technology (CN)
National Natural Science Foundation of China, Nanchang Institute of Technology
Affordable and clean energy
Openalex Percentile: Top 28%
Process Optimization and Integration
0.66
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