In-service Pavements Research Articles

Modelling asphalt pavement analyzer rut depth using different statistical techniques

Different computer-operated temperature-controlled equipments are used to predict asphalt mixture performance in laboratory at approximately similar conditions to actual in-service pavements. Asphalt pavement analyzer (APA) is one such multi-functional sophisticated equipment. Wearing course layers are primarily attributable to be deteriorated by rutting distress in flexible asphalt pavements. Therefore, 30 representative wearing course mixtures commonly used in road pavements were tested for rutting distress using APA. Mixtures were evaluated based on their rutting performance and found that consistent ranking has been observed at temperature conditions of 40°C and 50°C. It was observed that APA rut depth could be effectively modelled using statistical techniques of multiple non-linear regression and artificial neural network. Novel aggregate material indices designated as ‘aggregate source index’ and ‘aggregate gradation index’ were developed in this study. Based on past literature; temperature, aggregate source index (ASI), aggregate gradation index, bitumen penetration values, and number of APA loading cycles/strokes were included as independent variables in the model developed for selected asphalt mixtures. It has been concluded from the values of non-linear regression parameters that temperature has the highest significance for rut depth prediction, followed by the bitumen penetration value, ASI, aggregate gradation index and number of loading cycles. Statistical parameters i.e. coefficient of determination, root mean squared error, values account for, and mean absolute percentage error showed that the artificial neural network technique better predicts the APA rut depth as compared to multiple non-linear regression techniques.

Development of a Structural Capacity Prediction Model Based on Traffic Speed Deflectometer Measurements

The importance of incorporating pavement structural conditions in the selection of maintenance and rehabilitation strategies along with functional indices has been recognized by state agencies. To measure in-service pavement structural capacity, surface deflection under a defined load has been typically used. The traffic speed deflectometer (TSD) has emerged as a continuous deflection-measuring device as it operates at traffic speed and reduces lane closure and user delays. The present study developed a nonlinear regression model to predict pavement structural number (SN) based on surface deflections measured by the TSD along with the total pavement layer thickness and traffic volume. The proposed model was successfully developed and validated with SN calculated based on TSD and falling weight deflectometer deflection data obtained from two testing programs in Louisiana and Idaho. The model was further validated with respect to its prediction of in-service structural capacity loss and deficiency. Based on statistical measures and the model’s ability in identifying structurally deficient sections, results showed satisfactory accuracy of the model and supports its use for network-level decision-making processes in the pavement management system.

Pavement performance compared with asphalt properties for five contracts in Ontario

This paper analyzes pavement performance of five Ontario Ministry of Transportation contracts paved in 2011 in relation to the properties of asphaltic materials used during construction. Pavement cracking data collected in 2016 was compared with characteristics of asphalt cement supplied for paving and recovered from pavement cores at year five. A major finding was that the Extended Bending Beam Rheometer test; part of enhanced testing currently carried out on asphalt cement in Ontario, was more reliable at predicting pavement performance than the standard Superpave™ Bending Beam Rheometer test for both asphalt supplied to the contract and recovered from in-service pavements.

Influence of temperature on the cracking behavior of asphalt base courses with structural weaknesses

Abstract Asphalt pavement is known to be deteriorated by the repetitive traffic loading, climatic condition, aging of asphalt mixture etc. after opening to traffic. Crack plays a critical role in pavement deterioration. Several studies have been conducted to obtain a better understanding with respect to climate related pavement fracture behavior. However, the limitation of the previous researches was that most of them were conducted by laboratory experiment or numerical simulation. The main objective of this study is to determine the relationship between the continuously changed temperature and the relative crack opening in asphalt base course by analyzing the data collected from an in-service asphalt pavement. To achieve this objective, four artificial transverse cracks were first induced on the asphalt subbase of a test track, and then their temperatures and crack opening were recorded by monitoring systems. Diurnal and annual trends of temperature and relative crack opening as well as their relationship were investigated and discussed. In this study, a test track with defined asphalt layers was constructed, which was specially equipped with sensors that continuously monitored the temperatures and opening widths of structural cracks in the test track. On the basis of the findings obtained, it is possible for the first time to make direct statements about the deformation conditions occurring in an asphalt base layer as a result of temperature.

