An Experiment Design to Determine the Discharge Coefficient of an Unknown Fluid
- Andrea Schultz
- Oct 2, 2017
- 2 min read

ME 321 focuses on the fundamentals of measurement systems in mechanical engineering including transducer operation, signal conditioning, data reduction, and presentation of results. Transducer and measurement systems characteristics include resolution, sensitivity, loading, time response, and frequency response, which is what the course was heavily focused on. In addition, operating principals of basic instrumentation for measurement of mechanical quantities such as force, torque, pressure, temperature, and flow were focused on. Major topics in this course included uncertainty analysis, data analysis, calibration, data acquisition, presentation of results and an introduction to experiment design.
The final project in this class challenged myself and three others to come up with a design experiment based on what we had learn in the past six weeks. Theoretically, by analyzing different fluids, our experiment design would be able to determine the discharge coefficient of each fluid.
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Our parameters of the design were the discharge coefficient, C, density, p, and the diameter, d.
We selected a range for our parameters, which can viewed under Class Projects on the main page of Portfolio. With these, we broke down our DRE and did an uncertainty analysis, below, and determined that the uncertainty in each measurand would have to be 2,9% in order to reach our goal of 10% uncertainty in our resultant, C.

If we were to hypothetically conduct this experiment, a flow sensor, pressure sensor, and scale would be needed to collect data and water would be the first sample. The accuracy of each sensor was taken into consideration during our uncertainty analysis, taking the non-linearity and accuracy from each spec sheet and applying it to our calculations. Overall a design space was coded using the minimum and maximum of each scale's capabilities along with the ranges of each parameter. As pictured below, our design space is highlighted in blue with each point resulting in a 2.16% to 2.55% uncertainty for our resultant. Using water as our test case, the uncertainty budget shows that our design would meet our 10% goal, having an RSSC percentage of 2.58%.


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