Compacted Pavement Research Articles

Improved density prediction model based on global optimization algorithm for GPR system

Density prediction models are key to pavement compaction and density estimation using ground penetrating radar (GPR). However, current models do not account for the effects of dielectric constant errors and rely on limited data for parameter fitting. This article introduces an electromagnetic (EM) mixing theory and genetic algorithm (GA) based density prediction model named EM-GA. A comprehensive density database is established from literature, laboratory and field tests. After comparing Bayesian optimization, GA, simulated annealing (SA), and particle swarm optimization (PSO), the GA, which performs the best, is selected. On the testing set, the EM-GA model outperforms traditional models, with a notable reduction of 43.6 % in Mean Absolute Percentage Error (MAPE) and 39.8 % in Root Mean Square Error (RMSE). More importantly, the EM-GA predictions are accurate in the validation of four continuous survey lines. The proposed EM-GA model effectively enhances the accuracy of GPR-based density estimation for newly constructed asphalt pavement.

Investigation of Particle Rotation Characteristics and Compaction Quality Control of Asphalt Pavement Using the Discrete Element Method.

The compaction of asphalt pavement is a crucial step to ensure its service life. Although intelligent compaction technology can monitor compaction quality in real time, its application to individual asphalt surface courses still faces limitations. Therefore, it is necessary to study the compaction mechanism of asphalt pavements from the particle level to optimize intelligent compaction technology. This study constructed an asphalt pavement compaction model using the Discrete Element Method (DEM). First, the changes in pavement smoothness during the compaction process were analyzed. Second, the changes in the angular velocity of the mixture and the triaxial angular velocity (TAV) of the mortar, aggregates, and mixture during vibratory compaction were examined. Finally, the correlations between the TAV amplitude and the coordination number (CN) amplitude with the compaction degree of the mixture were investigated. This study found that vibratory compaction can significantly reduce asymmetric wave deformation, improving pavement smoothness. The mixture primarily rotates in the vertical plane during the first six passes of vibratory compaction and within the horizontal plane during the seventh pass. Additionally, TAV reveals the three-dimensional dynamic rotation characteristics of the particles, and the linear relationship between its amplitude and the pavement compaction degree aids in controlling the compaction quality of asphalt pavements. Finally, the linear relationship between CN amplitude and pavement compaction degree can predict the stability of the aggregate structure. This study significantly enhances quality control in pavement compaction and advances intelligent compaction technology development.

Recent Development in Intelligent Compaction for Asphalt Pavement Construction: Leveraging Smart Sensors and Machine Learning.

Intelligent compaction (IC) has emerged as a breakthrough technology that utilizes advanced sensing, data transmission, and control systems to optimize asphalt pavement compaction quality and efficiency. However, accurate assessment of compaction status remains challenging under real construction conditions. This paper reviewed recent progress and applications of smart sensors and machine learning (ML) to address existing limitations in IC. The principles and components of various advanced sensors deployed in IC systems were introduced, including SmartRock, fiber Bragg grating, and integrated circuit piezoelectric acceleration sensors. Case studies on utilizing these sensors for particle behavior monitoring, strain measurement, and impact data collection were reviewed. Meanwhile, common ML algorithms including regression, classification, clustering, and artificial neural networks were discussed. Practical examples of applying ML to estimate mechanical properties, evaluate overall compaction quality, and predict soil firmness through supervised and unsupervised models were examined. Results indicated smart sensors have enhanced compaction monitoring capabilities but require robustness improvements. ML provides a data-driven approach to complement traditional empirical methods but necessitates extensive field validation. Potential integration with digital construction technologies such as building information modeling and augmented reality was also explored. In conclusion, leveraging emerging sensing and artificial intelligence presents opportunities to optimize the IC process and address key challenges. However, cooperation across disciplines will be vital to test and refine technologies under real-world conditions. This study serves to advance understanding and highlight priority areas for future research toward the realization of IC's full potential.

Analisis Kepadatan Lapangan Dengan Metode Sand Cone Pada Pembangunan Jalan Lingkar Utara Lamongan

The location of the road studied is the northern ring road which is still in the form of a compacted pavement layer. With this road, it can reduce traffic jams in the city and divert heavy vehicles. Field density analysis was carried out on the North Ring Road in Lamongan district using the Sand Cone method to obtain soil water content values ​​on the road. The work procedure carried out is determining the weight of the sand, the weight of the soil, the grade water, dry soil density, and field density. The testing point was carried out at 152 different points for every 25 meters, namely from STA 0+000 to STA 3+800. The results showed that the average soil water content was 19.0%, and the soil density was 96.98%. According to the requirements of SNI 03-2008-1992, the recommended soil density value is 95%. From the results of the tests that have been carried out it can be concluded that the density The soil in the field meets the specified soil density requirements because the average density in the field on road pavement is 96.98%.

