Factors affecting the reliability of data related to … Enea Sogno...Factors affecting the reliability of data related to pavement profiles and surface characteristics ENEA SOGNO

Factors affecting the reliability of data related to pavement profiles and surface characteristics

ENEA SOGNO and MICHELE [email protected]

[email protected]

Copenhagen, 2017.10.19

Pointing out some issues

The company

About longitudinal and transverse roughness

About macrotexture and skid rates

About surface distress (cracking, raveling, potholes)

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Summary

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WHAT TYPE

Collecting data...

BASED ON CONTACT

Physical interaction between the structure and the machine is necessary

BASED ON LASER EMISSIONS

The interaction between the structure and the machine is evaluated from the shape and the

amplitude of source-to-target signals

PAVEMENT

Friction, deflection basins

PAVEMENT/ROAD

Profiles, contour marking strips, deflection basins, geometry

HOW TO USE

Skid rate, elastic modulus, roughness, rut depth, macrotexture, surface indicators, reflective power, carriageway/infrastructure dimensions and slopes

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WHICH NEEDS

ROAD MANAGERS PUBLIC ADMINISTRATIONS

TECHNICAL SUPPORT

Usable information

ECONOMIC SOLUTIONS

Fit budget

WHICH EXPECTATIONS

Maintenance?

Safety?

To save money?

...in answer to

Data is the key, processing and post-processing make

the difference


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Laser sensors @64 KHzShould we get any answers from that?


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At least, one: the need for data!

We do not need instruments and technologies to assess whether potholes or cracks exist upon the pavement surface. Cams are sufficient for that…

Right side view 45°

Left side view 45° Front view

Spherical cameras

Panoramic

view up to

324°


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We need surveys to assess the level of distress of the pavement surface in a quantitative and qualitative way through the analysis of key performance indicators.

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Reliable raw data => Effective KPIs


The company

Sina S.p.A. is an Italian company which provides extended engineering services to infrastructure

managers worldwide. It belongs to the Gavio Group.

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The experience with laser technologies

Technology Services and other

Shipbuilding

Engineering

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Surveying for evaluation and for comparison purposes implies the necessity of fully controlling each factor which makes the results different (i.e. trajectory, surface distress, speed, weather, …).

Road profiling with…

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AASHTO requires at least 25mm long sampling for class 1 profilers!!


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Using the most accurate and repeatable technologies could help, but uncertainties will remain!

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Rep1 Rep2 Rep3 Rep4 Rep5 Rep6 Mean RMS CV

IRI_right 1,67 1,76 1,73 1,63 1,68 1,68 1,69 0,05 3%

IRI_left 1,08 1,03 1,06 1,00 1,00 1,03 1,03 0,03 3%

IRI_avg 1,37 1,40 1,40 1,32 1,34 1,36 1,36 0,03 2%

Selcom right versus left side => same dispersion, different mean values

NEW PAVEMENT NO CRACKS NOR RUTS

Something happens to profiles in the right wheel-path, is that due to pavement concerns or to the machine? The transverse position? All of

these factors?

Mostly controlling surveying conditions could be an improvement, but uncertainties will remain

once again!

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Completely scanning the road lane would finally lead to lowly-spaced longitudinal profiles that may help, and many times they do, but they’re not THE solution!

storage concerns

need for data quantity reduction

difficult evaluation of detailed results

1 1

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Avg per long profile

IRI_avg IRI_max St.dev. CV

Test site #1 1.52 2.90 0.36 23.44

Motorway

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IRI_avg IRI_max st.dev. CV

Test site #2 1.44 2.73 0.37 25.61

Motorway

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Test site #3 2.32 7.93 1.56 56.82

Roadway

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Test site #1 1.52 2.90 0.36 23.44