Development of dynamic modulus master curves of in-service asphalt layers using MEPDG models

The new mechanistic-empirical pavement design guide (MEPDG) uses a combination of field and laboratory tests for structural analysis of in-service pavements. In this guide, asphalt dynamic modulus (|E*|) is one of the most important parameters used in flexible pavement design and rehabilitation approaches. This paper evaluates the validity of dynamic modulus models used in MEPDG for in-service asphalt pavements. For this purpose, nine asphalt pavement sites with various structural, ages and conditions were selected in Khuzestan and Kerman provinces in southern regions in Iran. At each site, falling weight deflectometer data, resilient modulus (determined from the cored samples) and surface condition data were collected. These three sets of data are necessary to compute damages at input levels of 1, 2 and 3 in MEPDG, respectively. Core samples were extracted, and mix volumetric properties as well as their binder characteristics were determined. Viscosity-based NCHRP 1-37A (Witczak) and G*-based NCHRP 1-40D (Modified Witczak) dynamic modulus predictive models were incorporated into these three input levels and six combinations of in situ |E*| master curves were developed. Analysis of the results indicates a weak correlation between field backcalculated moduli and those measured in laboratory. Hence, application of both field and laboratory moduli is not necessarily a good approach to determine damages, and the MEPDG proposed method would better be modified. Validation of MEPDG models showed that the NCHRP 1-37A model predicts dynamic modulus master curves with lower errors rather than the NCHRP 1-40D model. In addition, using the NCHRP 1-37A model at input level 1 would be a better approach among the others to evaluate both new and rehabilitated asphalt layers. Results will also be useful for local agencies in implementation of American Association of State Highway and Transportation Officials (AASHTO)mechanistic-empirical pavement design procedure in various climatic conditions.

Crack identification for rigid pavements using unmanned aerial vehicles

Pavement condition assessment is an essential piece of modern pavement management systems as rehabilitation strategies are planned based upon its outcomes. For proper evaluation of existing pavements, they must be continuously and effectively monitored using practical means. Conventionally, truck-based pavement monitoring systems have been in-use in assessing the remaining life of in-service pavements. Although such systems produce accurate results, their use can be expensive and data processing can be time consuming, which make them infeasible considering the demand for quick pavement evaluation. To overcome such problems, Unmanned Aerial Vehicles (UAVs) can be used as an alternative as they are relatively cheaper and easier-to-use. In this study, we propose a UAV based pavement crack identification system for monitoring rigid pavements’ existing conditions. The system consists of recently introduced image processing algorithms used together with conventional machine learning techniques, both of which are used to perform detection of cracks on rigid pavements’ surface and their classification. Through image processing, the distinct features of labelled crack bodies are first obtained from the UAV based images and then used for training of a Support Vector Machine (SVM) model. The performance of the developed SVM model was assessed with a field study performed along a rigid pavement exposed to low traffic and serious temperature changes. Available cracks were classified using the UAV based system and obtained results indicate it ensures a good alternative solution for pavement monitoring applications.

