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Last semester, our team recorded a lot of data, not knowing how the effluent turbidity data might vary greatly even if the same experiment were to be run twice. In order to get a better picture of the noise or high frequency data fluctuations in our past data, we wanted to design a simple experiment to quantify how much of the fluctuation can be removed through ensemble averaging the data from a large number of experimental runs.
Experiment
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Procedures
Our team re-ran a typical an experiment multiple times repeatedly to see how the effluent turbidity data fluctuated during the settling state in each experiments and to compare the data fluctuation between experiments. The experiment set up was an influent turbidity of 50 NTU, an alum concentration of 25 mg/L, a flocculator length of 25 feet, and a G flow rate (Q) of 3.1 1mL/ssec. We repeated this experiment at least ten times in a row.
We extrapolated looked at the data effluent turbidity from just the settling state (600 seconds), we found and computed the ensemble average and standard deviation of the influent turbidity over the 10 runs and the effluent turbidity separately also the standard deviation about the ensemble mean at each second interval. We conducted this experiment for the typical position of the turbidimeter at the top of the settling column and at a new position of the turbidimeter at the bottom of the settling columntime interval.
Results
Figure 1: Standard Deviations of the Influent and Effluent Settling Turbidities from 10 consecutive experiments using the same position of the settling column (top).
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