Asphalt Pavement Density Research Articles

An Artificial Neural Network-Based Approach to Improve Non-Destructive Asphalt Pavement Density Measurement with an Electrical Density Gauge

Asphalt pavement density can be measured using either a destructive or a non-destructive method. The destructive method offers high measurement accuracy but causes damage to the pavement and is inefficient. In contrast, the non-destructive method is highly efficient without damaging the pavement, but its accuracy is not as good as that of the destructive method. Among the devices for non-destructive measurement, the nuclear density gauge (NDG) is the most accurate, but radiation in the device is a serious hazard. The electrical density gauge (EDG), while safer and more convenient to use, is affected by the factors other than density, such as temperature and moisture of the environment. To enhance its accuracy by minimizing or eliminating those non-density factors, an original approach based on artificial neural networks (ANNs) is proposed. Density readings, temperature, and moisture obtained by the EDG are the inputs, and the corresponding densities obtained by the NDG are the outputs to train the ANN models through Levenberg-Marquardt, Bayesian regularization, and Scaled Conjugate Gradient algorithms. Results indicate that the ANN models trained greatly improve the measurement accuracy of the electrical density gauge.

Non-destructive prediction techniques for asphalt mixture based on back propagation neural networks

ABSTRACT The density of the asphalt mixture surface is an important indicator to evaluate the quality of construction and is of great importance to ensure the quality of construction and maintain the long-term serviceability of the pavement. The 3D ground-penetrating radar (3D GPR) and density prediction model can achieve rapid and continuous prediction of the density of asphalt pavement. In this study, a back propagation neural network (BPNN) density prediction model was established and combined with 3D GPR to conduct field experiments on a new asphalt concrete mid-surface layer to compare the density values obtained by the coring method in order to verify the model performance. The results show that the BPNN prediction model established in this study has good application to the overall density diagnosis of the road in the field. The average prediction error of the BPNN density prediction model is 0.184%, which is highly reproducible in practical applications.

Evaluation of Performance of Void-Reducing Asphalt Membrane and Tack Coat on Asphalt Mixtures’ Longitudinal Joints

The longitudinal joint is one of the most crucial parts of asphalt pavement construction becuase several types of distress of the pavement can occur if the target density does not meet at the joint. A low density of asphalt pavement causes the pavement at the joint to be more exposed to water penetration, accelerating the rate of deterioration. To address this issue, asphalt agencies use various construction techniques and innovative materials to improve the joint’s performance. Void-reducing asphalt membrane (VRAM) is an innovative adhesive liquid that consists of an asphalt binder, an elastomeric polymer, and a wax modifier. In this study, field cores were collected from an Indiana state road to evaluate the VRAM and tack coat performance at the joint. Semicircular bending Illinois flexibility index (SCB-IFIT) and modified pulloff strength tests were performed to investigate the fatigue resistance and bond strength of VRAM and tack coat at the joint. Digital image analysis confirms that VRAM can migrate up to 15.88 mm (5/8 in.) from the interface. In addition, the pulloff strength test reveals that the interface bonding of the pavement containing VRAM is less than the pavement containing tack coat at low and intermediate temperatures. One of the key findings from the SCB-IFIT test is that the flexibility index of VRAM-containing pavement is around eight times higher than tack coat–containing pavement. Moreover, the fatigue cracking resistance of the VRAM-containing pavement is higher than the laboratory-prepared asphalt mixtures with PG 64-22, PG 70-22, and PG 76-22.

Asphalt Pavement Compaction Control: Relevance of Laboratory and Non-Destructive Testing Methods of Density

Assurance of asphalt pavement layer compaction, expressed by air voids ratio between field and laboratory bulk density, is one of the main criteria of the asphalt pavement durability. Thus, destructive measures should be applied, and many asphalt samples should be taken on site in order to determine the representative compaction level of constructed pavement. With the fast development of technologies, new methods should be considered for fast, non-destructive and accurate determination of asphalt bulk density on site. As there are quite few non-destructive methods related to asphalt pavement density measurement, there is a need to make comparison of such methods. Currently, when GPR methods are used to determine the density, calibration cores are used in all cases to estimate the unknown or unmeasured variables or conditions that may affect the results of dielectric value measurements. The aim of this study is to develop a regression model that can predict the bulk density of the compacted asphalt layer without coring, using the design values of the bulk density determined in the type tests of asphalt mixtures or other currently used non-destructive testing technologies (in this case PQI and NDG) and GPR measured dielectric constant values.

