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The figures 2,3,4,5 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 (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)
Figure 2, A and B, shows 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 3, A and B, represents the normalized turbidity as a function of Vs. As Vs is the inverse of time, we observe the opposite trend in the data. Figure 4, A and B, shows the cumulative distribution function and figure 5, A and B, 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).
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