Document

Computational Study of Gas Separation Using Reverse Osmosis Membranes

About this Digital Document

Hollow fiber (HFM) and spiral wound membrane modules are among the most common separation devices employed in reverse osmosis gas separation and desalination applications. Three-dimensional steady state computational fluid dynamics (CFD) simulations are carried out to study flow past hollow fiber membrane banks (HFMB). This work focuses on enhancing the membrane performance by improving the momentum mixing in the feed channel by placing hollow fiber membranes in different arrangements and spacings. The current study investigates the effects of flow behavior on membrane performance during binary mixture separations. Carbon dioxide (CO_2) removal from methane (CH_4) is examined in the staggered and inline arrangement of HFMs. The most common HFM module arrangement in industrial applications is the axial flow configuration. However, this work focuses on the radial crossflow configuration. Membrane surface is treated as a functional boundary where the suction rate and concentration of each species are coupled and are functions of the local partial pressures, the permeability, and the selectivity of the membrane. The CFD simulations employed the turbulent k-ω Shear Stress Transport (k-ω SST) model to study membrane performance for a wide range of the Reynolds number. The efficiency of the inline and staggered arrangements in the separation module is evaluated by the coefficient of performance and the rate of mass flow per unit area of CO2 passing across the membrane surface. This work demonstrates that the module with staggered arrangements outperforms the module with inline arrangements.This study also considers a three-dimensional hybrid separation module consisting of two parallel spiral wound membranes bounding the feed channel that contains hollow fiber membranes with various arrangements. The results of numerical simulations indicate that the hybrid membrane system with a net hollow fiber membrane provides profoundly improved membrane flux performances for both spiral wound membranes and HFMs. The removal of CO2 from CH4 is enhanced by the presence of net hollow fiber membranes in the feed channel.This work also numerically characterizes flux performance of the membrane, concentration polarization, and potential fouling sites in the reverse osmosis desalination module, which contains hollow fiber membranes arranged in an inline and a staggered configuration. An accurate membrane flux model, the solution-diffusion model, is employed. Hollow fiber membrane surface is treated as a functional boundary where the rate of water permeation is coupled with local concentration along the membrane surface. The rate of water permeation increases and concentration polarization decreases as the feed flow rate is increased. Hollow fiber membranes in the staggered geometry perform better than those in the inline geometry.It is proven by the present study that gas separation and desalination modules containing hollow fiber membranes should be designed and optimized by careful consideration of their configurations.
Full Title
Computational Study of Gas Separation Using Reverse Osmosis Membranes
Contributor(s)
Publisher
Lehigh University
Date Issued
2018-01
Language
English
Type
Form
electronic documents
Department name
Mechanical Engineering
Digital Format
electronic documents
Media type
Creator role
Graduate Student
Identifier
1035318354
https://asa.lib.lehigh.edu/Record/10927047
Alrehili, . M. F. (2018). Computational Study of Gas Separation Using Reverse Osmosis Membranes (1–). https://preserve.lehigh.edu/lehigh-scholarship/graduate-publications-theses-dissertations/theses-dissertations/computational-21
Alrehili, Mohammed Faraj. 2018. “Computational Study of Gas Separation Using Reverse Osmosis Membranes”. https://preserve.lehigh.edu/lehigh-scholarship/graduate-publications-theses-dissertations/theses-dissertations/computational-21.
Alrehili, Mohammed Faraj. Computational Study of Gas Separation Using Reverse Osmosis Membranes. Jan. 2018, https://preserve.lehigh.edu/lehigh-scholarship/graduate-publications-theses-dissertations/theses-dissertations/computational-21.