Data Fluctuation Experiment
Objectives
Floc sedimentation is a deterministic process that, under ideal conditions and the same initial conditions, should be highly repeatable. However, because we do not have ideal conditions there will invariably be statistical variance from the actual values. Moreover, the nepthalometric turbidimeter does a poor job of resolving individual flocs both temporally and spatially. For example, when we have a solution containing many large flocs slowly settling out in relatively clear water, the turbidity value will fluctuate between high and low values as flocs move into and out of the measurement volume. This is an intrinsic problem with using turbidity as a quantifying metric for how clear a solution is when large colloids are present in the suspension. For lack of a better measurement technique, we must try and estimate the mean turbidity as a function of time to infer some information about either floc concentration or floc size or both. We suspect that if we take the ensemble average of multiple realizations of the same experiment, we may be able to average out some of the higher frequency fluctuations that are caused by large flocs moving in and out of the sample volume.
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. This is due to the fact that flocs and floc formation is not an exact science, and that flocs that form during one time in one experiment will not be exactly the same as flocs formed at another time using the same experiment setup with all the same variable values. In order to get a better picture of the noise or random high frequency data fluctuations in our past data, we wanted to design a simple experiment to quantify how much of this fluctuation we are seeing and if it is affected by the time, turbidimeter position, and the experiment location within the fluctuation can be removed through ensemble averaging the data from a large number of experiment experimental runs.
Experiment Procedurs
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