Measurement and evaluation on deterioration of asphalt pavements by geophones

To determine a feasible strategy for maintenance and rehabilitation of in-service asphalt pavements, the precise in-situ determination of pavement deterioration is of significant importance. Conventional methods such as fatigue tests on core specimens in the laboratory or stationary deflection measurements in-situ exhibit their own disadvantages. This study proposes an innovative system to measure and evaluate the deterioration of asphalt pavements under moving loads by means of geophones, a mobile load simulator (MLS) and a back-calculation tool. A test track was evaluated with this method at three different service states. For each state, the vibrations of the test track induced by a passing truck were measured by an array of geophones. The vibrations were transferred to a surface deflection in the analysis and then used to compute the material parameters of the test track with the back-calculation tool. The results show that the deflections derived from an individual geophone are in high agreement with each other and thus the repeatability indicates the measurement is mechanically robust. The computational variation of material parameters and the corresponding mechanical responses are consistent with the increase of loading cycles applied by the MLS. It indicates that the proposed system is able to provide a tool for an accurate and efficient measurement of the surface deflection and evaluation of the deterioration of asphalt pavements under moving loads.

Application of FWD data in developing dynamic modulus master curves of in-service asphalt layers

This paper presents a simple method to determine dynamic modulus master curve of asphalt layers by con­ducting Falling Weight Deflectometer (FWD) for use in mechanistic-empirical rehabilitation. Ten new and rehabilitated in-service asphalt pavements with different physical characteristics were selected in Khuzestan and Kerman provinces in south of Iran. FWD testing was conducted on these pavements and core samples were taken. Witczak prediction model was used to predict dynamic modulus master curves from mix volumetric properties as well as the bitumen viscosity characteristics. Adjustments were made using FWD results and the in-situ dynamic modulus master curves were ob­tained. In order to evaluate the efficiency of the proposed method, the results were compared with those obtained by us­ing the developed procedure of the state-of-the-practice, Mechanistic-Empirical Pavement Design Guide (MEPDG). Re­sults showed the proposed method has several advantages over MEPDG including: (1) simplicity in directly constructing in-situ dynamic modulus master curve; (2) developing in-situ master curve in the same trend with the main predicted one; (3) covering the large differences between in-situ and predicted master curve in high frequencies; and (4) the value obtained for the in-situ dynamic modulus is the same as the value measured by the FWD for a corresponding frequency.

Statistical evaluation of factors affecting the laboratory rutting susceptibility of asphalt mixtures

Rutting or plastic deformation is one of most frequently observed distress types in the wheel paths of flexible road pavements. This distress may cause the pavement structure to be attributable to early failure by expediting the deterioration due to load and environmental detrimental agents. Therefore, it is ideal to simulate the rutting performance of different asphalt mixtures in laboratory-controlled conditions before exposing them to aggressive field conditions. Different rutting simulation computer-controlled equipments are available to predict the mixture performance in laboratory at nearly similar conditions to actual in-service pavements. Cooper wheel tracking equipment is one such precise equipment. Mostly, the wearing course is likely to be damaged by this distress type in flexible asphalt pavements. Therefore, in this research study, thirty representative wearing course mixtures commonly used in road pavements were tested for rutting distress using Cooper wheel tracker. Three aggregate sources, three binders from two sources, five mixture gradations and two temperature conditions were included in the testing scheme. Mixtures were evaluated based on the terminal value of rut depth. Consistent ranking of mixtures has been observed for variable combinations of aggregates, binders, temperatures and gradations. Flakiness index (FI) of aggregates, binder penetration values, per cent coarse material retained on 4.75 mm sieve and temperature values are considered as independent variables based on past researches. The significance of these independent variables on the dependent variable of rut depth has been analysed by analytical tools of general full factorial design analysis. It has been concluded that temperature has highest significance for the rut depth prediction, followed by FI of aggregates, bitumen penetration value and percentage of coarse fraction.

