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Measurement of density and kinematic viscosity

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Title: Measurement of density and kinematic viscosity


1
Measurement of density and kinematic viscosity
  • S. Ghosh, M. Muste, F. Stern

2
Table of contents
  • Purpose
  • Experimental design
  • Experimental process
  • Test Setup
  • Data acquisition
  • Data reduction
  • Uncertainty analysis
  • Data analysis

3
Purpose
  • Provide hands-on experience with simple table top
    facility and measurement systems.
  • Demonstrate fluids mechanics and experimental
    fluid dynamics concepts.
  • Implementing rigorous uncertainty analysis.
  • Compare experimental results with benchmark data.

4
Experimental design
  • Viscosity is a thermodynamic property and varies
    with pressure and temperature.
  • Since the term m/r, where r is the density of the
    fluid, frequently appears in the equations of
    fluid mechanics, it is given a special name,
    Kinematic viscosity (n).
  • We will measure the kinematic viscosity through
    its effect on a falling object.
  • The facility includes
  • A transparent cylinder containing
  • glycerin.
  • Teflon and steel spheres of different
  • diameters
  • Stopwatch
  • Micrometer
  • Thermometer

5
Experimental process
6
Test set-up
  • Verify the vertical position for the cylinder.
  • Open the cylinder lid.
  • Prepare 10 teflon and 10 steel spheres.
  • Clean the spheres.
  • Test the functionality of stopwatch, micrometer
    and thermometer.

7
Data Acquisition
  • Experimental procedure
  • Measure room temperature.
  • Measure ?.
  • Measure sphere diameter using micrometer.
  • Release sphere at fluid surface and then release
    gate handle.
  • Release teflon and steel spheres one by one.
  • Measure time for each sphere to travel ?.
  • Repeat steps 3-6 for all spheres. At least 10
    measurements are required for each sphere.

8
Data reduction
  • Terminal velocity attained by an object in free
    fall is strongly affected by the viscosity of the
    fluid through which it is falling.
  • When terminal velocity is attained, the body
    experiences no acceleration, so the forces acting
    on the body are in equilibrium.
  • Resistance of the fluid to the motion of a body
    is defined as drag force and is given by Stokes
    expression (see above) for a sphere (valid for
    Reynolds numbers, Re VD/n ltlt1),
  • where D is the sphere diameter, rfluid
    is the density of the fluid, rsphere is the
    density of the falling sphere, n is the viscosity
    of the fluid, Fd, Fb, and Fg, denote the drag,
    buoyancy, and weight forces, respectively, V is
    the velocity of the sphere through the fluid (in
    this case, the terminal velocity), and g is the
    acceleration due to gravity (White 1994).

9
Data reduction (contd.)
  • Once terminal velocity is achieved, a summation
    of the vertical forces must balance. Equating
    the forces gives
  • where t is the time for the sphere to
    fall a vertical distance l.
  • Using this equation for two different balls,
    namely, teflon and steel spheres, the following
    relationship for the density of the fluid is
    obtained, where subscripts s and t refer to the
    steel and teflon balls, respectively.

10
Data reduction (contd.)
Sheet 2
Sheet 1
11
Experimental Uncertainty Assessment
  • Uncertainty analysis (UA) rigorous methodology
    for uncertainty assessment using statistical and
    engineering concepts.
  • ASME (1998) and AIAA (1999) standards are the
    most recent updates of UA methodologies, which
    are internationally recognized as summarized in
    IIHR 1999.
  • Error difference between measured and true
    value.
  • Uncertainties (U) estimate of errors in
    measurements of individual variables Xi (Uxi)
    or results (Ur) obtained by combining Uxi.
  • Estimates of U made at 95 confidence level.

12
Definitions
  • Bias error b
  • Fixed and systematic
  • Precision error e
  • and random
  • Total error d b e

13
Propagation of errors
Block diagram showing elemental error
sources, individual measurement systems
measurement of individual variables, data
reduction equations, and experimental results
14
Uncertainty equations for single and multiple
tests
  • Measurements can be made in several ways
  • Single test (for complex or expensive
    experiments) one set of measurements (X1, X2,
    , Xj) for r
  • According to the present methodology, a test is
    considered a single test if the entire test is
    performed only once, even if the measurements of
    one or more variables are made from many samples
    (e.g., LDV velocity measurements)
  • Multiple tests (ideal situations) many sets of
    measurements (X1, X2, , Xj) for r at a fixed
    test condition with the same measurement system

