Model Based Simulation and Genetic Algorithm Based Optimisation of Spiral Wound Membrane RO Process for Improved...

Area of Science:

• Environmental Engineering
• Chemical Engineering
• Water Treatment Technologies

Background:

• Dimethylphenol is a highly toxic organic pollutant prevalent in wastewater.
• Even low concentrations of dimethylphenol pose significant risks to human health and ecosystems.
• Effective wastewater treatment methods are crucial for mitigating environmental contamination.

Purpose of the Study:

• To develop a model-based framework for simulating and optimizing the Reverse Osmosis (RO) process for dimethylphenol removal.
• To investigate the impact of membrane design parameters on RO performance.
• To achieve optimal dimethylphenol rejection with reduced energy consumption.

Main Methods:

• Incorporation of a validated process model into a Species Conserving Genetic Algorithm (SCGA) optimization framework.
• Simulation of RO process performance under varying operating conditions and membrane parameters (length, width, feed channel height).
• Development of a multi-objective function to optimize membrane design, dimethylphenol rejection, and energy consumption.

Main Results:

• Membrane length and width showed insignificant and significant impacts on dimethylphenol rejection and energy consumption, respectively.
• Increased feed channel height negatively influenced performance indicators like rejection and energy consumption.
• Optimized design achieved high dimethylphenol removal (up to 98.72%) with a substantial reduction in specific energy consumption (around 20.6%).

Conclusions:

• The study successfully optimized RO process parameters for efficient dimethylphenol removal.
• The developed framework provides a valuable tool for designing and operating RO systems for toxic pollutant removal.
• Optimized RO processes offer a sustainable solution for wastewater treatment, balancing high rejection rates with energy efficiency.