Ames, IA
August 15-16, 2013
Establishment of Relation between Pavement
Surface Friction and Mixture Design Properties
Mozhdeh Rajaei
Nima Roohi Sefidmazgi
Hussain Bahia, Ph.D.
Outline
1. Background and Introduction
2. Materials and Methods
3. Results and Conclusions
BACKGROUND AND INTRODUCTION
Friction in Pavement
• The cost for highway accidents in 2000 exceeded $230 billion.
Many of these crashes are tied to wet road conditions, and
inadequate friction characteristics (Noyce et al., 2007).
• Factors affecting friction:
 pavement surface characteristics,
 vehicle characteristics,
 tire characteristics, and
 environmental conditions
Surface Texture
• Surface texture refers to the combination of different aggregate shapes and
sizes used in asphalt mixtures. Surface texture is defined in terms of
wavelength (λ, distance along the surface) and amplitude (a, height above
the surface).
(Henry 2000)
Factors Affecting Texture
Property
Texture Range
Nominal Maximum Aggregate Size (NMAS)
Macro-Texture
Mixture Coarse Aggregate Type
Macro-Texture
Micro-Texture
Mixture Fine Aggregate Type
Macro-Texture
Micro-Texture
Asphalt Binder Content
Macro-Texture
Aggregate Gradation
Macro-Texture
Mixture Air Voids
Macro-Texture
(Sandberg 2000, Hall 2009, Ahamed 2009)
Objectives of Study
1. Relate lab/field friction measures to mixture
properties
2. Relating lab texture measurements to field friction
measures
Materials and Methods
Stationary Laser Profilometer (SLP)
Circular Track Meter (CTM)
Friction Number (FN)
Methods
•Field Friction Measurement:
– Friction Number (FN)
•Field Texture Measurement:
– Circular Track Meter (CTM)
•Laboratory Texture Measurement:
– Stationary Laser Profilometer (SLP)
Pavement Friction Measures
•Friction number (FN):
 The average coefficient of friction measured by a locked-wheel test device as
specified in ASTM E274.
 This device was developed to use in situations with no anti-lock brakes.
 Skid Trailer was K.J. Law Profiler.
FN (V) = 100 * μ = 100 * F/W
•
•
•
•
V is velocity of the test tire, km/hr (65 km/hr).
μ is the coefficient of friction.
F is the tractive horizontal force applied to the tire, kg.
W is the vertical load applied to the tire, kg.
Stationary Laser Profilometer (SLP)
• Used both in the laboratory and in the field.
• Texture measurements described in ISO 13473-4.
Lab Texture Measure
Profile Depth
(mm)
•Mean Profile Depth (MPD):
4.0
3.0
2.0
1.0
0.0
-1.0 0
-2.0
-3.0
-4.0
500
1000
1500
2000
2500
3000
3500
4000
Data Point
 MPD values yield a two-dimensional representation of the surface
texture (ISO 13473-1 2004).
 MPD texture parameters provide averaged values for surface
texture but do not quantify the distribution of asperities at the
pavement surface.
Circular Track Meter (CTM)
• Measures pavement macrotexture in circular area
– SLP make’s linear measure.
• Standardized under ASTM
E2157 2009.
Materials
•Field sections and corresponding cores from
across WI.
•Field Sections and corresponding cores from
MnROAD, MN.
•Both dense graded and porous/gap graded.
• Different mixture properties:
– Varying NMAS, Pb, gradation and density.
Weibull Distribution
• In order to describe gradation with the minimum number of
variables, a Weibull distribution is fitted to gradation curve.
• x is the aggregate size (mm)
• κ is the shape factor
• λ is the scale factor
100%
100%
Increasing λ
80%
Percent Passing
Percent Passing
80%
60%
40%
20%
60%
40%
20%
0%
Increasing κ
0%
Sieve Size
0.45
Sieve Size 0.45
ANALYSIS AND DISCUSSION
Regression Analysis
•Regression analysis has been performed using
Minitab16.
•The magnitude of the statistical parameter, pvalue, for each variable is an indicator of the
significance of that variable
– p-value closer to zero indicates high significance.
– Significance of values approaching 1.0 is negligible.
