Project Lead
Abdalellah Mohmmed
Subject Lead - School of Engineering, Infrastructure and Sustainability, Mechanical Engineering - De Montfort University - Dubai Campus
Collaborator
Prof. Daegyoum Kim
Korea Advanced Institute of Science and Technology (KAIST), Department of Mechanical Engineering
Working collaboratively between De Montfort University Dubai and KAIST has been a highly enriching experience, combining complementary expertise in advanced computational modelling and engineering applications to address complex sustainability challenges. This partnership not only strengthens our research capacity but also fosters meaningful knowledge exchange across institutions and cultures. Together, we are committed to delivering impactful outcomes that contribute to the advancement of sustainable and resilient urban systems.
Water scarcity and the rising energy demand of desalination systems present critical challenges for sustainable urban development, particularly in arid regions. Conventional desalination technologies are energy-intensive and prone to membrane fouling, scaling, and performance degradation, limiting their long-term sustainability.
This project proposes an innovative, AI-driven and bio-inspired approach to enhance the efficiency, resilience, and environmental performance of membrane-based desalination systems. Inspired by the hierarchical branching architecture of the human lung, the project will develop a lung-like flow distribution system that optimizes two-phase (liquid–vapour) flow behaviour within membrane distillation modules.
The bio-inspired distributor is designed to promote uniform flow distribution, improve phase separation, reduce stagnation zones, and mitigate fouling and scaling at the membrane surface. Advanced computational fluid dynamics (CFD) modelling will be employed to analyse multiphase flow regimes and guide the design of the system.
To enable intelligent and adaptive operation, artificial intelligence (AI) algorithms will be integrated with real-time sensor data (pressure, temperature, flow rate, and conductivity). These algorithms will predict flow transitions, detect early signs of fouling or membrane wetting, and dynamically adjust operating conditions to maximize permeate flux and energy efficiency.
The proposed design will be fabricated using advanced 3D-printing techniques and experimentally validated under varying salinity, temperature, and flow conditions. The project is jointly conducted by De Montfort University Dubai and KAIST (Korea) under an international co-funded research programme (Dubai Future Foundation & National Research Korea) and contributes to SDGs 6 (Clean Water and Sanitation), 9 (Industry, Innovation and Infrastructure), 11 (Sustainable Cities and Communities), 12 (Responsible Consumption and Production), and 13 (Climate Action).
Expected outcomes include a validated prototype, peer-reviewed publications, and scalable design guidelines for smart, low-energy desalination systems supporting sustainable and climate-resilient urban water infrastructure.