Novel design of flow path spacers for reverse electrodialysis cell

Abstract

Reverse electrodialysis (RED) is one of the technologies used to harness ‘Blue Energy’, which is generated from the controlled separation of ions between salt water and fresh water through cation and anion exchange membranes (CEM/AEM) stack with end electrodes. The spacers present in between CEM and AEM allows the flow of salt and fresh water significantly affecting the fouling and concentration polarization in the RED cell. The present work focuses on improvement in flow path design, which may be used in place of mesh spacers in order to reduce pressure drop and enhance shear stress on the surface of the membrane to reduce concentration polarization. A three‐dimensional direct numerical simulation of the Navier–Stokes equation is conducted using Fluent 14.0 to analyze four different flow field designs, including serpentine, criss‐cross, rhombus, diamond, and standard mesh spacers. The simulation predicted closely the experimental data on pressure drop for the mesh spacers available in the literature. The present study points out that the diamond type flow field design, which combines characteristics of mesh spacers and flow field plates, gives lesser pressure drop per unit length with the increase in velocity within the same range of shear stress generated in mesh spacers. In other words, net power density of RED would improve with the use of diamond type spacer flow field with the decrease in concentration polarization loss and pumping power density.

Introduction to the K. Nandakumar Festschrift Issue section ofCJCE

“…Alizadeh et al [ 7 ] share their work that uses artificial neural networks to adequately predict 10 important properties of crude oil collected from seven different Canadian oil fields using only their Fourier transform infrared spectroscopy (FTIR) spectra. In their contribution, Basu and Mahajan [ 8 ] employ 3D direct numerical simulation to evaluate four specific flow field designs and make recommendations for a reverse electrodialysis cell that can be used to produce ‘blue energy’. Yifei and Lakshminarayanan [ 9 ] focus on developing a multi‐agent reinforcement learning framework for process control applications and investigate the effect of increasing dynamical interactions on the control performance of such systems.…”