Statistical Model
Lab Friction vs. Mix Design Properties
• Laser MPD = 9.47 - 3.20 Gmb - 0.356 Pb + 0.0846 NMAS + 1.35 κ - 1.48 λ
–
–
–
–
–
Where MPD is the mean profile depth in millimeter,
Gmb is bulk asphalt mixture density (g/cm3),
Pb is the binder percent,
NMAS is the nominal maximum aggregate size in millimeter,
κ and λ are the Weibull distribution parameters.
Predictor
Coefficient
Standard Error Coefficient
T value
P value
Constant
Gmb
Pb
9.467
-3.197
-0.356
4.040
1.115
0.315
2.340
-2.870
-1.130
0.036
0.013
0.278
NMAS
κ
0.085
1.354
0.043
0.234
1.940
5.800
0.074
0.000
λ
-1.476
0.360
-4.100
0.001
Model Quality of Fit
Estimated SLP MPD (mm)
2.5
Dense Graded and Porous
Dense Graded
Equality
2
1.5
R² = 0.78
R² = 0.60
1
0.5
0
0
0.5
1
1.5
2
Measured SLP MPD (mm)
2.5
3
Discussion of Model
• NMAS: Positive coefficient
– Gradations with higher NMAS, (generally coarser gradations) result in higher MPD
• Bulk specific gravity (Gmb): Negative Coefficient
– Lower Gmb, (thus higher air voids and porosity), leads to higher MPD.
• Binder Content (Pb): Negative Coefficient
– Lower Pb reduces binder film thickness around aggregates as well as reducing the
aggregate packing level, thus increasing MPD.
• Weibull Shape Factor (κ): Positive coefficient
– Higher κ values will result in gradations closer to a one-sized gradation and further from the
maximum density line, thus resulting in higher MPD values.
• Weibull Scale Factor (λ): Negative coefficient
– Decreasing λ will generally result in finer gradation. If all curves above max density line,
lower λ will being further from line.
Discussion of Model: Gradation
• It hypothesized that what is important for gradation is
being further from the maximum density line, and not only
the overall coarseness or fineness of the gradation.
100%
90%
% Passing
80%
Decreasing λ
70%
60%
50%
40%
30%
20%
10%
0%
0.00
0.50
1.00
1.50
2.00
2.50
Sieve Opeining Size (mm0.45)
3.00
Filed Friction vs. Lab Friction
Almost
equivalent
for dataset
•
•
CTM MPD is the mean profile depth (mm) measured using the CTM in the field,
SLP MPD is the mean profile depth (mm) measured using the laser profilometer in the laboratory.
Relating Laboratory Texture to Field Friction
• FN is the smooth-tire friction number from field measurements,
• CTM MPD is the mean profile depth (mm) measured using the CTM in the field.
Using SLP-CTM
Model
• FN is the smooth-tire friction number from field measurements,
• SLP MPD is the mean profile depth (mm) measured using the laser profilometer
in the laboratory
Conclusions
• Using statistical analysis mixture design parameters (i.e. volumetric
and aggregate gradation properties) could be related to laboratory
texture measurements (MPD).
• Knowing mixture design properties can lead to the estimation of road
texture parameters.
• It was shown that increasing the distance of the gradation curve from
the maximum density line (on both the coarse or fine side) is more
important than the overall coarseness or fineness of the gradation in
terms of increasing the expected texture.
Conclusions
• Laboratory measured friction parameters (MPD) can be related to
field friction values (FN) using regression analysis.
• Utilizing the models developed in this study, by further
investigation, mixture designers can have a guideline to estimate
friction.
• Models developed in this study showed that the measurements for
field and laboratory compacted samples from SLP device can be
used to estimate friction parameters.
• A limited data set were used to develop models in this study,
therefore more tests and analysis are needed to verify the results.
Acknowledgements
•This research was sponsored by CFIRE under project
I.D. 07-09 and the Western Research Institute
"Asphalt Research Consortium".
•Authors would also like to acknowledge the
contributions of Mr. Timothy Miller, formerly of UWMadison; as well as MnROAD for use of their test track
database friction measurements.
Thank You!
Questions?
www.uwmarc.org
Mozhdeh Rajaei
rajaei@wisc.edu
Nima Roohi Sefidmazgi
roohisefidma@wisc.edu
Hussain Bahia
bahia@engr.wisc.edu