The 16th BESETO Conference
6 - 8 August 2025, Kanazawa University, Japan
Developing a Prediction Model for Water Film
Thickness and Its Impact on Pavement Friction
and Road Geometry
Chann Seng, Ph.D. Student
Choi, Yein, Ph.D. Student
Young Kyu Kim, Ph.D., Research Professor
Seung Woo Lee, Ph.D., Professor
6 2024.Nov.16
- 8 August 2025
1. Purpose of study
▪
Tining concrete surface is typical in many country including Korea.
✓ This study investigates the effects of various rainfall intensities, pavement
slopes, drainage lengths, and surface textures on the water film thickness on
Tining and Diamond-grooving concrete pavements.
▪
Wet pavement friction coefficient is used for road geometry design and pavement
management.
▪
What is wet condition? WFT = 0.5mm ? 1mm ? 2mm?
✓ Investigate the influence of WFT on wet pavement friction by using the British
Pendulum Test (BPT)
▪
BPN measurement by ASTM 303-93 request providing wet condition as spraying
water on the pavement surface,
✓ Figure out the WFT corresponding with the BPN measurement by ASTM 303-93
Presented by: Chann SENG, 2025
2
2. Introduction
2.1 Friction Coefficient for Road Geometry Design
▪ Based on vehicles crash data, the possibility of causing accidents on wet pavements is 10
times greater than on dry pavements (Abdic et al., 2016; Ling et al., 2023).
❑ Stopping Sight distance (Ds)
❑ Radius of the curve (R)
Rmin = (Vd)2/[15(e+ fRmax )]
SSDmin = 1.47Vdt + (Vd)2/30 fTmax
SSDmin : minimum stopping sigh distance (ft)
Rmin
: minimum Radius of curve (ft)
Vd
: design speed (mph)
V
: design speed (mph)
fTmax
: maximum allowable tangential friction factor
fRmax
: maximum allowable side friction factor
t
: perception-reaction time
e
: maximum superelevation rate (ft/ft)
Note: fRmax = 0.925 • 0.4 fTmax ,the factor 0.925 represent only the tire specific influence (Lamm et
al., 1991)
Forward
Visibility Splay
Vehicle turning right
2.0 m
0.6m
Fig. 1. Stopping Sign Distance
Presented by: Chann SENG, 2025
Fig. 2. superelevation in road
3
2. Introduction
2.2 Mechanism of Friction in Dry and Wet Conditions
▪ Dry Conditions: Adhesion plays the key role in friction, mainly dependent on micro-texture,
while hysteresis contributes but is less significant.
▪ Wet Conditions: Hysteresis, influenced by macrotexture, has a greater effect than adhesion,
which is reduced by the water film thickness (WFT) (Persson et al., 2001; Fwa, 2021).
Sliding Direction
Sliding Direction
Rubber Element
Adhesion
Adhesion
Adhesion depends
mostly on micro
Hysteresis
Hysteresis depends
mostly on macro
Hysteresis
Fig. 3. Mechanisms of pavement skid resistance generation
Presented by: Chann SENG, 2025
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2. Introduction
2.3 Influence of WFT on Pavement Friction Performance
▪ Hydroplaning occurs when a layer of water builds up between the tire and the road surface,
causing lose contact area between vehicle tire and pavement surface (Persson et al.,2001).
▪ This reduces the friction between the tire and the road, leading to a loss of control and
causing accident (Persson et al.,2001).
▪ The higher WFT, the smaller the contact area becomes (Fwa, 2021).
▪ Wet pavement friction varies significantly with Water film thickness (WFT)
▪ Water film thickness (WFT) was affected by the pavement slope, rainfall intensity, drainage
path length and pavement texture (Ling, et al., 2023).
