Monday, November 9, 2015: 1:14 PM
155C (Salt Palace Convention Center)
Membrane distillation (MD) is an emerging thermally driven desalination process, which combines low thermal energy distillation and membrane system. The direct contact membrane distillation (DCMD), considered in this study, is a flat sheet membrane module which has two adiabatic impermeable walls with the flat sheet membrane in between. The membrane has two hydrophobic walls permeable for water vapor but impermeable for liquid water. The main objective of this study is to develop a mathematical dynamic 2-D model for the lab scale DCMD plant. The model for the DCMD plant consists of several equations, which have a set of known parameters (obtained from the literature), such as membrane characteristics, and physical properties of the materials and water solution and also some unknown parameters. Examples of the unknown parameters include thermal conductivity of the water liquid in the feed and permeate channels, heat loss coefficient in the brine tank, and heat transfer coefficient in the distillate tank. The two sets of the model parameters have been estimated using gPROMS, which combines mathematically based optimization techniques with the maximum likelihood formulation. Those techniques determine the best values for the unknown parameters which minimize the deviation between the model predictions and experimental data. A parametric study in a lab scale DCMD experiment was carried out for parameter estimation and model validation. Results show that the 2-D dynamic model identifies: 1) the temperature distribution across the membrane module, 2) temperature and concentration polarization at the surface of the membrane, 3) temperature at the inlet and outlet sides of the membrane, 4) inlet and outlet flow rates across the membrane, 5) temperature distribution across the DCMD plant and 6) flow rate distribution across the DCMD plant. Furthermore, the parameter estimation study for the thermal conductivity of the water liquid in the feed and permeate channels, heat loss coefficient in the brine tank, and heat transfer coefficient in the distillate tank show that the standard deviation was at least one order or more of magnitude lower than the value of each parameter. In addition, the 95% t-value of each parameter is larger than the reference t-value. Also, the 2-D dynamic model has been optimized and thus validated using the experimental data obtained from the lab scale DCMD investigation. In conclusion, model validation showed that the 2-D dynamic model is a good representation of the DCMD pilot plant, and therefore, can be used successfully to design and scale up the DCMD desalination systems.