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Modeling and statistical analysis of the three-side membrane reactor for the optimization of hydrocarbon production from CO2 hydrogenation.

Authors :
Najari, Sara
Gróf, Gyula
Saeidi, Samrand
Bihari, Péter
Chen, Wei-Hsin
Source :
Energy Conversion & Management. Mar2020, Vol. 207, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

• Modeling of CO 2 hydrogenation to hydrocarbons in a three-side reactor is developed. • Tr, Ts, Tt, θ and φ are considered as main effects in determining product yields. • Statistical analysis is performed to study the effects of variables on the yields. • Optimized operating conditions are determined to maximize olefin yields. Direct CO 2 hydrogenation to hydrocarbons is a promising method of reducing CO 2 emissions along with producing value-added products. However, reactor design and performance have remained a challenging issue because of low olefin efficiency and high water production as a by-product. Accordingly, a one-dimensional non-isothermal mathematical model is proposed to predict the membrane reactor performance and statistical analysis is used to assess the effects of important variables such as temperatures of reactor (Tr:A), shell (Ts:B) and tube (Tt:C) as well as sweep ratio (θ:D) and pressure ratio (φ:E) and their interactions on the products yields. In addition, the optimized operating conditions are also obtained to achieve maximum olefin yields. Results reveal that interacting effects comprising AB (TrTs), AC (TrTt), AE (Trφ), BC (TsTt), CE (Ttφ), CD (Ttθ) and DE (θφ) play important roles on the product yields. It is concluded that higher temperatures at low sweep and pressure ratios can maximize the yields of olefins, while simultaneously the yields of paraffins are minimized. In this regard, optimized values for Tr, Ts, Tt, θ and φ are determined as 325 °C, 306.96 °C, 325 °C, 1 and 1, respectively. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01968904
Volume :
207
Database :
Academic Search Index
Journal :
Energy Conversion & Management
Publication Type :
Academic Journal
Accession number :
141918409
Full Text :
https://doi.org/10.1016/j.enconman.2020.112481