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The StaRS Filter Theory team rebuilt an apparatus with an inlet system that used an orifice, rather than copper mesh or slotted pipes. Experiments were run to test the head loss across our system with certain coagulant dosages and determine the relationship between the coagulant doses and head loss across sand. Our ultimate goal is to build a mathematical model that can be used to access the filtration performance parameters and reflects the filter's effluent turbidity, head loss, and time until turbidity breakthrough or excessively high head loss.
Spring 2016
Filter performance can be described in a mathematical model to promote the understanding of stacked rapid sand filters. A variable that has been suspected to affect filter efficiency is coagulant dosage. The StaRS filtration experimental apparatus was adjusted by removing the flow accumulator to prevent sand from entering the inlet system and adding a flocculator to create small flocs. The collected data will be used to create a mathematical model to examine how coagulant mass affects the filter's effluent turbidity, head loss, and breakthrough time.
Fall 2016
Experiments with varied PACl dosages were ran to test the performance of the stacked rapid sand filter. Head loss and effluent turbidity were collected from the experiments with influent water at 5 NTU. The data from these experiments were used to create a mathematical model on the performance of the filter. The created model will then be used to write a research paper on a model for stacked rapid sand filters. The team hopes to publish this paper.
Spring 2017
This semester, the StaRS Filter Theory team continued to research on the development of a model and summarize the findings and complete the paper that was started last semester. Team started with validating washer model assumptions and found that the washer model does not work. The team also performed literature review and completed the paper by summarizing the new modelling approach.
Fall 2017
This semester, the StaRS Filter Theory team will continue to refine the existing understanding about how the stacked sand filter functions. Current plans include conducting experiments to confirm assumptions made in developing the visual model, translating the visual model into a mathematical model, and ultimately using the mathematical model to optimize filter performance.
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