Correlation of ground penetrating radar and nuclear density gauge data to determine the density of asphalt pavement

This paper demonstrates the field performance of Ground Penetrating Radar (GPR) as a non-destructive testing tool to predict in situ asphalt pavement. In previous study, GPR has been used successfully in a variety of pavements application such as determining layer thickness, detecting subsurface distresses, and others. Nuclear Density Gauge (NDG) is specifically designed to measure the moisture and density of soils, aggregates, cement, and lime treated materials, and also to measure the density of asphalt concrete. Alternative analysis approaches by correlating the GPR and NDG data had been performed for density prediction of asphalt pavement. A density model name Al-Qadi, Lahouar, and Leng (ALL model) was used to predict the density of the asphalt pavement from the GPR data correlate with NDG database. This study shows that density for asphalt pavement from GPR data provide reasonably accurate density prediction when ALL model approach was used.

Modeling of asphalt mixture-screed interaction: A nonlinear dynamic vibration model for improving paving density

Paving compaction has an important influence on the significant improvement of the asphalt mixture density during pavement construction, and the paving density is mainly affected by the paver response and material behavior. To improve the density of asphalt pavement, this paper proposes a nonlinear dynamic vibration system of the interaction between asphalt mixture and screed plate. Based on the harmonic balance principle, a multi-degree of freedom nonlinear system of the screed plate-asphalt mixture interaction was established. By considering material characteristics and energy absorption efficiency during paving compaction, a paving density tendency-vibration frequency theoretical model was applied to analyze the influence law of dynamic response of the asphalt-screed interaction on the material density. The analysis results indicated that 1) both the characteristics of the asphalt mixture and the vibration frequency of the screed affected the material density during the paving process; 2) the optimal vibration frequency was higher than the natural frequency, and further compaction with a lower vibration frequency can effectively improve the energy absorption efficiency; 3) for the screed in movement, only when the vibration frequency enters the resonance region of the high-density mixture can a better compaction effect be obtained. Finally, the nonlinear dynamic model was experimentally verified. The research results are beneficial for improving the paving density and the quality of asphalt pavement, providing a basis for the effective compaction of asphalt pavement.

A GPR-Based Pavement Density Profiler: Operating Principles and Applications

Density is one of the most important parameters in the construction of asphalt mixtures and pavement engineering. When a mixture is properly designed and compacted, it will contain enough air voids to prevent plastic deformation but will have low enough air void content to prevent water ingress and moisture damage. By mapping asphalt pavement density, areas with air void content outside of the acceptable range can be identified to predict its future life and performance. We describe a new instrument, the pavement density profiler (PDP) that has evolved from many years of making measurements of asphalt pavement properties. This instrument measures the electromagnetic (EM) wave impedance to infer the asphalt pavement density (or air void content) locally and over profiles.

Achieving Asphalt Pavement Density with Minimal Mat Defects

It is well established that in-place density significantly influences asphalt pavement performance and service life. This paper discusses solutions to challenges that agencies and contractors often face when trying to achieve density requirements, or increase density, while eliminating compaction-related mat defects during the construction process. The basics of the asphalt pavement compaction processes, equipment, operations, and asphalt mixture densification are first presented, followed by information collected on a series of FHWA sponsored departments of transportation (DOTs) density demonstration projects. The authors then summarize the root causes associated with challenges in obtaining the desired density without compaction-related mat defects in a series of categories based on the DOT demonstration projects and experience assisting contractors with obtaining density on hundreds of projects. Examples are described for each category along with potential opportunities for improvements to overcome them. The demonstration projects illustrated that it is possible to make improvements when agencies and contractors embrace the idea of increasing density and reducing mat defects.

FDTD Simulation for Moisture Asphalt Pavement Thickness and Density Estimation Utilizing Ground Penetrating Radar

Ground penetrating radar (GPR) has the potential to estimate the thickness and density of asphalt pavement during compaction. However, the surface moisture sprayed by the compactor interferes with the accuracy of data collection significantly. This study proposed an approach based on the extended common midpoint (XCMP) method to minimize the effect of surface moisture. Both the numerical simulation of finite-difference time-domain (FDTD) and laboratory experiments were carried out to study the effect of the surface moisture on the GPR signal. Then, three FDTD models with different incident angles of GPR signal were established, and the difference of time intervals obtained from dry and moisture pavements with each model was studied to propose a proper antennas installation mode. Finally, the thickness and density estimated using the proposed method and surface reflection method were compared to validate the accuracy of the proposed approach. The results show that: 1) FDTD models were verified to simulate the interaction of GPR signal with moisture pavement effectively; 2) the time interval of the GPR signal between the surface and bottom of AC layer increased as the thin wet layer dielectric constant grew, and remained unaffected by the electric conductivity of the thin wet layer; 3) the average error of thickness and density predicted utilizing the proposed method were less than 1.3% and 2.4%, respectively, undercomplicated compaction conditions. This study notes that compaction monitoring in real time could benefit from the proposed method.