Full Road Contact
Tire hits standing water and
cuts through
Reduce Road Contact
Water will build up in front
of the tire
Hydroplaning
Tire fully was separated from
the pavement surface by WFT
Fig. 4. Hydroplaning
Presented by: Chann SENG, 2025
5
2. Introduction
2.4 Factors affect the water film thickness
▪ According to previous studies (Ling, et al., 2023; Gallaway, et al., 1971; Lou, et al., 2016; Xiao,
et al., 2023), WFT is considered to be highly correlated with
•
Rainfall Intensity
•
Pavement Slope
•
Drainage Path Length
•
Mean Texture Depth
Fig. 5. Factors Affecting Water film thickness
Presented by: Chann SENG, 2025
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2. Introduction
2.5 The existing WFT prediction equations
Table 1. Summary of the Equations in the Existing Model
Source
Equations
Gallaway WFT= 0.01485 [MTD0.11L0.43I0.59S-0.42] - MTD
RRL
PAVDRN
Parameter
WFT : Water film
thickness
(mm),
•
Rolled asphalt
MTD : Mean Texture
Depth
(mm),
•
Brushed-finish
concrete
L
: Drainage Path
Length
(m),
•
Asphalt
concrete
I
: rainfall
intensity
(mm/h),
•
Dense grade
friction course
S
: Pavement
slope (m/m)
•
Open grade
friction course
n
: Manning’s n
value
WFT= 0.046 [ LI0.5 S-0.2] - MTD
𝐖𝐅𝐓 = 𝐧𝐋𝐈 36.1 𝐒 −0.5 −0.6 − 𝐌𝐓𝐃
Presented by: Chann SENG, 2025
Pavement Surface
7
3. WFT Measurements using Rainfall Simulator
3.1 Rainfall Simulator
Rainfall Simulator Capacity
▪ Rainfall Intensity
: 0 -130
mm/h
▪ Pavement Slope
: 0 -15
%
▪ Drainage Length
: 0 - 5.5
%
▪ Specimen
:3
25 sprinklers
Rainfall
Simulator
Heigh: 5.5m
Sprinkler Rotation
controller
(controlling intensity)
Hydraulic jack
adjustment
(Slop controller
= 0-15%)
Water pressure
(controlling intensity)
Specimen Width: 1.2m
Water Tank
Water Pump
Specimen length: 5.5m
Fig. 6. Rainfall Simulator at GWNU
Presented by: Chann SENG, 2025
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3. WFT Measurements using Rainfall Simulator
3.2 Water film thickness (WFTs) measurement
▪
The water film thickness (WFT) was measured at the same times with Various
condition of the pavement slopes (2-10%), drainage path length (1-5m), rainfall
intensity (30-130mm/h) and surface texture.
▪
A water film thickness gauge, calibrated with a 0–5 mm scale, was used to
measure the water film thickness (WFT) under a rainfall simulator
Fig. 7. Measurement of the WFT
Presented by: Chann SENG, 2025
Fig. 8. Water Film thickness Guage
9
3. WFT Measurements using Rainfall Simulator
3.3 Study Condition
Table 2. Test Condition
Pavement Surface
•
Non tining
•
Tining surface with 16mm spacing
•
Tining surface with 25mm spacing
•
Diamond Grooving with 20mm spacing
Non Tining
Tining surface with
16mm spacing
MTD
(mm)
Durations
(minutes)
0.3
0.8
0.9
1.4
5
10
15
50
Pavement
Slope
(%)
2
5
10
Tining surface with
25mm spacing
Rainfall
Intensity
(mm/h)
Drainage
Path
length
(m)
40
80
130
1
2
3
4
5
Diamond grooving
with 25mm spacing
16mm
Fig. 9. Pavement Texture Geometry
Presented by: Chann SENG, 2025
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4. Result of WFT measurement
4.1 Effect of Drainage Path Length on Water film thickness
Condition: Rainfall Intensity: 80mm/h
Pavement Slope: 2%
2.5
Water Film Thickness (mm)
Water Film Thickness (mm)
Diamond Grooving
Tining Surface with 16mm spacing
Tining Surface with 25mm spacing
Non Tining
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
5
Condition:Rainfall Intensity: 130mm/h
Pavement Slope: 2%
Diamond Grooving
Tining Surface with 16mm spacing
Tining Surface with 25mm spacing
Non Tining
2.5
2.0
1.5
1.0
0.5
0.0
6
Drainage Path Length (m)
0
1
2
3
4
5
6
Drainage Path Length (m)
Water Film Thickness (mm)
Condition: Rainfall Intensity: 40mm/h
Pavement Slope: 2%
Diamond Grooving
Tining Surface with 16mm spacing
Tining Surface with 25mm spacing
Non Tining
2.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
5
6
Drainage Path Length (m)
Fig. 10. Effect of Drainage Path Length on Water film thickness
Presented by: Chann SENG, 2025
11
4. Result of WFT measurement