Development of a mid-depth profile monitoring system for accelerated pavement testing

This study presents the development of a new mid-depth profile monitoring system (MPMS) to investigate the rutting behavior of full-depth asphalt pavements. The scope incorporates an experimental study that uses a full-scale accelerated pavement testing (APT) facility. Two different thicknesses of full-depth asphalt pavements were constructed in the Indiana accelerated pavement-testing facility. A laser profile scanning system was designed to reconstruct the transverse profiles at each pavement layer interface throughout the process of accelerated pavement deterioration. The contribution of each pavement structural layer to the total rut depth and the evolution of layer deformation were determined. The developed system provides reasonable results with a high accuracy level based on the findings. First, the measured rutting curves at each layer interface agree well with the theoretical characteristics of rutting evolution and clearly exhibit the primary and secondary stages of rutting development. Furthermore, all the measured rutting curves have good coefficients of correlation. Second, the locations of critical rutting and the total rut depths were found to be independent of pavement thickness when the pavement is sufficiently thick, which is a finding that agrees with previous study results, the study reported the thickness threshold value to be 5.12in. (13.00cm) for their case. The results demonstrate MPMS developed in this study provides an excellent method to evaluate the rutting performance of asphalt pavements in the APT. In addition, MPMS has a potential application to in-service pavements.

Evaluation of Pavement Layer Moduli Using Instrumentation Measurements

Instrumentation embedded in pavements is increasingly being used to measure the critical responses and monitor performance of specially-constructed experimental pavement sections or in-service pavements under controlled wheel loading or live traffic. On the other hand, nondestructive tests (NDT), such as falling weight deflectometer (FWD) testing, are routinely performed to evaluate pavement layer structural properties based on deflections measured on the surface of the pavements. In cases where measurements from the pavement surface only are not sufficient to infer pavement layer modulus values, e.g. rolling wheel deflectometer (RWD) tests typically with only one deflection measurement or complex geometries, a procedure that combines measurements from the embedded instruments and surface deflections would provide an alternative to the traditional backcalculation of pavement layer moduli. This study presents an inverse analysis procedure integrating finite element (FE) models and a population-based optimization technique, Covariance Matrix Adaptation Evolution Strategy (CMA-ES), to determine the pavement layer structural properties. Tests using a lightweight deflectometer (LWD) were conducted on instrumented three-layer scaled flexible pavement test sections. The time histories of the LWD load, surface deflection underneath the LWD load, subgrade deflection and vertical stress were recorded and used in the inverse analysis. While the common practice in backcalculating pavement layer properties still assumes a static FWD load and makes use of only peak values of the load and deflections, dynamic analysis was conducted to simulate the impulse LWD load. Results of the inverse analysis show that consistent pavement layer properties can be obtained based on the LWD surface deflection data and measurements of the embedded instrumentation.

Dynamic Soil Models for Backcalculation of Material Properties from Falling Weight Deflectometer Deflection Data

Falling Weight Deflectometer (FWD) test is one of the most widely used methods for in-situ nondestructive evaluation of pavement/soil properties and examination of the structural condition of in-service pavements. A dynamic half-space model is employed in the present work for backcalculation of engineering soil properties from the FWD data. The advantages, limitations and the reliability of the backcalculation elastic moduli evaluated from dynamic soil model are discussed in this paper. Selected numerical results are presented to portray the influence of governing parameters, for example, the presence of shallow stiff layer and the mass density of soil material on dynamic backcalculation of the soil elastic modulus. The investigation presented in this study provides a better understanding of dynamic backcalculation processes which is essential for the development of dynamic backcalculation program and its applications.

Backcalculation of Flexible Pavement Layer Moduli from Traffic Speed Deflectometer Data

In the past few years, state transportation departments in the United States have been investigating the potential use of the traffic speed deflectometer (TSD) in routine network-level pavement structural evaluation, including efforts to compute parameters typically obtained with the falling weight deflectometer (FWD). However, differences in loading configuration (single plate versus dual tires) and mechanism (impact versus moving load) between the FWD and the TSD necessitate modification of conventional analysis methodologies for use with TSD data. The TSD is a trailer truck that uses Doppler lasers to measure the pavement deflection velocities at normal traffic speed. Deflection velocities are then converted to surface deflections with a computational algorithm. This study proposes two approaches to backcalculating layer moduli from the TSD data. The first method uses 3D-Move software and deflection velocities measured directly by the TSD. The 3D-Move software can closely simulate TSD loading by considering moving load, nonuniform contact pressure of the dual tires, and viscoelastic material properties of asphalt layers. The second method uses TSD-computed surface deflections in a linear elastic analysis backcalculation program modified to incorporate a dual-tire configuration. The two methods were evaluated with field data from the MnROAD test facility and two in-service pavement sections in Pennsylvania and Idaho. The results show that the second method can be reliably used in network-level applications until the first method becomes computationally practical. The limitations of use of the TSD deflection measurement in the conventional FWD backcalculation program was also demonstrated.