Test site #2 1.44 2.73 0.37 25.61

Test site #3 2.32 7.93 1.56 56.82

Transverseposition

IRI_avg_#1 IRI_avg_#2 IRI_avg_#3

-1.9 2.07 1.91 1.96

-1.8 1.72 1.66 1.92-1.7 1.63 1.63 1.84-1.6 1.56 1.62 1.77

-1.5 1.58 1.63 1.76

-1.4 1.63 1.62 1.78-1.3 1.69 1.59 1.79-1.2 1.74 1.55 1.79

-1.1 1.77 1.48 1.77

-1 1.77 1.44 1.77-0.9 1.74 1.40 1.71-0.8 1.70 1.37 1.70

-0.7 1.65 1.34 1.71

-0.6 1.58 1.34 1.70-0.5 1.54 1.36 1.75-0.4 1.53 1.38 1.79

-0.3 1.53 1.41 1.81-0.2 1.54 1.43 1.81-0.1 1.55 1.44 1.820.1 1.29 1.26 1.61

0.2 1.25 1.24 1.550.3 1.26 1.26 1.550.4 1.25 1.26 1.610.5 1.24 1.26 1.65

0.6 1.23 1.25 1.680.7 1.24 1.27 1.78

0.8 1.30 1.31 1.950.9 1.34 1.34 2.10

1 1.36 1.36 2.181.1 1.37 1.38 2.18

1.2 1.37 1.38 2.09

1.3 1.38 1.39 2.04

1.4 1.38 1.41 1.961.5 1.38 1.43 2.00

1.6 1.44 1.50 2.43

1.7 1.49 1.54 4.25

1.8 1.59 1.56 7.601.9 1.92 1.66 12.15

Lower and more homogeneous IRI

values from sides to the center of the road lane

Different quality in test sites #1 and #2 compared to #3

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Localized repairs


We got lots of information on roughness and were able to make comparisons…but still have to decide how to use data!!

What is the goal?

Analysis at the network level

Design

PMS

IRI_avg IRI_max St.dev. CV

Test site #1, 1.9 - 160mt 1.92 5.60 0.64 33.21

Test site #1, -1.9 - 160mt 2.07 4.41 0.60 29.01

Test site #1, 1.9 - 2mt 1.92 15.70 1.47 76.54

Test site #1, -1.9 - 2mt 2.07 16.93 1.51 73.10

2mt vs 160mt

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Remembering that…

Processing is the powerful instrument that

can really help to reduce uncertainties and

focus on the goal of the survey!

Raw data is 1 profile elevation each some

millimeters, processed data is 1 reference

value each some meters.

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Only if the exact needs are well known, the available information can be properly read and

managed. For instance, we won’t take care of the spacing, if we’re looking for subgrade and/or

viscous AC rutting, but we will wisely consider the trajectory of the vehicle along the lane.

Then…

As well, we won’t take care of the transverse

position of long profiles, if we’re looking for

joints!

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About 26 mt from PSD analysis

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Macrotexture and skid rates

Modern technologies allow data to be acquired each some millimeters again, even in the case of contact-based determinations such as the skid rate. But sometimes a lower and lower resolution may be convenient for technicians…

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Raw data each 10 cm, moving averages at 600mt

Evaluating homogeneous sections at the network analysis level can produce effective results both from contact-based and from profile-based determinations…

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But, looking for more detailed information will bring to some differences due to the temperature and the speed at which SR and MPD were measured, the geometry of the site.

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Dealing with a patch and with a road network is quite different!

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…and surveying conditions count

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Surface distress (cracking, raveling, potholes)

Improved road surveying allows operators to analyse even cracks and punctual distress which exist on the pavement surface, providing a large multitude of data (widths, lengths, depths, areas).

Is it better to know how many cracks do we see in the picture above (and their characteristics) or the reason why

we can miss some of them?

Proficient synthesis, you’re welcome!

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A good answer would be both!

Without knowing the quantity of cracks we won’t be able to make analyses…

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But, without knowing factors which influence the results we won’t be able to improve the reliability

of our analyses!

Is it possible to miss that due to adverse weather conditions? Powder? Wrong resolution? Something else?

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Looking for answers…from

tests

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Dry

Wet

Intermediate 1

Half-wet

Intermediate 2

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Dry

Wet

Intermediate 1

Half-wet

Intermediate 2

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Copenhagen, 19th October 2017

Thank you for your attention



ENEA SOGNO and MICHELE [email protected]

[email protected]

Copenhagen, 2017.10.19

Documents

Factors affecting the reliability of data related to … Enea Sogno...Factors affecting the reliability of data related to pavement profiles and surface characteristics ENEA SOGNO