Improving Durability of Asphalt Pavements in Louisiana through Increased In-Place Field Density

The objective of this project was to evaluate the effects of increasing the initial in-place density of asphalt pavements on expected field performance and durability. This study was completed as part of the FHWA’s demonstration project on “Enhanced Durability through Increased In-Place Pavement Density.” Two approaches for increasing in-place density were explored: (i) the addition of an Evotherm warm-mix asphalt (WMA) additive at a dosage rate of 0.6% by the weight of mix; and (ii) the addition of 0.2% asphalt binder (Plus AC) to the design optimum asphalt binder content of standard dense-graded mixtures. The field component of the research involved three 4,000-ft long test sections representing control hot-mix asphalt (HMA) mixtures, Evotherm WMA mixtures, and the Plus AC HMA mixtures. Each test section included a binder and a wearing course for a total of six mixtures. Density measurements were determined in the laboratory from field cores taken at each test section. The high- and intermediate-temperature properties of field cores were evaluated using the Loaded Wheel Tracking and Semi-Circular Bending tests, respectively. Further, the Indirect Tensile Dynamic Modulus (IDT |E*|) test was conducted for full viscoelastic characterization of the asphalt mixtures. The two approaches considered in this study were successful in increasing field density, especially for the binder course mixtures. The two strategies for increasing in-place density also resulted in better than expected resistance to cracking and rutting, as well as an increase in mixture stiffness as measured by the IDT |E*|.

Factors Impacting Monitoring Asphalt Pavement Density by Ground Penetrating Radar

Real-time asphalt concrete (AC) pavement density monitoring is important for quality control (QC) and quality assurance (QA) purposes, because it allows correction during the compaction process. Ground penetrating radar (GPR) is capable of providing real-time AC mixture density prediction using the Al-Qadi, Lahouar, and Leng (ALL) density prediction model. However, noise sources, such as surface moisture and vibrations, may jeopardize the AC density prediction accuracy. This study proposes a mean reflection coefficient algorithm and digital filter design method to remove the surface moisture and smooth the density profile. In the mean reflection algorithm, the frequency-select bandwidth was selected as 40–70% of the actual peak frequency in the magnitude spectrum through the simulation studies. White Gaussian noise was added in the models for robustness testing. In the digital filter design method, the magnitude spectrum of the GPR predicted density profile was analyzed to decide filter types and corresponding parameters. Thresholding method was used to remove abnormal values, and window-based finite impulse response (FIR) filters were used to smooth the density profile. Lab-controlled and field tests were performed for both algorithms. Estimated aggregate dielectric constant was used to predict pavement density. A sensitivity analysis was performed to evaluate the effect of different aggregate dielectric constant on density (or air void). For surface moisture effect removal, mean reflection coefficient algorithm may be utilized to reconstruct dielectric constant values at an error less than 4%. This algorithm is independent of the antenna central frequency. For the density profile smoothing during continuous GPR survey, results show that various filter types have comparable smoothing performances. For the effect of aggregate dielectric constant on density prediction, sensitivity analysis shows that when aggregate dielectric constant values changes from 6.5 to 7, the predicted air void increases from 2.5% to 6.3%. This indicates the importance of an accurate aggregate dielectric constant estimate when applying ALL model for pavement density predictions; hence, aggregate dielectric constant estimate must be utilized.

In-Place Density of Asphalt Pavements: Case Study during Cold Weather Paving

Late-season paving is common and often performed in colder temperatures, which is the most challenging environment for attaining optimal in-place density and compaction. The in-place density of asphalt pavement greatly affects the life span of the pavement. This case study aims to evaluate and compare the effectiveness of different compaction, delivery, and mix design characteristics to ensure the optimization of in-place asphalt pavement density. To this end, four test sections were constructed over four separate days of paving during cold weather conditions. The in-place density was measured using four methods: (1) conventional or traditional cut roadway cores, (2) combination of infrared continuous thermal scanning (ICTS) with conventional or traditional cut roadway cores, (3) nonnuclear density gauge (NNDG), and (4) rolling density meter (RDM) utilizing ground-penetrating radar (GPR). The results revealed that during cold weather paving, the material transfer vehicles (MTVs) provide an effective method to minimize thermal segregation and therefore provide improved temperature and density consistency. In addition, the combination roller provided a consistent improvement compared to the standard three double-drum steel roller compaction method. It was shown that ICTS is an effective measuring technique, especially for paving in cold weather conditions, since it provides real-time information to the producer for improving temperature consistency that will result in more uniform densities. The use of nondestructive testing equipment can also strengthen the acceptance procedure in a more rigorous way by increasing the testing frequency.

