Procedure
Our experiments were all performed on the same Flocculator Residual Turbidity Analyzer (FReTA) setup that was developed previously (Spring 2009). FReTA consisted of five parts: an alum stock bucket at 2.5 g/L, a kaolin clay stock bucketat 10g/L, a raw water reservoir, a coiled tube (insert diameter) serving as the flocculator, and the residual turbidty analyzer with a settling column. The raw water turbidity was controlled using a feedback loop mechanism; clay from the stock bucket was metered in automatically if the turbidity became too low. Peristaltic pumps were used to provide the flow rate and meter in the alum solution. All flow rates and chemical dosages were calculated, monitored and controlled using the Process Controller sotware (Weber-Shirk 2008). For detailed information on FReTA setup and the Process Controller figuration, please see Ian Tse's MS thesis (link to Ian thesis). Characteristics of the tap water used can also be found there.
In order to verify that the equipment was working properly and to familiarize our team with FReTA, we first performed a similar experiment to one that had been done the previous semester. We modified an earlier Process Controller file(see process controller file attached)that been set to run at flocculator length of 2796 cm with an influent turbidity of 50 NTU and a constant alum dosage of 38 mg/L while varying the plant flow rate from 3-19 mL/s increasing by 1 mL/s each trial to run instead at an influent turbidity of 100 NTU with an alum dosage of 45 mg/L; we maintained the same flow rate variation.
During each run, the influent raw water combined with the correct alum dosage was allowed to run through the plant until two residence times had passed, insuring a steady-state effluent floc distribution. Then the pumps gradually ramped down, and a valve sealed off the settling column from the rest of the flocculator. The turbidity was monitored every second for half an hour as the flocs settled out, and the data recorded in an EXCEL spreadsheet. We then analyzed the data using Mathcad files developed by the previous (Spring 2009) team to develop settling velocity probability density function for the flocs. After the analysis, the results could be used to find the flow rate (shear) with the best performance for the set turbidity and alum dosage. For details on how the data was collected by process controller, and how Mathcad was used to analyze the data, see Ian Tse's MS thesis.
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Results and Discussion
The sedimentation rate velocity and the residual turbidity of flocculated suspension are important properties in a flocculator. The Spring 2009 team evaluated quantitatively the effect of shear velocity on these parameters. To do so, they used the flocculation residual turbidity meter (FRETA) developed by the AguaClara team and a data processor (MathCAD file) to analyze these parameters automatically.
Our goal for these first experiments was to familiarize ourselves with the apparatus and the data processor (MathCAD file) made by the previous team (Spring 2009) and to try to replicate one of their last experiments to make sure that the apparatus and the MathCAD file were working properly.
Flocculator length |
Flow rate |
Influent Turbidity |
Alum dose |
|---|---|---|---|
2796 cm |
3-19 mL/s |
100 NTU |
45 mg/L |
Table 1: Parameters for the Fall 09 experiment
The experiment was conducted with the parameters shown in table 1. The parameters were based on one of Ian's experiment (data from 5/13/2009) conducted with the same inputs, except for the flow rates which vary from 4 to 19 mL/s and the turbidity which was set at 50 NTU(see MathCAD file attached). Figure 3 shows the plot of the effluent turbidity during the settling state as a function of time and flow rate. The flow is, in fact, changing at each cycle and we can see that the turbidity is decreasing at each settling state.
Figure 1:Plot of the effluent turbidity (NTU) during the loading state vs. time (sec) and flow rate (mL/s). Experiment of 9/24/2009
The figures 4,5,6,7,8,9,10, and 11 show the plots, given by the data processor, with the data from our experiment (9/24/09) and the data from the Spring 2009 experiment (5/13/09). Comparing graphs at each state, we observed similar results when compared with the previous years experiments. Our experimental values; seen on the graphs below, are not exactly the same as Ian's Spring 2009 data because the experiments were not performed under the same conditions, but they closely resembled one another. Data smoothing and normalization were the first transformations performed on the raw turbidity data. The smoothing allows us to exclude outlying data points caused by really large flocs passing in front of the light sensor of FRETA, which create turbidity fluctuations. The normalization allows us to compare data sets with varying influent turbidities. The settling velocity (Vs) was calculated by dividing the distance between the ball valve and the zone illuminated by the infrared LED of FRETA by the time elapsed. The plot of normalized turbidity vs. Vs can be interpreted as a cumulative distribution function (CFD) of turbidity with respect to Vs. A CFD describes the probability that a variable is less than or equal to some value. To make the analysis more robust, the experimental data was fit to a gamma distribution. Then a derivative of the CFD of the gamma distribution gives a probability distribution of the particle population with respect to Vs.
Figure 4 and 5 show the normalized effluent turbidity vs. time during the settling state for Spring 2009 team's experiment and Fall 2009 team's experiment, respectively. In both cases, the turbidity of the water decreases rapidly. Moreover, we can observe that for low flow rates, the turbidity decreases more rapidly and the residual turbidity is lower in both experiments. Figure 6 and 7 represent the normalized turbidity as a function of Vs. As Vs is the inverse of time, we observe the opposite trend in the data. Figure 8 and 9 show the cumulative distribution function and figure 10 and 11 show the resulting probability density function (PDF) of settling velocities obtained from the fitted gamma distribution for Fall 2009 experiment and Spring 2009 experiment. We can observe on the PDF curves that in both cases the mean velocities are decreasing with the flow rate (trace 1 being the lowest flow rate and trace 8 the highest).
A B
A ----------------------------- B
figure 3:Plot of the normalized effluent turbidity (NTU) vs. time(s).Experiment of 9/24/2009(A). Experiment of 5/13/2009 (B)