Boosting carbon dioxide adsorption capacity applying Jellyfish optimization and ANFIS-based modelling
A.G. Olabi, Hegazy Rezk, Enas Taha Sayed, Rania M. Ghoniem, Mohammad Ali Abdelkareem
Abstract
Carbon capture and storage (CCS) are essential for controlling global warming. Among the different CCS technologies, adsorption using amines is promising and applied on an industrial scale. In this research work, the optimal values of tetraethylenepentamine (TEPA), imidazole (Im) and temperature are identified to boost CO2 adsorption capacity. The proposed methodology integrates Jellyfish optimization (JO) and ANFIS-based modelling. In the first step, using measured data, ANFIS model is constructed to simulate the CO2 adsorption capacity in terms of the mentioned parameters. The second step, using JO, the best values of temperature, TEPA, and Im are identified to maximize the CO2 adsorption capacity. To confirm the superiority of the integration between JO and ANFIS, the main findings were compared with response surface methodology and measured data. The proposed strategy succeeded in boosting the CO2 capture adsorption from 4.27 (mmol/g) to 5.25 (mmol/g).