Estimation of Stone-loss on network condition surveys by use of multiple texture lasers

Thomas Wahlman, thomas.wahlman@ramboll.sePeter Ekdahl, peter.ekdahl@ramboll.se

OUTLINE

•5 years of experience in Finland

•Ravelling project in Netherlands

•Homogeneity

Indication of RavellingFinland

…detected by point lasers

4

Basic information of collected data

The Laser works at a frequency of 32 000 pulses per second

Speed km/h

Interval between

values30 0.3 mm50 0.4 mm70 0.6 mm90 0.8 mm

Spotsize 0.5 mm

Vertical resolution 0.1 mm

Porous Asphalt, 16 years old

-20

-15

-10

-5

0

5

10

1100 1120 1140 1160 1180 1200 1220 1240 1260 1280 1300 1320 1340 1360 1380 1400

Dep

th

mm-data

Even Surface

Max stone size

What will the collected values look like?

Dense Asphalt, 12 years old

-20

-15

-10

-5

0

5

276.2 276.3 276.4 276.5

Depth

mm-data

What is what? Crack or Loss of stone?

6

Indication of Ravelling - Model

Input

Divide into homogenous sections-similar surface type

Read all RMST value of each 100mm

Look for possible ravelling in each 5m-interval

Step 1

Step 2

Output Validate result and state Ravelling/Not Ravelling per 5m

7

Indication of Ravelling. Change in Surface type

Dis

tan

ce

Avera

ge

Mod

e

Max

Std

dev

Ku

rtosis

Skew

ness

Ran

ge

PER

C 5

%

PER

C 9

5%

0.4

0.5

0.6

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0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

