Turbidity Filter Trials and the Limits of a Majority Vote
A team in a school engineering challenge must lower the turbidity of 500 mL of synthetic gray water from about 120 NTU to below 25 NTU. Their filter may cost no more than $8.00 and must pass water at 20 mL/min or faster. The team builds a column with gravel, sand, and activated carbon. In trial 1, effluent turbidity is 18 NTU and flow is 24 mL/min. In trial 2, using a new batch of sand packed to the same height but rinsed less, turbidity is 42 NTU and flow is 31 mL/min. In trial 3, turbidity is 19 NTU and flow is 22 mL/min. The team wants to report that the design meets the goal because two of three trials are below 25 NTU. Their teacher asks them to justify the claim with evidence and to consider whether the trials are comparable.
1. Identify the independent, dependent, and controlled variables in this investigation, and explain why trial 2 weakens the team's claim.
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The independent variable is the filter design or treatment-here, the sand batch and its rinsing, plus packing. The dependent variables are effluent turbidity and flow rate. Controlled variables should include the source and initial turbidity of the water, the volume treated, column diameter and packing height, the order and mass of layers, and the method and timing of turbidity measurement. Trial 2 is not comparable because the sand was rinsed less, so it changed both the material and the pre-treatment while the team still treats it as the same design. A claim of success needs repeated trials under the same controlled conditions; two low readings and one high reading show the design is not robust to a variable the team did not control. The teacher should ask for a distribution of results, not a majority vote.
2. The team proposes to fix trial 2 by using more sand. Evaluate whether this is a sound next step, and describe a better experimental plan.
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Using more sand is not a clean fix because it changes flow rate, cost, and residence time at once. If turbidity improves, the team cannot tell whether the cause is more sand, reduced flow, or better filtration. A better plan is to hold the column design fixed, standardize the sand rinsing-for example, rinse until the rinse water turbidity is below a set value-run at least three trials with the same batch, and measure both turbidity and flow each time. If they want to test sand depth, vary only depth in planned increments and plot turbidity and flow versus depth. They should also calibrate the turbidity meter with a blank and a standard and report averages with spread.
3. Suppose the team must choose between a design with average turbidity 22 NTU and flow 21 mL/min and one with 12 NTU and flow 14 mL/min. Which is better under the constraints? Justify using engineering trade-offs.
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The first design is the only one that meets all constraints: 22 NTU is below 25 NTU and 21 mL/min is above 20 mL/min. The second has better turbidity, 12 NTU, but fails the minimum flow, 14 mL/min, so it is not eligible unless the team redesigns it to increase flow. In engineering, constraints are pass/fail before optimization. If both met the constraints, the lower turbidity would be preferable, but only after checking cost and reliability. The team should not trade a hard requirement for a better score on another criterion; instead, it should try to improve the second design's flow while preserving turbidity.