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Flocculator length | Flow rate | Influent Turbidity | Alum dose |
|---|---|---|---|
2796 cm | 3-19 mL/s | 100 NTU | 45 mg/L |
Expand this table to include relevant values for G and G*theta. OR I think it may be more beneficial to plot a graph of this in MathCAD and then show the figure so that all someone has to do is look at the graph and pull off a G for a given flow rate)
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(MathCAD file). 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. (I don't think that a 3-D plot conveys this well. You should put the 3-D plot in your "Materials and Methods" section and describe why you use it. Do not present this as data, especially since someone reading it on here cannot rotate the graph.)
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
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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 (Can put an equation on here in MathType to describe this?). 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. (Better description than in the other section. This really should be under "Materials and Methods" in a "Data Analysis" section.)
For more precision in data analysis, see Ian Tse's thesis (Chatper I, data analysis)
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