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Turbidity measurements provide the primary source of performance monitoring at many water treatment plants. Turbidity provides an excellent way to measure overall plant performance, but it does not provide insight as to why the water treatment plants are performing well or poorly. The Floc Size and Count App team aims to overcome this problem by creating a tool for operators to analyze flocculation as a means to understand plant efficiency and performance as well as to understand the underlying reasons for this.
Fall 2017
This semester, the team went through a little change by losing two members and gaining two new ones. The new members started to learn LabVIEW as the floc app development continued. Time stamps were added to support functionality if the program were to be run for a long time. A documentation of the code was created. The team is working on data representation.
Spring 2017
This semester, the team has primarily worked on improving the data outputted by the Floc App. Distances in a computer are originally stored in units of pixels (tiny squares that are combined together to form store and display digital images). This unit must be converted to micrometers (a physical unit of length) using some scaling constant. The Floc App originally had this factor fixed, which would provide inaccurate measurements for different lab setups. To deal with this, the team created a function that allows a user to set this factor.
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Members Deniz Yilmazer: dy223@cornell.edu Anthony Verghese: akv26@cornell Melanie Lim: ml876@cornell.edu Christian Rodriguez: cer95@cornellShaima Parveen: sp822@cornell.edu
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