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NTRODUCTION
One of the most critical task for the world transportation community is adequately maintaining existing pavements observing safety standards. Road and air traffic is increasing and it requires new way to optimize investments to provide maintenance and rehabilitation to all the pavement infrastructures. Many road administrations use the bigger amount of their resources on pavement repairs and maintenance, while only a smaller part on new construction. The world holds approximately 24 million km of paved roads, affected every year by a growing traffic. If we add to this amount all the pavement structures from airfields it’s easy to understand how the maintenance of the existing pavement heritage is becoming more and more important.
A good knowledge about pavement condition is essential for optimum planning of road maintenance and rehabilitation.
The most important performance parameter of a pavement structure is its bearing capacity, which is an indicator of the remaining structural service life. Structural data of pavement layers are in most of the world collected using the Falling Weight Deflectometer (FWD) which enables prediction of the remaining life of pavement structure. This device is non-destructive and very accurate, but also slow and stationary. To reduce safety hazards it requires traffic interruption due to risk of collision with the surrounding vehicles. This makes the use of the FWD test on major roads with high traffic intensity inappropriate, excluding a large percentage of existing pavement from structural testing. Therefore the FWD is typically used for project level testing only and not for road network analysis.
To solve the problem of using stationary test methods on roads with high traffic intensity, starting from the ’90 road administration tried to develop a new generation of testing device capable of performing measurements of the pavement bearing capacity at normal traffic speed. The target was to develop a non-destructive, high-efficient, structural pavement testing method which will facilitate pavement maintenance and rehabilitation strategies on a network level, providing useful information for a proactive approach.
The result of these projects was a Rolling Wheel Deflectometer (RWD), which will provide a simple screening method that enables road and airport agencies to identify road sections with reduced bearing capacity. This device is supposed to be used in combination with the FWD such that the RWD monitors the entire road network and points out the few sections
with poor bearing capacity which need to be tested with a more detailed investigation using the FWD to identify the reason of the problem.
The purpose of this new device is to improve the understanding of pavement conditions over a network level, to reduce costs through an optimization and a better allocation of pavement maintenance funds.
A predictive approach to maintain pavements before significant deterioration of bearing capacity will save a lot of money. A damaged road deteriorates much faster because the water may penetrate through cracks, damaging the layers under the surface and lowering the bearing capacity. The reconstruction of such deterioration will cost 4 to 5 times more than a proactive approach to maintenance and rehabilitation.
Graph 1.1 – Evolution of pavement conditions over time.
Maintenance and rehabilitation of a road network require knowledge about its immediate condition as well as its future condition. Knowledge about the actual condition is used to make decisions about repair works, while knowledge about the expected future condition is used for planning purposes. Traditionally two types of condition tests are carried out on pavements, measuring surface features like roughness, rutting, or cracks detecting, and collecting structural data and bearing capacity. While surface features are detected by the users, determining comfort and safety for users and vehicles, the bearing capacity is mainly of interest for the road administrations.
In an ideal situation with enough funds for pavement maintenance, information about the future bearing capacity provides an optimum background for planning budgets needed for pavement maintenance. In a real situation with few funds available for pavement maintenance, knowledge about the immediate and future pavement condition is necessary to
avoid unpleasant surprises with several high deteriorated roads, which requires additional money to be fixed. With the heavy increase of the traffic which has taken place in Europe since 1990, most of the roads will reach the predicted traffic volumes much earlier than it was expected. This means that the design of these roads will be inappropriate and the predicted lifetime of the pavement will be shorter. The best timing decision to provide maintenance repairs to a pavement can only be made after a measurement of both structural and functional data. These data collection should be made regularly to understand the progress of road deterioration.
The collected pavement condition data can be used in a Pavement Management System (PMS). A pavement management system provides different ways to perform pavement maintenance. They are based on prediction of pavement deterioration due to traffic and environment. After a prediction they offers different solutions for maintenance and repairs to the pavement basing on the type of the pavement, the future traffic and pavement condition parameters. The answers which a PMS software provides are where, when, and how is necessary to perform maintenance and rehabilitation repairs. They provide different solutions in order to meet the needs of different road managers with different money availability. Every solution consists in a priority order for each road section with the maintenance repairs which the pavement needs, based on a benefit-costs analysis. They include also information about the amount of money for each works and the expected frequency of the repairs.