3820 0.8 0.8 1.2 0.1 0.6 0.9 0.6 1 1.05 26% 32% 20% 10% 10% 2%3825 0.8 0.8 1.3 0.2 2.6 1.3 0.8 1 1.06 10% 28% 24% 20% 12% 2% 4%3830 0.9 0.9 1.3 0.2 ## 0 0.9 1 1.21 2% 8% 10% 12% 28% 18% 10% 6% 6%3835 0.9 0.8 1.5 0.2 1.5 1.1 1 1 1.32 4% 12% 18% 26% 18% 8% 6% 2% 2% 2% 2%3840 0.9 0.9 1.4 0.2 ## 0.5 0.8 1 1.22 8% 10% 16% 24% 18% 8% 8% 4% 4%3845 0.9 0.6 1.3 0.2 ## 0.3 0.9 1 1.31 4% 2% 18% 12% 18% 22% 2% 14% 2% 6%3850 0.8 0.9 1.2 0.1 1.9 0.7 0.7 1 0.95 8% 12% 36% 32% 8% 2% 2%3855 0.8 0.7 1.2 0.2 ## 0.7 0.6 1 1.17 2% 24% 18% 26% 12% 8% 8% 2%3860 0.9 0.7 1.3 0.2 ## 0.2 0.8 1 1.15 2% 8% 8% 20% 22% 16% 16% 6% 2%3865 0.9 0.9 1.5 0.2 0.9 0.7 0.9 1 1.14 8% 18% 12% 24% 18% 10% 8% 2%3870 0.9 0.9 1.5 0.2 2.0 0.6 1 1 1.17 2% 2% 6% 18% 26% 26% 8% 8% 2% 2%3875 0.8 0.7 1.3 0.2 0.4 0.5 0.8 1 1.15 4% 4% 20% 26% 22% 8% 8% 4% 4%3880 0.8 0.9 1.3 0.2 0.2 0.4 0.8 1 1.11 6% 18% 18% 32% 12% 8% 4% 2%3885 0.9 0.8 1.2 0.1 ## 0.3 0.6 1 1.07 2% 12% 34% 12% 24% 12% 2% 2%3890 0.8 0.8 1.2 0.2 ## 0.1 0.7 1 1.09 2% 16% 6% 22% 24% 16% 10% 4%3895 0.9 0.8 1.4 0.2 0.1 0.4 1 1 1.28 2% 12% 14% 26% 18% 10% 8% 8% 2%3900 0.9 0.8 1.4 0.2 0.5 0.3 0.9 1 1.12 10% 10% 14% 22% 18% 20% 4% 2%3905 0.9 1.0 1.2 0.1 ## ## 0.6 0.7 1.1 4% 8% 18% 22% 26% 20% 2%3910 0.9 0.8 1.2 0.1 0.5 0.2 0.7 0.7 1.1 4% 12% 20% 36% 12% 12% 2% 2%3915 0.8 0.9 1.2 0.2 ## 0.2 0.7 0.6 1.2 2% 8% 16% 12% 24% 24% 4% 4% 6%3920 0.8 0.7 1.3 0.2 0.3 0.5 0.8 0.6 1.2 4% 22% 10% 32% 20% 4% 4% 4%3925 1.0 0.9 1.5 0.2 ## 0.1 1.0 0.6 1.3 6% 8% 10% 14% 24% 10% 14% 6% 6% 2%3930 1.0 1.0 1.4 0.2 ## 0.0 0.8 0.7 1.3 2% 8% 14% 8% 26% 24% 6% 8% 4%3935 1.0 0.8 1.6 0.2 ## 0.3 0.9 0.7 1.3 6% 10% 12% 22% 14% 16% 14% 4% 2%3940 1.0 0.9 1.4 0.2 ## 0.1 0.8 0.7 1.4 2% 2% 10% 12% 20% 18% 14% 10% 6% 6%3945 1.0 1.0 1.6 0.2 0.5 0.7 1.0 0.8 1.3 2% 10% 24% 20% 16% 12% 10% 4% 2%3950 1.0 1.1 1.5 0.2 ## 0.2 1.0 0.6 1.4 4% 14% 12% 14% 6% 24% 6% 6% 10% 2% 2%3955 0.9 0.9 1.2 0.1 ## 0.1 0.6 0.7 1.2 2% 20% 14% 30% 20% 8% 6%3960 0.7 0.9 1.5 0.4 ## 0.2 1.2 0.3 1.3 12% 22% 10% 2% 2% 4% 20% 6% 10% 4% 6% 2% CHANGE IN SURFACE TYPE3965 0.3 0.3 0.6 0.1 2.7 1.3 0.4 0.2 0.5 2% 42% 46% 6% 4%3970 0.3 0.3 0.5 0.1 2.5 0.3 0.4 0.2 0.4 4% 36% 54% 4% 2%3975 0.3 0.3 0.4 0.0 ## 0.2 0.2 0.2 0.4 52% 46% 2%3980 0.3 0.2 0.5 0.1 0.6 0.7 0.3 0.2 0.4 60% 36% 4%3985 0.3 0.4 0.5 0.1 ## 0.0 0.3 0.2 0.4 2% 32% 54% 12%3990 0.4 0.4 0.7 0.1 0.5 0.7 0.5 0.3 0.6 22% 34% 30% 8% 4% 2%3995 0.3 0.3 0.6 0.1 0.5 0.6 0.4 0.2 0.5 2% 28% 50% 16% 4%4000 0.3 0.3 0.5 0.1 ## 0.0 0.3 0.3 0.4 2% 28% 56% 14%4005 0.3 0.3 0.6 0.1 6.2 1.7 0.4 0.2 0.4 50% 44% 4% 2%4010 0.3 0.3 0.4 0.0 0.2 0.0 0.2 0.2 0.4 4% 58% 38%4015 0.3 0.4 0.5 0.1 0.2 0.2 0.3 0.3 0.4 26% 62% 12%4020 0.3 0.3 0.5 0.1 ## 0.5 0.3 0.3 0.5 34% 44% 22%4025 0.3 0.4 0.5 0.1 ## ## 0.2 0.2 0.4 30% 54% 16%4030 0.3 0.4 0.5 0.1 1.3 0.9 0.3 0.2 0.4 40% 54% 4% 2%4035 0.3 0.3 0.6 0.1 3.2 1.4 0.4 0.3 0.5 42% 40% 16% 2%4040 0.3 0.3 0.5 0.1 0.1 0.7 0.3 0.2 0.5 42% 46% 10% 2%4045 0.4 0.4 0.6 0.1 0.9 0.4 0.4 0.3 0.5 26% 50% 22% 2%4050 0.3 0.3 0.5 0.1 0.8 0.7 0.3 0.2 0.4 44% 50% 6%4055 0.3 0.3 0.4 0.0 ## 0.0 0.2 0.2 0.4 60% 40%4060 0.3 0.3 0.5 0.1 0.5 0.6 0.3 0.2 0.4 44% 48% 6% 2%4065 0.3 0.3 0.5 0.1 ## 0.2 0.2 0.2 0.4 46% 44% 10%4070 0.3 0.3 0.5 0.1 0.7 0.6 0.3 0.2 0.4 36% 54% 8% 2%4075 0.4 0.3 0.7 0.1 3.3 1.2 0.4 0.3 0.5 22% 46% 30% 2%4080 0.4 0.3 0.7 0.1 0.9 1.2 0.5 0.3 0.6 20% 42% 22% 6% 8% 2%4085 0.4 0.4 0.7 0.1 3.3 1.3 0.5 0.3 0.5 14% 56% 22% 6% 2%4090 0.4 0.4 0.7 0.1 2.7 1.2 0.5 0.3 0.5 20% 44% 30% 4% 2%

Porous Asphalt

Dense Asphalt

8

Indication of Ravelling. Make Statistics within same Surface Type (1)

Histogram RRMSTypical Distributions

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60

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0

RMST Intervall (mm)

Perc

en

tag

e

Porous AsphaltExtensive Stone loss

Dense AsphaltMinor Ravelling

Dense AsphaltExtensive ravelling

9

RMS 10mväg 1102, sektion 1 (uu505b)

0.00

0.10

0.20

0.30

0.40

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0.90

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Distance

RR

MS

Right Wheel Average RMS

Middle Position Average RMS

50-percentile

90-percentile

Possible Ravelling

Moderate Ravelling

Severe Ravelling

Indication of Ravelling. Pre-test Road 1102

Ravelling - NetherlandsBased on experience from 30 000 km survey over 6 years on the secondary road network in Netherlands

Purpose: Establish a methodology that can identify surfaces to be renewed within 2 years due to raveling.

