Multi-objective optimization of venturi scrubbers using a three-dimensional model for collection efficiency

Abstract

Multi-objective optimization of a venturi scrubber was carried out using a three-dimensional model for collection efficiency and non-dominated sorting genetic algorithm (NSGA). Two objective functions, namely (a) maximization of the overall collection efficiency, and (b) minimization of the pressure drop were used in this study. Three decision variables including two operating parameters, viz liquid-gas ratio and gas velocity in the throat, and the nozzle configuration, which takes into account the three-dimensional nature of the problem, were used in the optimization. Optimal design curves (non-dominated Pareto sets) and the values of the decision variables corresponding to optimum conditions on the Pareto set for a pilot-scale scrubber were obtained. The liquid to gas (L/G) ratio, which is a key decision variable that determines the uniformity of liquid distribution, and a staggered nozzle configuration can produce uniform liquid distribution in the scrubber. Multiple penetration using nozzles of two different sizes in a triangular staggered arrangement can reduce liquid loading by as much as 50%, consequently reducing the pressure drop in the scrubber.