Analysis of Road Cover Roughness on “Control” Road Section with Crumb Tire Rubber

Results of acoustic level measurements are presented in the paper. Measurements were carried out on “control” road sections in Mala Ida village (Kosice region, Slovakia) and Haniska village (Presov region, Slovakia). Descriptions of the sections, conditions of laying and technology of the mixture are given in the paper too. During the period between autumn 2014 and spring 2015 noise levels and pavement surface characteristics were investigated on experimental road sections consisting of asphalt concrete pavement with addition of crumb rubber from waste tires. The surface properties of the in-service pavement were measured to establish the characteristics of a “control” road constructed with crumb tire rubber. Correlation of the results from the measured surface characteristics in pavement with crumb tire rubber indicates that the parameters of roughness and texture could have a relevant role in global tire/pavement sound emissions.

Nondestructive In Situ Characterization of Elastic Moduli of Full-Depth Reclamation Base Mixtures

State highway agencies are searching for more cost-effective methods for rehabilitating roads. One sustainable solution is full-depth reclamation (FDR), which is a pavement rehabilitation technique that involves pulverizing and reusing materials from existing distressed pavements in place. However, there is little information on the long-term properties of these recycled materials. An important property, the elastic modulus, indicates the structural capacity of pavement materials and is highly recommended for design purposes by the Mechanistic–Empirical Pavement Design Guide. The elastic modulus directly affects selection of the overall pavement thickness; therefore, an accurate estimation of the modulus is key to a cost-effective pavement design. This research investigated the elastic modulus trends of three in-service pavements rehabilitated with the FDR technique during the 2008 Virginia Department of Transportation construction season. Foamed asphalt (2.7% with 1% cement), asphalt emulsion (3.5%), and portland cement (5%) were used as stabilizing agents for the FDR layers. The results of the moduli measured for the recycled base materials varied significantly over time. These changes were attributed to curing after construction, seasonal effects, and subgrade moisture. The structural capacity of the pavements improved irrespective of the stabilizing agent used.

Pavement skid resistance consideration in rain-related wet-weather speed limits determination

Posted maximum speed limits used by highway agencies worldwide are typically applicable to dry-weather driving conditions. During wet weather, these speed limits may exceed the maximum speed for safe traffic operations. More and more highway agencies are employing variable speed limits as a means to improve wet-weather driving safety. For rain-related wet-weather conditions, the variable speed limit systems in use today commonly set speed limits based on either consideration of stopping sight distance, or past experience and engineering judgement. A common shortcoming of the existing systems is that the actual pavement skid resistance characteristics are not considered in setting the speed limits. This paper proposes an improved procedure to derive mechanistically the speed limits from the required safe stopping distance as well as the minimum skid resistance requirement for safe driving, based on the actual skid resistance properties of the pavement considered. The proposed procedure makes use of a finite-element skid resistance computer simulation model to determine both the available skid resistance values and vehicle braking distances at different vehicle speeds of the in-service pavement under specified rain-related wet-weather conditions. The procedure is theoretically sound, and is consistent with the concept of pavement network friction management system. In the analysis, the rain-related wet-weather condition is represented by rainfall intensity, and the road section is characterised by its gradient and cross slope, as well as the skid resistance properties of the pavement. A numerical example is presented to illustrate the working of the proposed procedure.

