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The StaRS Filter Theory team designed and built an apparatus to test the clogging across slotted pipes and evaluate their performance in stacked rapid sand filters. Experiments were run for the sole purpose of clogging the slotted pipe and characterizing the extent of clogging and what conditions caused the slots to clog. The team found that instead of head loss changing as a function of coagulant dosage only, as previously hypothesized, head loss was also affected by the amount of floc buildup on the slots. The coagulant to clay ratio thus affected the clogging rate and amount of head loss that built up over time.

Fall 2015

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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Members

Theresa Chu

Nicholas Coyle

William Pennock

Lucinda Li

Lingzi Xia

Dylan Vu

Liz CantlebaryAlexandra Schwab

Email Team

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Challenges

Tasks

Literature Search

Symposium

Final Presentation

Final Report

Spring '18   StaRS Filter Theory Symposium Spring 2018  
Fall '17

 

  StaRS Filter Theory-Fall 2017StaRS Filter Theory Final Presentation-Fall 2017StaRS Filter Theory Final Report-Fall 2017
Spring '17   StaRS Filter Theory-2017 Spring.pptxStaRS Filter Theory Final Presentation - 2017 Spring.pptx 
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