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Forward osmosis system design and optimization using a commercial cellulose triacetate hollow fibre membrane module for energy efficient desalination

  • Syed Muztuza Ali
  • , Sung Ju Im
  • , Am Jang
  • , Sherub Phuntsho
  • , Ho Kyong Shon
  • University of Technology Sydney
  • Sungkyunkwan University

Research output: Contribution to journalArticlepeer-review

Abstract

This study is aimed at developing system mathematical design models to simulate and optimize a full scale forward osmosis (FO) for a hollow fibre membrane module for energy efficient desalination. Experimental data from a commercial outer selective CTA hollow fibre FO membrane module was used for validation. Less than 10% difference between the simulation and experimental results were observed which validated the reliability of the models. Simulation and design were performed for a 1000 m3/day FO plant using 0.6 M NaCl as draw solution (DS) (~seawater) and 0.02 M NaCl feed solution (FS) (~MBR effluent) to produce 0.25, 0.2 and 0.15 M NaCl diluted seawater to reduce the energy consumption of downstream pressure driven desalination process. A single element parallel module arrangement was found more suitable for this commercial hollow fibre membrane element. Finally, the numerical simulations revealed that to achieve 0.25, 0.20 and 0.15 M final DS concentrations, the optimum number of modules required were 370, 435 and 555 respectively considering membrane cost and energy consumption. The FO system using the commercial CTA hollow fibre module was found more energy efficient than a commercial TFC spiral wound membrane module.

Original languageEnglish
Article number115075
JournalDesalination
Volume510
DOIs
StatePublished - 15 Aug 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation
  2. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Forward osmosis
  • Hollow fibre module
  • Modelling
  • Operating conditions
  • Optimization
  • Simulation
  • Specific energy consumption

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