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1: Making Measurement Connections

  • Page ID
    121246
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    Learning Objectives
    • Willingness to ask questions (often repeatedly) to increase knowledge and understanding

     

    1. Why conduct experiments?
      Exercise \(\PageIndex{1}\)

      Students suggest their own reasons to conduct experiments:

      Answer
      • Test
      • Evaluate
      • Explore
      • Confirm quality
      • Discover
    2. Why here in conjunction with Capstone project? Why as a junior or senior in engineering curriculum?
      Exercise \(\PageIndex{2}\)

      Students indicate connectivity to their current status

      Answer
      • Sufficient foundation
      • Confirmation of knowledge
      • Preliminary project management
      • Practice communication
    3. How should the process of experiment be sequenced? There are many questions in each phase:
      1. Planning
        • Does variation alone create an experiment (i.e., changing parameters in simulation)?
        • What outcomes will make for a successful experiment (regardless of data collected)?
        • Should the approach include redundancy, significant precision, testing outside nominal conditions, etc.?
      2. Identifying system components
        • What is the fundamental principle and how is it observable?
        • Can the sensors reach the experimental region? AND survive the chemical/thermal/vibrational/structural environment?
        • How will the signals reach the signal conditioner to display/record digital values?
        • How will the presence of sensors affect the physical principle?
      3. Assessing performance
        • What is the correlation of the independent variable to the dependent outcome and measurand?
        • To what standard is the device calibrated?
        • Is uncertainty based on component, combination, and/or statistics?
      4. Setting signal sampling
        • Is the signal voltage, current, displacement, luminosity?
        • What makes for a sufficient data set? Consider both individual trials as well as overall system.
        • What sampling rate has sufficient accuracy without excessive storage requirements?
        • How does the combination of frequencies (input, output, sampling) influence data?
      5. Analyze results
        • What analytical equations characterize the results?
        • How do the statistical approaches impact the confidence in the reported result?
        • Does the trend of input-to-output correlate based on the functional relationship?
        • What is the comparison with theory and/or other experiments?
        • Is uncertainty constant throughout or measurement dependent?
        • What are criteria for rejecting spurious data? Is the method of rejection reported?
        • If a hypothesis is proposed before experimentation, does the result confirm or reject the hypothesis?
      6. Report (written and verbal)
        • What audience will review the experiment?
        • What level of detail is necessary for each section to:
          1. demonstrate the learning outcome?
          2. prove capability of the sensing device?
          3. repeat experiment for the non-expert?
          4. convince decision-maker of next steps?
        • What are the proper numbers, units, and uncertainty expressions?
        • How are you organizing the content to tell the story effectively?
        • Will it be reviewed in a static written form or in a dynamic oral presentation?

    Answers from any question can iteratively update prior ones.

    1. Useful definitions
      1. Experimental Classification
        1. Variational - quantify functional relationship of input changes to output observations; calibrating a standard
        2. Validational - test hypothesis to validate or refute; improve existing theory
        3. Pedagogical - teach/demonstrate established concept
        4. Explorational - pursue first steps of idea/theory
      2. Carefully crafted terms
        1. Parameters - fixed values for whole experiment
        2. Variable - something that undergoes change
        3. Independent variable - term that is manipulated by the experimenter
        4. Dependent variable - physical response of some sort
        5. Measurand - only those variables directly observed by a sensor
    1. General Measurement Model Flow chart sequence of General Measurement Model
      Exercise \(\PageIndex{3}\)

      Describe the use of the Extech HD350 Pitot Probe Anemometer in context of the General Measurement Model

      Pitot probe held within wind tunnel test section

      Answer

      Physical environment is the smaller cross section area of the wind tunnel (as compared to a large inlet area).

      Numerous independent variables could be modified:

      • Wind tunnel speed setting
      • Spatial location of the probe
      • Shape or position of upstream object deflecting air flow 

      A pitot probe is mounted within the test section through a small opening.

      Black and white tubes connect the stagnation and static pressure ports to the handheld transducer; sometimes may be wires for electrical-based sensor.

      Pressure differences converted by transducer to a numerical value.

      Options for signal conditioning:

      • Select units: meters per second, miles per hour, knots, etc.
      • Volume flow rate: input cross-sectional area
      • Sampling rate: real-time digital update, moving average of N data points

      Numerical readout can be stored in handwritten notebook or digital data acquisition file.

    2. Units of measure
      1. Quantity is represented by three properties
        1. Dimension (fundamental physical description)
        2. Unit (from accepted standard, i.e. SI, Imperial)
        3. Magnitude (actual numerical value)
      2. Fundamental dimensions are based on system of units
    Order Name Representation Typical Units
    1. Mass [M] kg, lbm
    2. Length [L] meters, feet, miles
    3. Time [T] seconds, days
    4. Temperature [\(\mathcal{T}\)] Kelvin, Rankine
    5. Current [I] Ampere
    6. Light [C] candela, lumen
    7. Matter [n] mol
    1. Fundamentals are used in combination to create secondary dimensions (e.g., torque is equivalent to mass x length2 x time-2).
    1. How to maintain universal consistency? (systems of units)
      1. Originally based on artifacts Historical context
      2. Now scientifically repeatable
      3. Standards
        • Length: meter - distance light travels in vacuum in \(\frac{1}{299,792,258}\) seconds
        • Temperature: Kelvin - \(\frac{1}{273.16}\) of triple point of water
        • Mass: WAS an artifact The kg is dead
        • Time: second - 9,912,631,700 cycles of Cesium radiation
    2. Hierarchy of standards
      1. Traceable path relating unit to standard
      2. Allows trading of commodities with consistent magnitudes of units
      3. Calibration standard is typically 1 part-per-billion
        • Thickness of 2 sheets of paper to a football field
    3. Convenient or unique conversion factors
      • 25.4 mm = 1 inch
      • 1 kW = 1.34102 hP
      • 5,280 feet = 1 mile
      • 1 smoot = 1.70 meter
      • 1 sydharb = 500 gigalitres
      • 1 beard second = 1 angstrom

    1: Making Measurement Connections is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by LibreTexts.

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