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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 a stock concentration of 2.5 g/L, a kaolin clay stock bucket at a stock concentration of 10g/L, a raw water reservoir, a coiled tube (0.953 cm diameter) serving as the flocculator (I would like you to expand this a little bit since this is the focus of your research. Can you show the equations that characterize flocculation in a coiled tube? Perhaps keep this in this section or make a link to another page with this information.), and the residual turbidty analyzer with a settling column (You described the process of analyzing the residual turbidity in your page where you varied the alum dosage.You should put this description in one place that anyone can find.) . 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 software developed by Weber-Shirk (2008). For detailed information on FReTA setup and the Process Controller figuration, please see Ian Tse's MS Thesis. All general information on the setup can be found in Chapter 1 Sec. 1.3-1.4 of the thesis. Characteristics of the tap water used can also be found there. Details of the Process Controller states and setpoints used can be found in Appendix A.
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 (what does this mean in terms of G and G*Theta?) 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, ensuring 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 (Do you have a sample excel spreadsheet you can upload here?).
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. Details of the data analysis procedures can be found in Appendix B of Ian Tse's Thesis. After the analysis, the results could be used to find the flow rate (shear) with the best performance (lowest residual turbidity, largest mean floc size) for the set turbidity and alum dosage.
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The floc terminal sedimentation velocity and the residual turbidity of flocculated suspension are important properties in a flocculator because all the particles having a terminal velocity lower than the capture velocity of the sedimentation tank are going to live the tank with the clear water causing the residual turbidity. (Rewrite this sentence. Make the distinction of what terminal sedimentation velocity represents. Put in the description you had in the other section here. With residual turbidity, you are measuring the anticipated performance you would have if the effluent from the flocculator passed into the tube settlers without any other sedimentation process) 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 to analyze these parameters automatically. (You describe this in more detail in another page. Please combine these sections so that you only have to write this once)
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. (You already stated this in your procedure section on the same page. Avoid repeating yourself.)
Table 1: Parameters for the Fall 09 experiment
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