PMS requires both structural and functional data, but often many road administrations do not collect structural data on a network level. Therefore their decisions about maintenance and rehabilitation are based on an incomplete data set, wasting a lot of money in wrong or useless repair works. The develop of a RWD will enable road administrations to do structural data analysis on a network level, creating an overview of the bearing capacity of the whole network and optimizing its maintenance costs.
Dynatest started developing a RWD since the beginning of 1990. The first result was a functional prototype capable to test at a top speed of 30 km/h only on airfield pavement, due to his huge length. After these promising results they decided to keep developing this new technology. In 2011 Dynatest started a new project together with DTU, the Technical University of Denmark. Dynatest was working on a new prototype, trying to improve the features of the old one, to develop a new screening device to collect structural data over a network level, while DTU was developing methods for pavement response modelling and data interpretation.
Dynatest acquired a patent for the new “image correlation” process to derive deflection data matching the same spot on the pavement. This process allows a higher resolution of the data collected, using a new algorithm inspired by the one used previously.
This collaboration ended with a new prototype, radically different from the first one. This prototype has been used for several tests, helping Dynatest to develop a new way to collect, analyze and report results coming from this innovative technology. Many tests have been made to compare the result of this new RWD with the most worldwide used and widely accepted Falling Weight Deflectometer. The target was to see if the output from the Dynatest RWD can be used as a screening device to provide useful information for a network analysis, so it his output was matching with the one from the FWD, considered as a reference. All these tests and these analyses provided a big database to help Dynatest developing and improving new calibration trials, pavement structure models and data processing useful for the real RWD trailer. The design of this new vehicle was defined in May 2017, and it was delivered at the end of November 2017.
Starting from this new vehicle Dynatest stopped talking about rolling weight deflectometer and introduced a new concept of continuous road testing at normal driving speed. They started talking about a new platform called Rapid Pavement Tester® (RPT®) or mostly used RAPTOR®, used as a screening device to collect both structural and functional data. The vehicle consists of a specially designed semi-trailer and a standard truck. The semi-trailer will carry the RWD technology developed at Dynatest, as well as other systems such as Laser Cracks Management System. The first will provide structural data while the second integrated system performs a functional analysis of the pavement. The entire vehicle has the size of a regular city bus which gives the possibility of utilizing the equipment in a wider range of roads, thus not limited to major network level roads. The Dynatest RAPTOR has been assembled in the period between the end of 2017 and the beginning of 2018, to help Dynatest providing high speed structural measurements since the first months of 2018.
This study starts with a description of all the possible devices which can be used to collect both functional and structural data of a pavement. Basing on the main theme of this study, this initial part about the different ways and devices to test a pavement is centred more on continuous and structural devices, with an accurate description of the Falling Weight Deflectometer that is still considered as the reference device for structural data.
The main part of this work is focused on the new Dynatest RAPTOR, which represents the latest technological development in terms of Rolling Weight Deflectometers. The first idea
of a Rolling Weight Deflectometer dates back to the 1990, so this study reports also the history of the development of these new devices, with all the prototypes and the attempt which have been made until nowadays. It contains an accurate description and a comparison between the Dynatest’s RAPTOR and the other two Rolling Weight Deflectometer available on the market today, the ARA RWD and the Greenwood TSD, showing features, pros and cons of all the devices. A detailed description of technical components and tools for data collection complete the exposition about the RAPTOR and its prototype.
Furthermore it illustrates all the calibration trial and the shadow tests performed with the RAPTOR prototype against the FWD, before the arrival of the new RAPTOR trailer. This part has a central role and it takes up a lot of space of this study. All the results, the procedure defined for the data processing and the models developed with the RAPTOR prototype will be used also with the new RAPTOR trailer. The aim of these shadow tests performed with the FWD against the RAPTOR prototype is to validate the output coming from the new device, providing statistical indicators about the repeatability of its measurements and about the comparability of its data with the reference provided by the FWD. Many extract from the results of all the comparison performed are shown and presented, including graphs and tables. The comparison with the FWD ends with a detailed overview of the whole procedure defined to process the data.
The final part contains the conclusions obtained from the correlation trial, and the next targets planned for the RAPTOR. It also includes all the future aims and a description about where the RAPTOR will be used in the pavement engineering world.