Structure evolution analysis of asphalt mixtures during compaction based on particle tracking and granular properties

Pavement compaction is a process of structure evolution of materials accompanied by energy dissipation, which is closely related to the inherent granular properties of asphalt mixture. This research achieved dynamic characterization of particle migration energy and contact force development through particle tracking technique and discrete element simulation. Analytical theories for multi-stage structure evolution and compaction mechanisms were proposed based on granular properties. Results indicate that kinetic, dissipative, and potential energies dynamically represent stages of structure evolution, determined by particle collisions, self-organization into arches, and interlocking reinforcement. The initial density state is established after interparticle collisions, while self-organization occurs as particles adaptively rearrange spatially by rotation in response to unbalanced forces, accompanied by a cyclical strengthening trend of arch formation and collapse. Arches facilitate stress redistribution toward isotropy, with strong contact forces exhibiting a top-down and side-center trend, progressively supported by particles larger than 4.75 mm. Theoretical measures for compaction control were proposed, including pre-calculation of IC, selection of compaction temperature corresponding to the optimum energy efficiency, and control of principal stress deflection within the friction cone. This research aims to provide insight into granular properties and compaction dynamics, thereby contributing to intelligent compaction.

Assessing Asphalt Pavement Pre-Compaction with Paver Screed Frequency Measurements

The quality and longevity of an asphalt road depends on the accurate compaction of the asphalt pavement. Particular emphasis should be placed on the pre-compaction process involving the paver’s screed. Inadequate or excessive pre-compaction can result in paving errors and inhomogeneities within the pavement, which even expert roller operation cannot rectify. In practical paving, however, the degree of pre-compaction is rarely determined, so that one is dependent on the empirical knowledge and assessments of the paving personnel. Within the context of the research initiative, InfraROB (Grant Agreement No.: 955337), an innovative system was devised to infer the extent of pre-compaction by leveraging the resonance frequency of the paver’s screed. This system comprises a rugged, enclosed acceleration sensor capable of capturing high-speed accelerations and a Wi-Fi-enabled control unit for data storage and processing. To validate this system, a series of test pavements were constructed using an asphalt binder mix (AC 16 BS), deliberately varying the speed of the tamper compaction unit in four steps from 0 rpm up to 1500 rpm. Half of the test lanes were longitudinally compacted with rollers, allowing for the examination of the asphalt pavement in its partially pre-compacted state. To achieve this, drill cores were extracted, and their density was assessed in the laboratory. Through the application of Fast Fourier Transformation, the measured resonance frequency data was analysed and subsequently correlated with the outcomes of the drill core inspections. This analysis revealed a strong logarithmic relationship between the average peak acceleration and the bulk densities measured, with a high coefficient of determination exceeding 0.9. The presented method enables real-time assessment of the pre-compaction status of asphalt pavement, offering support to paving personnel, optimising roller usage, and enhancing asphalt pavement quality.

Analisis Kepadatan Lapangan Menggunakan Metoda Sand Cone Di Jalan Perumahan Ekajaya Permata 1 Sicincin Kota Payakumbuh

Every housing complex must have adequate road access because roads are a means of public transportation used by the community to support daily activities. Road infrastructure makes transportation easier and allows people to carry out activities. The road foundation layer will experience a decrease in the soil's bearing capacity as traffic flow increases, because the road structure distributes the load to all layers beneath it and supports the weight of vehicles passing on it. In circumstances like this, road construction must be of the utmost importance, and data about the existing soil on the site must be tested first. In this research, the author took a residential road that had just been built and still had a layer of compacted pavement. By making this road, people can more easily access transportation and feel comfortable when using it. Field density analysis was carried out on Jalan Perumahan Ekajaya Permata 1 Sicincin, Payakumbuh City. The sand cone method or sand cone test is used to calculate the degree of soil density. Various measurements are calculated, including sand bulk density, soil bulk density, water content, dry soil bulk density, and degree of field density. Tests were carried out at ten points at a distance of 25 meters each. The average soil water content is 7.73%. According to SNI 03-2008-1992, the recommended value of soil density is 95%. The test results show that the average degree of density in the field is 72.51%. Because the soil density in the field does not yet meet the soil density requirements of 95%, it is necessary to increase the compaction further until it meets the specified density requirements.

Alabama Field Project to Evaluate Variability in Soil–Cement Specimens Compacted with the Plastic Mold Device

The plastic mold compaction device (PM Device) was developed in Mississippi to compact cementitiously stabilized soil inside plastic molds to improve soil–cement quality by adding value during design and construction activities. The PM Device has been incorporated as an AASHTO provisional standard (AASHTO PP92-19) and, to date, prevailing activities have been Mississippi Department of Transportation projects and have included controlled laboratory evaluations and field projects. This paper goes beyond previous efforts, to document a field study in which the PM Device was successfully used on an Alabama Department of Transportation project to evaluate its effectiveness within another state’s construction specifications. The PM Device was capable of capturing quantifiable variation in mechanical properties over the duration of the construction project, as well as producing similar mechanical properties to cores taken from the compacted pavement surface. Additionally, molds described in AASHTO PP92-19 were compared with one another to evaluate their potential within the standard practice. AASHTO PP92-19 protocols were sufficient to produce viable, repeatable test specimens within another state department of transportation construction environment for quality control and quality assurance.

