Optimization, control and monitoring of solar driven desalination systemsApply
Membrane distillation (MD) is a thermally driven distillation process. In this process, hot feed stream is passed along one side of a hydrophobic membrane, which is only permeable for water vapor and retains liquid water, whereas the other side is kept at a lower (cooler) temperature. Due to temperature difference across the membrane, water evaporates at the feed-membrane interface and the induced partial vapor pressure difference drives only water vapor through the membrane where it condenses on the other side of the membrane, called the permeate side. MD requires low-grade heat, which can be harvested from solar thermal energy, and other renewable or waste heat sources. Also, unlike the well-known reverse osmosis, MD operates at a lower water pressure, which in turns reduces the capital and operational costs. All these advantages make MD ideal for remote area desalination plants installations with minimal infrastructure and less demanding membrane characteristics. However, MD is faced with challenges that are yet to be addressed in order for this technology to be competitive with conventional desalination techniques. In recent years, MD has been coupled with renewable energy sources, such as solar thermal collectors and photovoltaic (PV) panels, to capitalize on the attractive features of MD. However, the unsteady nature of renewable energy sources imposes a challenge on solar powered membrane distillation (SPMD) that requires special attention on process modeling and system control. Moreover, over time, membrane permeability changes due to scaling and fouling. All these factors have to be taken into consideration when modeling MD. In this project, the student will design an optimal control strategy to control the productivity of the combined solar-MD system under different constraints. He will also design monitoring strategies for fouling detection using estimation methods. Experimental validation will be performed in collaboration with Water desalination and Reuse center at KAUST.
Program - Electrical Engineering
Division - Computer, Electrical and Mathematical Sciences and Engineering
Faculty Lab Link - https://emang.kaust.edu.sa/Pages/Home.aspx
Center Affiliation - Computational Bioscience Research Center
Field of Study - Electrical engineering/ Applied Mathematics/Control Theory
Associate Professor, Electrical and Computer Engineering
Professor Laleg-Kirati's research interests encompass work across the fields of applied mathematics, control systems, and signal analysis. She works on new methods for signal analysis based on a semi-classical approach with an application to the analysis of the arterial blood pressure. Laleg-Kirati is also interested in modeling, identification, control, fault detection, inverse problems and especially seismic inversion and has expertise in solitons waves and scattering theory.
Desired Project Deliverables
Controller will be deigned and tested by simulations and if time will allow experiments will be performed.- A paper will be submitted