ANFIS modeling of carbon dioxide capture from gas stream emissions in the petrochemical production units. (19th March 2017)

• Record Type: Journal Article
• Authors: Baghban, Alireza; Rajabi, Hamidreza; Jamshidi, Naser
• Is Part Of: Petroleum science and technology. Volume 35:Number 6(2017)
• Page Start: 625
• Page End: 631
• Publication Date: 2017-03-19
• Subjects: Amino acid -- ANFIS -- CO2 -- PSO -- sodium glycinate; Liquid fuels -- Periodicals; Petroleum -- Periodicals; 665.505
• DOI: 10.1080/10916466.2016.1273241
• Languages: English
• ISSNs: 1091-6466

Abstract

ABSTRACT: Amino acid salt, especially sodium glycinate, was known as a new class of environment-friendly solution that is now being studied as a favorable alternative to amines. In the present collaboration, the Adaptive Network-based Fuzzy Inference System (ANFIS) was employed to estimate CO2 loading capacity in the presence of aqueous sodium glycinate solution under broad ranges of temperature and pressure. The outcomes of suggested ANFIS model indicated their brilliant agreement with corresponding experimental values. The calculated values of mean relative error and R-squared were 2.93 and 0.988, respectively. Our suggested model can be of huge value for process engineers to have a simple and accurate tool in order to have rapid estimations of CO2 solubility as a function of temperature, pressure, and mass composition of sodium glycinate solution.