15
Uncertainty equations for single and multiple
tests
  • The total uncertainty of the result
  • Br same estimation procedure for single and
    multiple tests
  • Pr determined differently for single and
    multiple tests

16
Uncertainty equations for single and multiple
tests bias limits
  • Br
  • Sensitivity coefficients
  • Bi estimate of calibration, data acquisition,
    data reduction, conceptual bias errors for Xi..
    Within each category, there may be several
    elemental sources of bias. If for variable Xi
    there are J significant elemental bias errors
    estimated as (Bi)1, (Bi)2, (Bi)J, the bias
    limit for Xi is calculated as
  • Bike estimate of correlated bias limits for Xi
    and Xk

17
Precision limits for single test
  • Precision limit of the result (end to end)

t coverage factor (t 2 for N gt 10) Sr the
standard deviation for the N readings of the
result. Sr must be determined from N readings
over an appropriate/sufficient time interval
  • Precision limit of the result (individual
    variables)

the precision limits for Xi
Often is the case that the time interval for
collecting the data is inappropriate/insufficient
and Pis or Prs must be estimated based on
previous readings or best available information
18
Precision limits for multiple test
  • The average result
  • Precision limit of the result (end to end)

t coverage factor (t 2 for N gt 10)
standard deviation for M readings of the result
  • The total uncertainty for the average result
  • Alternatively can be determined by RSS
    of the precision limits of the individual
    variables

19
Uncertainty Analysis - density
  • Data reduction equation for density r

  • Total uncertainty for the average density

20
Bias Limit for Density
Correlated Bias two variables are measured with
the same instrument

21
Precision limit for density
Precision limit
22
Typical Uncertainty results
23
Uncertainty Analysis - Viscosity
Data reduction equation for density n

Total uncertainty for the average viscosity
(teflon sphere)
24
Calculating Bias Limit for Viscosity
No Correlated Bias errors contributing to
viscosity
25
Precision limit for viscosity
26
Typical Uncertainty results
27
Presentation of experimental results General
Format
  • EFD result A UA
  • Benchmark data B UB
  • E B-A
  • UE2 UA2UB2
  • Data calibrated at UE level if
  • E ? UE
  • Unaccounted for bias and precision limits if
  • E gt UE

28
Data analysis
Compare results with manufacturers data
29
Flow Visualization using ePIV
  • ePIV-(educational) Particle Image Velocimetry
  • Detects motion of particles using a camera
  • Camera details digital , 30 frames/second,
    600480 pixel resolution
  • Flash details 15mW green continuous diode laser

30
Results of ePIV
  • Identical particles are tracked in consecutive
    images to have quantitative estimate of fluid
    flow
  • Particles have the follow specifications
  • neutrally buoyant density of SG 1.0
  • small enough to follow nearly all fluid motions
    diameter11µm
  • Qualitative estimates of fluid flow can also be
    shown

31
Flow Visualization
  • Visualization-a means of viewing fluid flow as a
    way of examining the relative motion of the fluid
  • Generally fluid motion is highlighted by smoke,
    die, tuff, particles, shadowgraphs, Mach-Zehnder
    interferometer, and many other methods
  • Answer the following questions
  • Where is the circular cylinder?
  • In what direction is the fluid traveling?
  • Where is separation occurring?
  • Can you spot the separation bubbles?
  • What are the dark regions in the left half of the
    image?

32
Flow Visualization-Flow around a circular cylinder
  • Flow around a sphere is approximated by a
    circular cylinder
  • Flow in laboratory exercise has a Reynolds number
    less than 1.
  • Flow with ePIV has a Reynolds number range from
    2 to 90.
  • Reynolds number Re (VD)/? (? V D)/µ

Re 2
Re lt1
  • Glycerine solution with aluminum
  • powder, V1.5 mm/s, dia10 mm
  • ePIV, water and 10µm polymer
  • particels, V1.5 mm/s, dia4 mm

33
Flow Visualization-Flow around a circular
cylinder cont
  • Flow separation occurs at Re 5
  • Standing eddies occur between 5 lt Re lt 9
  • Length of separation bubble is found to grow
    linearly with Reynolds number until the flow
    becomes unstable about Re 40
  • Sinusoidal wake develops at about Re 50
  • Kármán vortex street develops around Re 100

Re1.54
Re9.6
34
Flow Visualization-Flow around a circular
cylinder cont
Re26
Re55
Re140
Re30
35
Flow Visualization-Flow around a circular
cylinder cont
  • Typical ePIV images

Re30
Re90
Re60
36
The End
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