Multiscale Analysis of Permeable and Impermeable Wall Models for Seawater Reverse Osmosis Desalination

Separations

article

Qingqing Yang¹  Yi Heng²  Ying Jiang²  Jiu Luo² 

[1] School of Materials Science and Engineering, Sun Yat-sen University;School of Computer Science and Engineering, Sun Yat-sen University;National Supercomputing Center in Guangzhou;Guangdong Province Key Laboratory of Computational Science

关键词: multiscale modeling;    impermeable and permeable wall models;    high permeability membranes;    feed spacer;    reverse osmosis desalination;   

DOI  :  10.3390/separations10020134

学科分类：社会科学、人文和艺术（综合）

来源: mdpi

【 摘 要 】

In recent years, high permeability membranes (HPMs) have attracted wide attention in seawater reverse osmosis (SWRO) desalination. However, the limitation of hydrodynamics and mass transfer characteristics for conventional spiral wound modules defeats the advantage of HPMs. Feed spacer design is one of the effective ways to improve module performance by enhancing permeation flux and mitigating membrane fouling. Herein, we propose a multiscale modeling framework that integrates a three-dimensional multi-physics model with a permeable wall and an impermeable wall, respectively, at a sub-millimeter scale and a system-level model at a meter scale. Using the proposed solution framework, a thorough quantitative analysis at different scales is conducted and it indicates that the average errors of the friction coefficient and the Sherwood number using the impermeable wall model are less than 2% and 9%, respectively, for commercial SWRO membrane (water permeability 1 L m−2 h−1 bar−1) and HPMs (3 L m−2 h−1 bar−1, 5 L m−2 h−1 bar−1 and 10 L m−2 h−1 bar−1) systems, compared to the predictions using the permeable wall model. Using both the permeable and impermeable wall models, the system-level simulations, e.g., specific energy consumption, average permeation flux, and the maximum concentration polarization factor at the system inlet are basically the same (error < 2%), while the impermeable wall model has a significant advantage in computational efficiency. The multiscale framework coupling the impermeable wall model can be used to guide the efficient and accurate optimal spacer design and system design for HPMs using, e.g., a machine learning approach.

【 授权许可】

CC BY