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• 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]

• Modeling of CO 2 hydrogenation to hydrocarbons in CR, AFSR and RFSR are accomplished. • Kinetic parameters are estimated via heuristic DA optimization algorithm. • Performance of the theoretical CR is compared with available experimental data. • Effect of reactor configuration is investigated in terms of conversion and selectivity. Climate change and global warming, as well as growing global demand for hydrocarbons in industrial sectors, make great incentives to investigate the utilization of CO 2 for hydrocarbons production. Therefore, finding an in-depth understanding of the CO 2 hydrogenation reactors along with simulating reactor responses to different operating conditions are of paramount importance. However, the reaction mechanisms for CO 2 hydrogenation and their corresponding kinetic parameters have been disputable yet. In this regard, considering the previously proposed Langmuir-Hinshelwood-Hougen-Watson (LHHW) mechanism, which considered CO 2 hydrogenation as a combination of reverse water gas shift (RWGS) and Fischer-Tropsch (FT) reactions, and using a one-dimensional pseudo-homogeneous non-isothermal model, kinetic parameters of the rate expressions are estimated via fitting experimental and modelling data through a novel swarm intelligence optimization technique called dragonfly algorithm (DA). The predicted reactants conversion using DA algorithm are closer to the experimental data (with about 4% error) comparing to those obtained by the artificial bee colony (ABC) algorithm, and are in significant agreement with available literature data. The proposed model is used to assess the effect of reactor configuration on the performance and temperature fluctuations. Results show that axial flow spherical reactor (AFSR) and radial flow spherical reactor (RFSR) exhibiting the same surface area with that of the cylindrical reactor (CR), i.e., AFSR-2 and RFSR-2-i are the most efficient exhibiting hydrocarbons selectivity of 40.330% and 40.286% at CO 2 conversion of 53.763% and 53.891%. In addition, it is revealed that the location of the jacket has an essential role in controlling the reactor temperature. [ABSTRACT FROM AUTHOR]