Membrane Distillation (MD) is an emerging sustainable desalination technique.
While MD has many advantages and can be powered by solar thermal energy, its
main drawback is the low water production rate. However, the MD process has
not been fully optimized in terms of its manipulated and controlled variables. This is
largely due to the lack of adequate dynamic models to study and simulate the process.
In addition, MD is prone to membrane fouling, which is a fault that degrades the
performance of the MD process.
This work has three contributions to address these challenges. First, we derive a
mathematical model of Direct Contact Membrane Distillation (DCMD), which is the
building block for the next parts. Then, the proposed model is extended to account
for membrane fouling and an observer-based fouling detection method is developed.
Finally, various control strategies are implemented to optimize the performance of
the DCMD solar-powered process.
In part one, a reduced-order dynamic model of DCMD is developed based on
lumped capacitance method and electrical analogy to thermal systems. The result is
an electrical equivalent thermal network to the DCMD process, which is modeled by
a system of nonlinear differential algebraic equations (DAEs). This model predicts
the water-vapor flux and the temperature distribution along the module length. Experimental data is collected to validate the steady-state and dynamic responses of the proposed model, with great agreement demonstrated in both.
The second part proposes an extension of the model to account for membrane
fouling. An adaptive observer for DAE systems is developed and convergence proof
is presented. A method for membrane fouling detection is then proposed based on
adaptive observers. Simulation results demonstrate the performance of the membrane
fouling detection method.
Finally, an optimization problem is formulated to maximize the process efficiency
of a solar-powered DCMD. The adapted method is known as Extremum Seeking (ES).
A Newton-based ES is designed and the proposed model is used to accurately forecast
the distilled water flux. Although good results are obtained with this method, a
practical modification to the ES scheme is proposed to enhance the practical stability.
|Date of Award||Dec 2016|
|Original language||English (US)|
- Computer, Electrical and Mathematical Science and Engineering
|Supervisor||Meriem Laleg (Supervisor)|
- Dynamic Reduced Order Modelling
- Direct Contact Membrane Distillation (DCMD)
- Membrane Fouling Detection
- Extremum Seeking Methods
- Optimal Control
- Adaptive Descriptor Observor