Modeling and Economic Optimization of a Hollow Fiber Membrane Module for CO₂ Separation Using Collocation Methods and Genetic Algorithms

Abstract

Hollow fiber membranes are frequently used to remove CO2 gas during the gas sweetening process due to their advantages such as cost-efficiency, simplicity of operation and maintenance, and compact size. Permeate flux behavior, which is governed by various factors such as membrane features and operating conditions, has a significant impact on the performance of membrane separation. The majority of existing research studies focused on enhancing the permeability and selectivity of membranes. The configuration and operation of membrane modules have received scant attention in investigation. The geometrical layout and operational parameters of a membrane module were taken into account as a multivariable optimization problem in this study. The total annual cost serves as the objective function. A construction expenditure based on the size of the membrane plant plus an operational expense related to energy usage make up the total cost. The module dimensions (fiber diameter, fiber length, and packing density) and operating conditions (inlet pressure) were taken into consideration as the design factors in the optimization problem. The membrane area and energy consumption, which are directly related to the overall cost, were calculated using a model to simulate the membrane plant. To simulate multicomponent gas transport through hollow fiber modules, a membrane model with a high prediction accuracy was adapted from a previous work and solved numerically using an orthogonal collocation method. The optimization process was carried out using a genetic algorithm. This study also investigated how different parameters affect the overall cost. The accuracy of the self-developed computation program was checked with the results obtained from ChemBrane. The relative difference in the results obtained from our program and ChemBrane is less than 1%, suggesting the applicability of our model and program. The proposed optimization process is able to find the conditions of the module that meet the requirement of CO2 concentration of effluent while minimizing the cost. The results suggest that the use of polyamides has a lower cost than the use of cellulose acetate membranes.

Keywords

• modeling
• optimization
• CO₂ separation
• membrane module
• collocation method
• genetic algorithm