Fatigue damage of bituminous mixes Sylvie Yotte et Mohsen Ech Centre de Développement des...
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Transcript of Fatigue damage of bituminous mixes Sylvie Yotte et Mohsen Ech Centre de Développement des...
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Fatigue damage of bituminous mixes
Sylvie Yotte et Mohsen Ech
Centre de Développement des Géosciences AppliquéesUniversité de BordeauxFrance
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Contents
● Pavement design and fatigue test● Damage model● Specimen simulation● Test simulation● Conclusion
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Pavement design
Fatigue cracking is one of the degradation mode of pavements
Many laboratory fatigue tests existsAmong them LCPC fatigue test (standard in France)
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Fatigue test
Xmsin(t)
Trapezoidal specimen subjected to a two point bending testSpecimen size : Bases : 25 mm and 56 mm – height : 250 mm
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Result of the test
Experimental fatigue test
0102030405060708090
100
0 200000 400000 600000 800000 1000000
Cycles
Stif
fnes
s
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Simulation of the test
The stiffness loss is due to
•An increase of temperature due to viscoelasticity
•Thixotropy
•Damage
Assumptions :
•The temperature increase is neglected (stiffness loss of 3%)
•Elastic damage (we are interested in the final state of the specimen)
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Simulation of the test
)10 DEE
3
1
12
)(1ln
DFD
NDF a
1
1
22IIIa
kk
kIIkIkk
lcr
a S
Sei
224
2
2
Three parameters damage test
1 = 50 – 2 = 5 – 3 = 3
= 0,5
r = 4mm
lc = 3mm
a is the weighted mean of the strain for elements which are within a circle of r radius of the examined element
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Specimen simulation
Image creation
Image meshing
Scale : 1 mm = 1 pixel
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Specimen simulation
gr3 gr2 gr1
aggregates 74.1 % 88.8% 90.1%
deviation=0.9% =0. 8% =1.3%
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Simulation • 3 granulometries :
0
20
40
60
80
100
120
0 10 20 30 40 50 60
diameter (mm)
frequ
ency
granulometry 1
granulometry 2
granulometry 3
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Results granulometry 1
60
65
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80
85
90
95
100
0 50000 100000 150000 200000 250000 300000 350000
cycles
stiff
ness
loss
mean
gr01 min
gr01 max
0
20
40
60
80
100
120
0 10 20 30 40 50 60
diameter (mm)
frequ
ency mean
max
min
16 specimens
Granulometry computed on the initial image
Results of the simulation
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Results granulometry 2
9 specimens
Granulometry computed on the initial image
Results of the simulation
60,00
65,00
70,00
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85,00
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95,00
100,00
0 50000 100000 150000 200000 250000 300000 350000
cycles
stiff
ness
loss
mean
gr02 min
gr02 max
0102030405060708090
100
0 10 20 30 40 50 60
diameter (mm)
frequ
ency
mean
max
min
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Results granulometry 3
0102030405060708090
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0 5 10 15 20 25 30 35
diameter (mm)
frequ
ency
mean
max
min
8 specimens
Granulometry computed on the initial image
Results of the simulation
70,00
75,00
80,00
85,00
90,00
95,00
100,00
0 50000 100000 150000 200000 250000 300000 350000
Cycles
Stiff
ness
loss
meangr03 mingr03 max
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Comparaison of the 3 simulations
60,00
65,00
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85,00
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95,00
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0 50000 100000 150000 200000 250000 300000
cycle number
stiff
ness
loss
gr01 min gr01 max gr02 mingr02 max gr03 min gr03 maxreal real realreal
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Results granulometry 4
9 specimens
Results of the simulation
5 % of asphalt mastic element were weak :
Eb = 9Mpa instead of 90 Mpa60,00
65,00
70,00
75,00
80,00
85,00
90,00
95,00
100,00
0 20000 40000 60000 80000
cycles
stiff
ness
60,00
65,00
70,00
75,00
80,00
85,00
90,00
95,00
100,00
0 10000 20000 30000 40000 50000 60000 70000
Cycles
Stiff
ness
mean
max alea
min alea
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Discussion
Granulometry does not explain the dispersion
The introduction of 5 % aleas in the asphalt mastic phase increases the brittleness
The model with the chosen parameters cannot modelize the localization
Possible causes :
There are more then 5% feeble points in the mastic phase.
The damage program favors the damage on one side of the specimen
Localization begins sooner in the second phase of the test
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Perspectives
● Identification method to set● Simulations with more aleas in the mastic phase● Healing simulation ● Multiscale simulation