Improved binary parameters using GA for multi-component aromatic extraction: NRTL model without and with closure equations

Abstract

Application of genetic algorithm (GA), which leads to globally optimal binary interaction parameters from multi-component liquid–liquid equilibrium data, has been recently demonstrated for some ternary, quaternary and quinary systems. The binary interaction parameters are related to each other through the closure equations. In this work, the binary interaction parameters based on non-random two liquid (NRTL) activity coefficient model have been estimated using GA, without and with closure equations for 65 multi-component aromatic extraction systems: 53 ternary, 9 quaternary and 3 quinary systems. Parameters that satisfy the closure equations exhibit better root mean square deviations than those that do not satisfy the closure equations. Root mean square deviation value without implementation of closure equations is 0–80% better than literature as compared to 0–90% better with implementation of closure equations.