The use of a non-nuclear density gauge for monitoring the compaction process of asphalt pavement

The mechanical performance of an asphalt pavement affects its durability – thus carbon footprint. Many parameters contribute to the success of a durable asphalt mix, e.g. material selection, an accurate mix and even the road design in which the asphalt mix quality is quantified. The quality of the asphalt mix, by its mechanical properties, is also related to the compaction degree. However, and specifically for high volume rates, the laying process at the construction site needs an effective method to monitor and adjust immediately the compaction quality before cooling and without damaging the layer, which is now absent. In this paper the use of a non-nuclear density gauge (PQI – Pavement Quality Indicator) is evaluated, based on a site at Brussels Airport. Considering the outcome of the present research, this PQI is advised as a unique tool for continuous density measurements and allow immediate adjustments during compaction, and decreases the number of core drilling for quality control, and as a posteriori asphalt pavement density test where cores are prohibited. The use of PQI could be recommended to be a part of the standard quality control process in the Flemish region.

Specification Limits and Pay Adjustment for Longitudinal Joint Density of Asphalt Pavements: Case Study in New Jersey

This paper summarizes a case study on developing specification limits and pay adjustments for the longitudinal joint density of asphalt pavements. The existing joint density specifications used by various agencies first were reviewed for the minimum joint density requirements and the corresponding pay adjustments. Laboratory tests were conducted to measure air voids of field cores taken from selected field projects with the saturated surface dry method (AASHTO T 166) and the automatic vacuum-sealing method (AASHTO T 331). Permeability measurements were conducted with a falling-head permeability device. The air voids at the joint were found to be 1.5% to 2% greater than the air voids at the mats adjacent to the joint. For conditions specific to New Jersey, individual testing of the theoretical maximum density of the cores taken at the joint is recommended because of the existence of joint adhesive. The upper limits for air voids at the longitudinal joint are recommended to be 9% for stone matrix asphalt and 10% for hot-mix asphalt, on the basis of the permeability criterion of 150 × 10−5 cm/s reported in previous studies. Furthermore, alternative pay equations for air voids at the longitudinal joint were proposed, with different triggers for retest and for rejectable quality level. A SpecRisk analysis was conducted to confirm that the effective acceptable quality level coincided with the stated acceptable quality level and that the acceptance procedures properly awarded 100% payment at the stated acceptable quality level. The study led to a draft quality assurance specification for longitudinal joint density that was proposed for future implementation.

Development of compaction monitoring system for asphalt pavements

There is a great interest in developing and implementing new technologies for real-time evaluation of the uniformity of the construction of asphalt layers. In this study, the researchers developed a system for monitoring and documenting the compaction process of asphalt mixtures in the field. This system is called the compaction monitoring system (CMS). The CMS uses the latest global positioning system technologies and various sensors to provide full coverage of an asphalt layer. The new system can be mounted on any roller in a matter of minutes, and it provides the roller operator with real-time color displays of the number of passes of the entire mat, the compaction effectiveness, and the temperature at the first pass of the roller. This system was successfully tested in a number of field projects. The CMS was able to show some inconsistencies in the compaction process such as unequal compaction converge across the mat, non-uniform compaction effort and temperature, and delay in compaction after placement of asphalt mixtures. The compaction data are stored for post-processing analysis and evaluation. In addition, the researchers validated a proposed method for predicting the density of asphalt pavements in the field. The results showed good correlation between predicted and measured density.

EFFECT OF PARTICLE SHAPE ON THE WORKABILITY AND PROPERTIES OF CONVENTIONAL BITUMINOUS MIXES

The flakiness and elongation index is an important physical property of mineral aggregates affecting the quality of asphalt mixes. The presence of Combined Flakiness and Elongation index (CFEI) exceeding certain limits adversely affects the durability and properties of asphalt mixture. A bituminous mixture is composed of approximately 95% by weight or 80% by volume of mineral aggregates. Therefore it is important to see how aggregate gradation and different combined indices affect the performance of bituminous mixes. In recent times continuous increase in volume of traffic has resulted in increased in demands for further research relating to the properties of the material such as workability and stability of hot mix asphalt. Workability of hot mix asphalt is a critical element in getting the desired density of asphalt pavements The present study was taken up with the observations of evaluating the influence of different combined shape indices on workability of bituminous mixes at upper, middle and lower gradation as per the MORTH specified For BC-II. In this study Marshall Method of mix design is adopted and OBC is determined only 30-35% combined indices of mid gradation. Same OBC is used for entire research work for evaluating the workability of bituminous mix at upper, middle and lower gradation of 30-35% 35-40%, 40-45% and 45-50% of combined indices.

