On improving the hydrogen and methanol production using an auto-thermal double-membrane reactor: Model prediction and optimisation

Hamid Rahmanifard, Reza Vakili, Tatyana Plaksina, Mohammad Reza Rahimpour, Masoud Babaei, Xiaolei Fan

Research output: Journal PublicationArticlepeer-review

6 Citations (Scopus)

Abstract

The concentric configured thermally-coupled double-membrane reactor (TCDMR) was optimised to improve the co-production of hydrogen and methanol. Using a detailed approach, we identified the non-linear differential evolution (DE) algorithm as the most suitable optimisation tool among the most used optimisation algorithms in reactor design (GA, PSO, and DE) due to its ability to converge to the optimal solution with fewer iterations. Considering DE algorithm with the industry benchmark data, we optimised the key operational parameters of TCDMR (as OTCDMR), leading to the improved reactor performance (regarding the overall heat transfer and methanol/hydrogen production) compared to the conventional methanol reactor (CMR) and TCDMR. Simulation results show that the methanol production rate of OTCDMR could reach 315.7 tonnes day−1, representing a 22.6% enhancement than CMR (257 tonnes day−1). For the hydrogen production, OTCDMR is predicted to deliver 19.7 tonnes of hydrogen per day, surpassing the 15.5 tonnes day−1 production rate by TCDMR.

Original languageEnglish
Pages (from-to)258-269
Number of pages12
JournalComputers and Chemical Engineering
Volume119
DOIs
Publication statusPublished - 2 Nov 2018
Externally publishedYes

Keywords

  • Auto-thermal reactor
  • Hydrogen
  • Membrane reactor
  • Methanol
  • Non-linear optimisation

ASJC Scopus subject areas

  • Chemical Engineering (all)
  • Computer Science Applications

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