4.2 Effect of Pavement Slope on Water film thickness
Diamond Grooving
Tining Surface with 16mm spacing
Tining Surface with 25mm spacing
Non Tining
2.5
Diamond Grooving
Tining Surface with 16mm spacing
Tining Surface with 25mm spacing
Non Tining
2.5
Diamond Grooving
Tining Surface with 16mm spacing
Tining Surface with 25mm spacing
Non Tining
2.0
1.5
1.0
0.5
0.0
0%
4%
8%
2.0
1.5
1.0
0.5
0.0
12%
Pavement Slope (%)
0%
4%
8%
Pavement Slope (%)
12%
Water Film Thickness (mm)
Condition:Rainfall Intensity: 130mm/h
Drainage Length : 5m
Water Film Thickness (mm)
Condition: Rainfall Intensity: 80mm/h
Drainage Length : 5m
Water Film Thickness (mm)
Condition: Rainfall Intensity: 40mm/h
Drainage Length : 5m
2.5
2.0
1.5
1.0
0.5
0.0
0%
4%
8%
12%
Pavement Slope (%)
Fig. 11. Effect of Pavement Slope on Water film thickness
Presented by: Chann SENG, 2025
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4. Result of WFT measurement
4.3 Effect of Rainfall Intensity on Water film thickness
Condition Pavement Slope : 5%
Drainage Length : 5m
2.5
2.0
1.5
1.0
0.5
0.0
0
25
50
75 100 125 150
Diamond Grooving
Tining Surface with 25mm spacing
Tining Surface with 16mm spacing
Non Tining
Water Film Thickness (mm)
Water Film Thickness (mm)
Diamond Grooving
Tining Surface with 25mm spacing
Tining Surface with 16mm spacing
Non Tining
Condition
2.5
2.0
1.5
1.0
0.5
0.0
Rainfall Intensity (mm/h)
0
25
50
75 100 125 150
Rainfall Intensity (mm/h)
Pavement Slope : 10%
Drainage Length : 5m
Diamond Grooving
Tining Surface with 25mm spacing
Tining Surface with 16mm spacing
Non Tining
Water Film Thickness (mm)
Condition: Pavement Slope : 2%
Drainage Length : 5m
2.5
2.0
1.5
1.0
0.5
0.0
0
25
50
75 100 125 150
Rainfall Intensity (mm/h)
Fig. 12. Effect of Rainfall Intensity on Water film thickness
Presented by: Chann SENG, 2025
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4. Result of WFT measurement
4.3 Effect of Mean Texture Depth on Water film thickness
2%
5%
3.0
Tining Surface
with 25mm
spacing
2.5
2.0 None Tining
Tining Surface
with 16mm
spacing
1.5
1.0
0.5
Diamond Grooving
with 20mm spacing
0.0
0
0.4
0.8
1.2
10%
Water Film Thickness (mm)
Water Film Thickness (mm)
10%
Condition: Rainfall Intensity: 80mm/h
Drainage Length : 5m
2.5
Tining Surface
with 25mm
spacing
Tining Surface
with 16mm
spacing
None Tining
2.0
1.5
1.0
Diamond Grooving
with 20mm spacing
0.5
10%
5%
3.0
0.0
1.6
Mean Texture Depth (mm)
2%
Condition: Rainfall Intensity: 130mm/h
Drainage Length : 5m
Water Film Thickness (mm)
Condition: Rainfall Intensity: 40mm/h
Drainage Length : 5m
2%
3.0
None Tining
2.5
2.0
5%
Tining Surface
with 25mm
spacing
Tining Surface
with 16mm
spacing
1.5
1.0
Diamond Grooving
with 20mm spacing
0.5
0.0
0
0.4
0.8
1.2
1.6
Mean Texture Depth (mm)
0
0.4
0.8
1.2
1.6
Mean Texture Depth (mm)
Fig. 13. Effect of Mean Texture Depth on Water film thickness
Presented by: Chann SENG, 2025
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5. Developing a GWNU WFT Prediction Model
5.1 GWNU WFT Prediction Model for Tining Concrete Pavement
WFT = 0.3724 [MTD0.072 L0.25 I0.22 S-0.144]-MTD
2.5
Where
Line of equality
GWNU model
2.0
: Water Film thickness (mm)
: Mean Texture Depth (mm)
: Drainage Path Length (m)
: Rainfall Intensity (mm/h)
: Pavement Slope (%)
Predition WFT (mm)
WFT
MTD
L
I
S
(R2 = 0.93, P-value 0.023)
R² = 0.9337
1.5
1.0
0.5
0.0
0.0
0.5
1.0
1.5
2.0
2.5
Measured WFT (mm)
Fig. 14. Measured WFTs and Predicted WFTs
Presented by: Chann SENG, 2025
15
5. Developing a GWNU WFT Prediction Model
5.2 Comparison The PAVDRN, Gallaway and the RRL prediction model
2.5
2.0
GWNU model
RRL model
Gallway model
PAVDRN model
Predition WFT (mm)
1.5
Predition WFT (mm)
2.0
1.5
1.0
Tining surface
with 25 mm
spacing
0.5
0.5
1.0
1.5
Measured WFT (mm)
2.0
1.0
0.5
Tining surface
with 16 mm
spacing
0.0
0.0
0.0
GWNU model
RRL model
Gallway model
PAVDRN model
2.5
0.0
0.5
1.0
1.5
2.0
Measured WFT (mm)
Fig. 15. Comparison the WFT prediction and WFT measured for tining surface
▪
▪
▪
RRL underestimates WFT by 0.7 mm (25 mm spacing) and 0.6 mm (16 mm spacing).
