In sophisticated dosing systems for water and wastewater treatment, chemicals or additives are injected and mixed directly in the process flow. This avoids the need of extra equipm...
In-line systems may suffer from an over-concentration at the dosing point which can be prevented by the introduction of static mixers and a faster, homogeneous distribution in the process flow can be achieved. Nevertheless, injecting a relatively small flow of chemical liquid into a larger stream is a common mixing and control challenge. Inefficient mixing can lead to undesirable competitive reactions or the formation of secondary products and it can also have a direct impact in the consumption of fresh water, chemicals and energy.
The simulation solution
PRE Technologies have developed a comprehensive set of computational analysis tools that can be used in the evaluation of the performance of these dosing systems. These tools are also of great use in the optimisation of existing systems, through the selection of the most effective retrofit modifications leading to an improvement in the system's performance. The hydrodynamic model of this type of systems is built using 3D CFD simulations of the internal flow in the main pipe or water channel. The transport of chemical species is also determined and its progression tracked throughout the simulation domain.
The benefits of this 3D computational approach are the direct visualisation of the internal flow and the actual distribution of additives, as well as the quantification of the quality of mixing in the system with a high degree of accuracy without the need to resort to physical measurements.
The best way to show the benefits of 3D flow simulation is by presenting an example. The model in this example consists of a pipe section with a 180 bend of a larger process system. The pipe has two injection locations for additives to be injected in the main flow. The injection of additives is made through injection quills located in two different positions along the pipe section.
This design must ensure that the additive injected in the first injection location (Additive 1) must be fully mixed with the bulk flow before reaching the second injection location to avoid or minimise competitive reactions between additives. Turbulence promotes the dispersion of the additives in the system given a sufficiently long length of pipe. In this case, however, complete mixing of additives was required in shorter distances and measures were taken in the system to promote faster mixing of the additives. Different system configurations were tested.
Results
The results are presented in two Figures. Figure 1 presents the concentration of species for the full system, with Additive 1 shown in blue and Additive 2 in red. Figure 2 shows the distribution of Additive 1 concentration in 3 different cross-section cuts in the system. In this Figure, the distance to the injection point is measured in number of diameters (D) of the pipe cross-section.
For the original configuration, Case A, the transport of injected additive is essentially kept parallel to the pipe walls for a long distance and dispersion occurs gradually along the pipe. In this case, the turbulence in the bulk fluid and the pipe length is not sufficient to ensure a complete mixing and both additives still remain considerably segregated from the main flow.
For case B, 3 injection points were distributed radially per injection location. This resulted in an improvement on the dispersion of additives in the system but solely due to the fact that the additives are already more distributed at the injection location. The dispersion of additive still occurs gradually for a relatively long length of pipe.
Nevertheless, this measure was enough to ensure that Additive 1 is reasonably mixed (although some segregation is still observed) before reaching the second injection location.
When the static mixers were included in the pipe for Case C, mixing of additives happens considerably faster and in this case, immediately after passing through the static mixer, both additives are complety mixed.
It is guaranteed in this case that Additive 1 is completely mixed before reaching the second injection point.
The second static mixer had a simillar effect to the dispersion of Additives is considerably faster in comparison to Cases A and B. In this case, it is also guaranteed that the Additive 1 is completely mixed before reaching the second injection point. To better compare the results between different cases, the quality of the radial mixing across the pipe was quantified. This was achieved by calculating the Coefficient of Variation (CoV), which gives information on the variance of concentrations in different sections of the pipe after the injection of chemicals. A value of 1 indicates that the two fluids remain completely segregated and a value of 0 indicates that complete mixing was achieved. Values very close to 0 were obtained for cases C and D (0.00 and 0.02 respectively) whereas higher values were obtained for cases A and B (0.83 and 0.31 respectively).
The improvement in the mixing by the use of static mixers can be explained by the increased turbulence in the bulk of the flow.
The increase in the turbulent intensity is made at the expense of an increase in the pressure drop across the system; this being one of the main drawbacks in the use of static mixers. Nevertheless, the pressure increase was still negligible in the whole process system and did not represent a relevant increase in the operation costs.
The level of confidence in the system performance and the detailed quantification of localised issue is one of the most advantageous features of computational analysis of this kind. The beneficial effect on the speed and effectiveness of design iterations will directly impact project costs and delivery as well as the quality of engineering.