Local calibration of flexible pavement performance models in Michigan

The performance prediction models in the Pavement-ME are nationally calibrated using in-service pavement material properties, pavement structure, climate and truck loading conditions, and performan...

Effects of environmental aging and ultra violet radiation on asphalt mixture dynamic modulus, permanent deformation and fatigue life

The aging process causes changes in the properties of asphalt mixtures, such as weak adhesion of mineral aggregates to the asphalt and increase of asphalt’s rigidity and viscosity, which in turn directly affect the durability of asphalt pavement. This study aims to evaluate the behavior of asphalt mixtures at different aging stages through the comparison of samples treated under ultraviolet radiation and samples extracted from the field. Laboratory mixtures were prepared from one aggregate source and one asphalt cement. Four types of asphalt mixtures were analyzed: un-aged, laboratory-aged - UV and Pressure Aging Vessel, and field-aged. For laboratory accelerated aging a UV radiation chamber was designed and samples were exposed to 100, 200 and 500-hour treatment periods. Samples aged in the field were obtained from in-service pavements of 1.5 to 11 years after construction. Mechanical behavior was evaluated through dynamic modulus, rutting and trapezoidal fatigue. Results showed that when aging time increases all samples undergone significant increases in dynamic moduli up to two times of unaged mixtures. Permanent deformation exhibited better resistance in aged mixtures than the unaged ones. On the other side, aging affected negatively fatigue life due to significant changes in the slope of fatigue law. Accelerated aging by UV chamber simulated up to 1.5 years in fatigue life and 11 years in permanent deformation performance.

Calibration of HDM-4 models for Indian conditions of flexible pavement having modified bitumen in wearing course

India is developing her national highway network through widening and rehabilitation of existing highways along with the construction of expressways in different phases, since 1999. Unprecedented growth of road traffic, high variations in pavement temperature and need of long lasting pavements have increased the use of modified bitumen specifically in wearing courses of many flexible pavement road sections of national highway network in entire country. Crumb rubber-modified bitumen (CRMB) and polymer-modified bitumen (PMB) of different grades are mostly used modified binders under different climatic and environmental conditions. During the design life, bituminous road sections show different rates of initiation and propagation of distresses under varying traffic and climatic conditions. In this study, an effort has been made to calibrate the internationally recognised Highway Development & Management (HDM-4) road deterioration models for the selected flexible pavement sections over time with traffic. The different road distresses are modelled using HDM-4 tool for the newly constructed flexible pavement sections of Indian national highway network having modified binder in bituminous concrete (BC) mixes which are located in different regions of the country. Pavement condition data of 23 in-service flexible pavement sections were collected for three consecutive years starting from 2011 to end of the year 2013. Data collected from the study were analysed for calibration and validation of HDM-4 distress models for similar climatic conditions, pavement compositions and traffic loading characteristics. The results of this study are useful for developing pavement maintenance management strategies for Indian national highway network with similar climatic conditions, pavement compositions and traffic characteristics.

Prediction of In-Service Pavement Structural Capacity Based on Traffic-Speed Deflection Measurements

AbstractNonstructural factors, such as surface distresses and ride quality, have been commonly used as the main indicators of in-service pavement conditions. In the last decade, the concept of implementing a structural condition index in pavement management system (PMS) to complement functional condition indices has become an important goal for many highway agencies. The rolling wheel deflectometer (RWD) provides the ability to measure pavement deflection while operating at the posted speed limits causing no user delays. The objective of this study was to develop a model to predict pavement structural capacity at a length interval of 0.16 km (0.1 mi) based on RWD measurements and to assess its effectiveness in identifying structurally deficient pavement sections. Rolling wheel deflectometer data collected from 153 road sections (more than 1,600 km) in District 05 of Louisiana were used in this study. The predicted structural number (SNRWD0.16) showed an acceptable accuracy with a root-mean square error (R...