PAVDRN underestimates WFT by 0.6 mm for both 25 mm and 16 mm spacing.
Gallaway underestimates WFT by 0.8 mm for both 25 mm and 16 mm spacing.
▪ The PAVDRN, RRL, and Gallaway models underestimate WFT on tined surfaces as they are
statistical models developed for asphalt concrete texture.
Presented by: Chann SENG, 2025
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5. Developing a GWNU WFT Prediction Model
5.2 Comparison The PAVDRN, Gallaway and the RRL prediction model (continued)
2.5
GWNU model
RRL model
Gallway model
PAVDRN model
Predition WFT (mm)
2.0
1.5
1.0
0.5
Non Tining
0.0
0.0
0.5
1.0
1.5
2.0
2.5
Measured WFT (mm)
Fig. 16. Comparison the WFT prediction and WFT measured for non tining surface
▪
▪
▪
RRL underestimates WFT by 0.1 mm for non tining surface
PAVDRN underestimates WFT by 0.1 mm for non tining surface
Gallaway underestimates WFT by 0.4 mm for non tining surface
▪
PAVDRN and RRL models underestimate WFT less on non-tined surfaces, as they are
statistical models developed for broom-finished and burlap concrete.
Presented by: Chann SENG, 2025
17
5. Developing a GWNU WFT Prediction Model
5.2 Comparison The PAVDRN, Gallaway and the RRL prediction model (continued)
3.0
GWNU model
RRL model
Gallway model
PAVDRN model
Predition WFT (mm)
2.5
2.0
1.5
1.0
Daimond
Grooving
0.5
0.0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Measured WFT (mm)
Fig. 17. Comparison the WFT prediction and WFT measured for Diamond Grooving Surface
▪
▪
▪
RRL overestimates WFT by 0.7 mm for Daimond Grooving
PAVDRN overestimates WFT by 0.6 mm for Daimond Grooving
Gallaway overestimates WFT by 0.7 mm for Daimond Grooving
▪
GWNU underestimate WFT less (0.04mm) on Daimond Grooving, as they are statistical models
developed for Tined Concrete pavement which has similar texture (differing only in groove
spacing, width, and depth)
Presented by: Chann SENG, 2025
18
6. Friction Measurements using British Pendulum Test
6.1 British Pendulum Number measurement (ASTM 303-93)
▪ Following ASTM E303-93 standard procedures, WFT was simulated by spraying water on
the pavement surface.
▪ However, the measurement of BPN did not include specific information about the thickness
of the water film present during the testing.
(a)
(b)
Fig. 18 (a) dry condition, wet condition following ASTM 303-93 and (b) wet condition using the
rainfall simulator
Presented by: Chann SENG, 2025
19
6. Friction Measurements using British Pendulum Test
6.2 British Pendulum Number measurement with various WFTs
▪ The BPN was measured under 3 condition (dry condition, wet condition following ASTM
303-93, wet condition using the rainfall simulator)
▪ The BPN was measured with various condition of rainfall intensity, slope, drainage length
and texture depth.
