inverse estimation of concrete properties andrew salisbury civil engineering november 27, 2006
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November 27, 2006Andrew Salisbury3 This talk explains the process of determining concrete properties Temperature Variation and Measurement Modeling Parameter EstimationTRANSCRIPT
Inverse Estimation of Concrete Properties
Andrew SalisburyCivil EngineeringNovember 27, 2006
November 27, 2006 Andrew Salisbury 2
Key Points From the Last Talk Background on concrete and its
important thermal properties Introduction to non-destructive
evaluation and its uses in engineering The ultimate goal of this research is to
determine concrete strength from material properties using heat flow
November 27, 2006 Andrew Salisbury 3
This talk explains the process of determining concrete properties
Air Temperature Variation
0
500
1000
1500
2000
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3000
3500
0 10 20 30 40 50 60 70 80
Time (Hours)
Hea
t flu
x (k
J/m
^2 C
) Temperature Variation and Measurement
Modeling
Parameter Estimation
November 27, 2006 Andrew Salisbury 4
Heat flow must be stimulated by an external source
Heat Flux Variation Due to Solar Heating
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500
1000
1500
2000
2500
3000
3500
0 10 20 30 40 50 60 70 80
Time (Hours)
Hea
t flu
x (k
J/m
2̂ C
)
Solar radiation causes periodic heat input
November 27, 2006 Andrew Salisbury 5
Infrared thermography allows non-invasive measurement of surface temperatures
Infrared image of a structure’s exterior reveals temperature variations.
Bright red colors signal higher temperatures.
November 27, 2006 Andrew Salisbury 6
Modeling with the finite element method allows for temperature simulation
Temperature and heat flux is calculated for each element
Accuracy depends on the mesh size
November 27, 2006 Andrew Salisbury 7
Appropriate boundary conditions are essential for an accurate model
0 1 2 3 4 5 6 7
x 105
30
35
40
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60
65
Time (Seconds)
Tem
pera
ture
(C)
The blue curve represents model temperatures while the red represents recorded ones
November 27, 2006 Andrew Salisbury 8
Parameter estimation requires an iterative optimization process
Recorded Temperatures
Generate Model Temperatures Calculate Error
Otherwise, Change Model Parameters
Make Initial Guess for Parameters
Stop if Error Meets Tolerance
November 27, 2006 Andrew Salisbury 9
Results suggest that this process is accurate 3 parameters solved simultaneously with
errors less than 10 percent Degrees of freedom limit the number of
independent unknowns Not a major problem since density has
the least variation and a constant value is often assumed
November 27, 2006 Andrew Salisbury 10
Summary and Future Outlook Determining material properties is an
iterative three step process The process is non-invasive and can be
used in many applications Future research will study early age
concrete and heat generation
November 27, 2006 Andrew Salisbury 11
Questions?
November 27, 2006 Andrew Salisbury 12
ReferencesOutdoor IR Thermography. (2006) [Online] Available
http://www.imaging1.com/gallery/images/outdoor%20ir%20thermography%20energy%20audit%20scan.jpg. November 26, 2006.
Global Optimization. (2006) [Online] Availablehttp://mathworld.wolfram.com/images/eps-gif/GlobalOptimization_1000.gifNovember 26, 2006.
Concrete Ready-Mix. (2006) [Online] Availablehttp://www.concrete-readymix.com/3.jpg. November 26, 2006.
Solarcrete Energy Efficient Buildings. (2006) [Online] Availablehttp://www.solarcrete.com/precast-concrete-thermal-infrared-images.php.November 26, 2006.