Set-up

• Information from road A348 over the years 2007, 2008, 2009, 2010 and 2011

• Measurement system: RST29, 32 kHz point lasers (3).

• Texture measured in the middle (1) and the right wheel position (2). In the years 2010 and 2011 the texture was also measured in the left wheel track.

11

Methodology – frame work

• The 95-percentile RMS texture value from year 1 (new asphalt) is reference.

• The change in texture is yearly monitored through survey.

• When the 95-percentile value has increased to “X” times compared to reference, the surface will be indicated as open.

• When the 95-percentile value has increased to “Y” times to the reference, the surface will be indicated as raveled and recommended for resurfacing.

12

Average RMS texture

13

Average value of RMS texture.

95-percentile RMS texture

Laser 1 in between wheel paths

Laser 2 in the right wheel path

The distribution is narrow which can be explained by the surface type with the dominating stone sizes of 5 mm.

Change in distribution over time

Texture in the middle of the lane (laser 1) seems to be more open than the texture in the right wheel path.

The change over time is visible.

Increase in RMS texture 2007-2011

15

Laser 1: + 37.1%Laser 2: + 35.8%

Figure: % of 5m sections with RMS texture over the 2007 year’s 95-percentile

Conclusions

• It seems possible to detect changes over time with RMS texture.

• It is possible to quantify this change and therefore possible to use it for indication of raveling.

• For detection of raveling the number of measurement point should be increased from 2-3 to 5 in order to cover also the edges of the lane.

• Driving pattern of the survey vehicle is essential (driver education).

 

 

16

Homogeneity as quality control

Examples

Poor texture/homogeneity Proper texture/homogeneity

Purpose with a control of homogeneity

The quality will rise by using demands on surface structure and homogeneity

Proper structure/texture• Better friction• Influence on fuel consumption, tire wear and noice

Proper homogeneity• Increase possibility for achieving the desired service life• Reduced risk for future stone loss and separations• Reduced risk for plastic deformations

Present control methods. Non-destructive

DOR (Density On Run)+ Good parameter (density)

+ Cover areas not lines

- Low speed (0.9 km/h)

- Less good repeatability on short sections

Radar (GPR)+ Parameter on variation in void content- Requires some cores samples

Thermal camera (FLIR)

Shows the asphalt temperature directly after paving

Sections with too low temperature are classified as risk sections

Texture

Point lasers in three lines

Makrotexture (wave lenght 0.5 – 50.0 mm)

Parameters: MPD (Mean Profile Depth), RMS

Poor quality - example

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3480 3490 3500 3510 3520 3530 3540 3550 3560

Distans (m)

MP

D (

mm

)

MPD V

MPD M

MPD H

Separation due to high binder content on the right hand side.

Left

Mid

Right

Objekt 2 2400-3600 meter

Mätdrag Höger

2

2.05

2.1

2.15

2.2

2.25

2.3

2.35

2.4

2400 2600 2800 3000 3200 3400 3600

Distans (m)

g/cm

3

-1.5

-1.3

-1.1

-0.9

-0.7

-0.5

-0.3

-0.1

mm

Densitet (g/cm3)

RRMS (mm)

Correlation RMS Texture/density

Model

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100

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Textur (mm)

(%)

Black

Normal distribution for the surface type

Blue

Dense surface, binder on the surface

Red

Open surface, risk for ravelling

• Collect data over 100 mm

• Calculate distribution for each 5 m

• Determine deviation from normal distribution

Conclusions - homogeneity

• Surface texture can be a proper indicator of open and dense suraces (quality)

• Acceptable correlation between DOR and laser survey

• Knowledge of expected values for different surface types is needed

Further work

• Determine ”master curve” for various asphalt types

• Define how deviations (grey area) shall be determined

• How large deviations can be accepted?

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0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Textur (mm)

(%)

Conclusions

• Point lasers can be used for indication of ravelling/stone loss and homogeneity (MPD under implementation in Sweden).

• The method should be based on macro texture and statistical distributions

• Changes over time are essential to track

• Reference data for new asphalt - nice to have “mastercurves”

• At least 5 lasers should be used

• Driving pattern of the survey vehicle is essential (driver education).

27

Thank you!

28