Transverse Tined
Longitudinal Tined
Fig.19. Wet Condition and dry condition (WFT was
simulate by the spraying)
Presented by: Chann SENG, 2025
Wet Condition
Fig. 20. Wet Condition (WFT
was simulate by the Rainfall
Simulator)
20
7. Influence of WFTs on BPNs
7.1 Influence of WFTs on BPNs for Different Transverse Surface Types
Transveres Tined Surface with 16mm spacing
Transveres Tined Surface with 25mm spacing
Transverse Diamond Grooving
Non Tining
Transverse Grooving
BPN = -4.9 WFT + 85
R² = 0.62
Transverse Tining with 16mm
BPN = -5.5 WFT + 80
R² = 0.61
Transverse Tining with 25mm
BPN = -10.1 WFT + 83.6
R² = 0.63
Non Tining Surface
BPN = -14 WFT + 79
R² = 0.60
90
BPN by ASTM
303-93
BPN by ASTM
303-93
85
BPN
80
78
BPN by ASTM
303-93
70
62
60
50
40
0
0.4 0.5
1 1.2
1.5
2
2.5
3
WFT (mm)
Fig. 21. Relationship Between WFT and BPN for difference Transverse Surface Types
Presented by: Chann SENG, 2025
21
7. Influence of WFTs on BPNs
7.2 Influence of WFTs on BPNs for Different Longitudinal Surface Types
Longitudinal Tined Surface with 16mm spacing
Longitudinal Tining Surface with 25mm spacing
Longitudinal Grooving
Longitudinal Diamond Grooving
BPN = -13.9 WFT + 84
Non Tining
R² = 0.63
Non Tining Surface
BPN = -14 WFT + 79
R² = 0.60
90
BPN by ASTM
303-93
BPN by ASTM
303-93
85
82
80
78
75
BPN
70
Longitudinal Tining with 16mm
BPN = -15 WFT + 81
R² = 0.60
Longitudinal Tining with 25mm
BPN = -18.87 WFT + 83
R² = 0.58
65
60
55
50
45
40
0
0.2 0.3
0.5
1
1.5
2
2.5
3
WFT (mm)
Fig. 22. Relationship Between WFT and BPN for difference Transverse Surface Types
Presented by: Chann SENG, 2025
22
7. Influence of WFTs on BPNs
7.3 Influence of WFTs on BPNs for Different Transverse Surface Types
Table 3. Summary of WFTs Corresponding to BPNs for Various Surface Types
Pavement Surface
BPN dry
condition
BPN wet
condition
following
ASTM 303-93
Corresponding
WFT
(mm)
Non Tining Surface
83
62
1.2
Longitudinal Tined Surface with 25 mm spacing
83
78
0.2
Longitudinal Tined Surface with 16 mm spacing
85
80
0.2
Transverse Tined Surface with 25 mm spacing
87
78
0.4
Transverse Tined Surface with 16 mm spacing
84
80
0.4
Longitudinal Diamond Grooving with 20 mm spacing
86
82
0.3
Transverse Diamond Grooving with 20 mm spacing
90
85
0.5
Presented by: Chann SENG, 2025
23
8. Conclusion
✓ The GWNU WFT prediction equation for tining concrete pavement were
developed based on WFT measurements under various conditions of
rainfall intensity, pavement slope, drainage path length, and mean texture
depth.
✓ The GWNU WFT equation may provide more reliable predictions of WFT
for tining concrete pavement compared to previous equations.
✓ The relationship between BPN and WFT for tining and diamond-grooved
surfaces is suggested.
✓ Transverse diamond-grooved surfaces demonstrate less reduction in BPN
with increasing WFT compared to other surface types.
Presented by: Chann SENG, 2025
24
8. Conclusion
✓ The GWNU WFT prediction equation for tining concrete pavement were
developed based on WFT measurements under various conditions of
rainfall intensity, pavement slope, drainage path length, and mean texture
depth.
✓ The GWNU WFT equation may provide more reliable predictions of WFT
for tining concrete pavement compared to previous equations.
✓ The relationship between BPN and WFT for tining and diamond-grooved
surfaces is suggested.
✓ Transverse diamond-grooved surfaces demonstrate less reduction in BPN
with increasing WFT compared to other surface types.
Presented by: Chann SENG, 2025
25
THANK YOU !
Seng, Chann
Department of Civil Engineering
Gangneung-Wonju National University (GWNU)
E-mail : sengchann2356@gamil.com