Abstract:
The performance of paddle flocculators in water treatment is highly influenced by the basin hydrodynamics. In their design, several hydrodynamic and geometric parameters are required to ensure the efficiency of the process. Amongst these parameters, the slippage factor k is estimated to fall in the range of 0.2 to 0.3. An existing lack of the quantitative understanding of the velocity flow field in such flocculators is evidently identified in the literature. This research investigates the velocity field of turbulent flow in a paddle flocculator, and its influence on the process performance by quantifying k at low rotational speeds of 3 rpm and 4 rpm. A laboratory scale paddle flocculator was designed and experimentally investigated using particle image velocimetry measurements. Time averaged velocity data of the flow field at a plane perpendicular to the paddle wheel revealed the velocity of water particles surrounding the blades. Numerical simulations using a commercial computational fluid dynamics software package, ANSYS, were generated for the laboratory scale paddle flocculator. The influences of mesh structure and turbulence models SST k–ω and IDDES were evaluated. As a result, a good correlation between the PIV and CFD results was verified through a Goodness-of-Fit evaluation (with a coefficient of determination almost equal to 0.9). Results showed that the SST k–ω model can accurately predict the flocculation flow when the more computationally expensive IDDES model is not feasible. The slippage factor k was quantified as 0.18 for both rotational speeds. This indicates that more power is imparted to the water body than estimated in most design procedures, thus yielding higher velocity gradient values for flocculation in the basin. It is expected that the application of the validated CFD model will help improve the design and optimization of paddle flocculators.