Calibration of FDTD Simulation of GPR Signal for Asphalt Pavement Compaction Monitoring

This paper demonstrates that the finite-difference time-domain (FDTD) method can be used to accurately simulate ground-penetrating radar (GPR) wave and its interaction with pavement having different densities and moisture conditions. The FDTD simulation described in this paper is part of the research efforts into the application of GPR on monitoring the density of asphalt pavement during compaction. The challenge is to separate the effect of density increase from the effect of the increase in surface moisture content on GPR signals. The first part of this paper describes the procedure for finding an equivalent excitation function used in simulation that can generate a GPR signal that matches the real signal. Discrete wavelet transform (DWT) was applied to denoise the signal. It was found that the equivalent excitation source and the DWT technique provided an accurate match between the simulation signal and real GPR signal in both the time domain and frequency domain. The second part of this paper demonstrates the application of FDTD simulation in investigating GPR responses on pavements with different densities and surface moisture content. The simulation successfully revealed the “frequency selective” feature of the effect of surface moisture content on GPR signals. Laboratory experiments were also conducted, and the results verified the findings in FDTD simulations. The FDTD simulation was shown to be an effective and efficient tool for studying the interaction of GPR waves with pavement. An accurate modeling of the signal and its propagation provided meaningful insights as well as the possibility for developing practical data-processing techniques.

Application of ground-penetrating radar in measuring the density of asphalt pavements and its relationship to mechanical properties

The ground-penetrating radar (GPR) is a proven technology that is used typically to determine the thicknesses of pavement layers. This paper explores the applicability of the GPR to assess the density of the asphalt layer in pavements. The measurements were conducted on three test sections that were constructed using different asphalt mixtures. Each of the test sections was divided into sub-test sections that were compacted using different compaction methods and number of roller passes in order to achieve a range of asphalt mixture densities. The results showed that there was very good correlation between the GPR results and density of extracted field cores. Consequently, the paper examines the correlation between density and mechanical properties of asphalt mixtures. The results of the mechanical tests provided valuable information on the effect of density on performance.

Algorithm development for the application of ground-penetrating radar on asphalt pavement compaction monitoring

Ground-penetrating radar (GPR) is a promising non-destructive technique to be applied on monitoring the density change during asphalt pavement compaction. The utmost challenge of this application is the unknown effect of surface moisture, sprayed by the compactor during compaction, on GPR signals. To extract density information without the effect of surface moisture, a correction algorithm based on reference scan approach was developed. To evaluate the performance of the algorithm, a full-scale test site was constructed with compaction pass number from 0 to 10, and a large amount of GPR data were collected from the pavement with different surface moisture contents. A total of 22 cores were extracted for validation purposes. After applying the algorithm, it was found that the average density prediction error was reduced significantly. By using correction algorithm together with the density model, the density of asphalt pavement was obtained with high accuracy.

Pattern recognition algorithms for density estimation of asphalt pavement during compaction: a simulation study

This paper presents the application of artificial neural network (ANN) based pattern recognition to extract the density information of asphalt pavement from simulated ground penetrating radar (GPR) signals. This study is part of research efforts into the application of GPR to monitor asphalt pavement density during compaction. The main challenge is to eliminate the effect of roller-sprayed water on GPR signals during compaction and to extract density information accurately. A calibration of the excitation function was conducted to provide an accurate match between the simulated signal and the real signal. A modified electromagnetic mixing model was then used to calculate the dielectric constant of asphalt mixture with water. A large database of GPR responses was generated from pavement models having different air void contents and various surface moisture contents using finite-difference time-domain simulation. Feature extraction was performed to extract density-related features from the simulated GPR responses. Air void contents were divided into five classes representing different compaction statuses. An ANN-based pattern recognition system was trained using the extracted features as inputs and air void content classes as target outputs. Accuracy of the system was tested using test data set. Classification of air void contents using the developed algorithm is found to be highly accurate, which indicates effectiveness of this method to predict asphalt concrete density.