Investigation on the roller-pavement interaction and asphalt pavement compactness based on marginal spectrum of vibration signal energy

Compaction is a critical assurance for the quality and performance of asphalt pavement in terms of durability and serviceability. At present, there is a knowledge gap in the roller-pavement interaction in terms of energy variation during the process of asphalt pavement compaction. This paper aims to reveal the interaction and energy variation between the vibrating drum and pavement surface course during compaction process. Based on field tests, vibration signals of both the vibrating drum and pavement (i.e., the top, middle and bottom surface layers) were captured by acceleration sensors, and then the Hilbert marginal spectrum of the signals was obtained by the Hilbert-Huang Transform (HHT) for interpreting the signal features. Based on the marginal spectrum, the energy variation of the vibrating system (drum and pavement) during compaction was obtained. A predictive model of pavement compactness was further established according to the observed linear relationships between the pavement compactness and the energies of the vibrating system, and was then validated in the field application. The findings show that the energy-based approach adopted herein is able to not only characterize the compactness of asphalt pavement, but also reflect the uniformity of compaction. The developed relationships have a good potential as a useful tool for quality control in the field compaction practice.

Optimizing Asphalt Surface Course Compaction: Insights from Aggregate Triaxial Acceleration Responses.

The compaction quality of asphalt surface courses has a significant impact on the overall performance of asphalt pavements, but the dynamic response and compaction degree variations of different asphalt surface courses (top, middle, and bottom surface courses) during vibrational compaction have still received limited research. SmartRock sensors can be utilized to monitor aggregate acceleration in real-time. This study aims to address this gap using SmartRock sensor technology to further understand the compaction mechanisms of different asphalt surface courses from a particle perspective, as well as the relationship between aggregate acceleration and compaction degree. The results indicate that the rolling of steel drums induces a significant alteration of the aggregate acceleration along the roller's rolling direction, primarily resulting in horizontal shearing in that direction. As distance increases, vibration waves gradually attenuate on both sides of vibrating drums, and surface course thickness and gradation significantly affect acceleration amplitude. There is a linear correlation between triaxial aggregate acceleration and compaction degree, with the vertical correlation being the strongest. Finally, an empirical relationship between triaxial acceleration and pavement compaction degree was established, providing a basis for predicting the asphalt surface course density. These findings enhance our understanding of pavement compaction mechanisms and promote innovation in asphalt pavement compaction and quality control methods.

Research on Compaction Technology of Municipal Road and Bridge Engineering Roadbed and Pavement

In recent years, China has constructed various scale and level of road projects. The implementation of these projects has improved China's road transportation system and brought great convenience to people's travel. However, the implementation of roadbed and pavement compaction is an aspect that cannot be ignored in road engineering. The application of technology and construction effectiveness are related to the quality of road engineering. Therefore, in any road engineering project, standardized roadbed and pavement compaction must be carried out based on the construction requirements of the road itself to ensure that the compaction meets the construction requirements.

Asphalt Pavement Compaction and Vehicle Speed Monitoring Using Intelligent Aggregate

The stable skeletal structure formed by the interlocking mechanism of the spatial movement of aggregate particles during compaction is the mechanism by which asphalt pavements are compacted and shaped. A major problem facing conventional compaction monitoring is that lacking the ability to monitor particle movement and a real-time evaluation method for pavement compaction, which can easily lead to problems such as uneven compaction and over-compaction. In addition, vehicle speed is an important parameter for analysing the dynamic response of a pavement. Current vehicle speed monitoring relies on complex field equipment and the collected vehicle speed parameters are difficult to match with other sensors for fusion analysis. In this paper, a method for monitoring the compaction quality of asphalt pavements and a method for collecting vehicle speed is proposed based on intelligent aggregate and aggregates interaction mechanisms. The experimental results show that with the continuous action of the compaction machinery, the compaction state of the asphalt pavement can be reliably captured and monitored by studying the spatio-temporal movement pattern of the intelligent aggregates. Meanwhile, the analysis of the time nodes of intelligent aggregate attitude change under the action of vehicle load allows accurate acquisition of vehicle speed parameters. Therefore, the method proposed in this study can improve the accuracy of asphalt pavement compaction state control as well as the accurate acquisition of vehicle speed. It can provide a reference for the later analysis of the dynamic response of pavement loads and the intelligent compaction of pavements.

Preliminary characterization on the dynamic mechanism of asphalt mixture under on-site vibratory compaction

Compaction is the final critical step in the construction of asphalt pavements, but the dynamic response of the mixtures at the particle scale and its correlation with the compaction degree have received limited in-depth investigations. Based on the SmartRock sensor technique, this study is aimed for this inadequacy and to further understand the interaction characteristics (e.g., rolling speed, vibration range and contact width) between the steel drums and pavement surface during compaction at the particle scale. Meanwhile, the dynamic responses (i.e., acceleration frequency and amplitude) of the aggregates in the asphalt mixture were comprehensively investigated to establish the correlation between the acceleration amplitude and compaction degree of pavement. According to the results, the vibrating drum shows a higher compaction effectiveness than the driving drum in the z-direction. The acceleration frequency reflects the energy attenuation of vibration waves during vibrational compaction, and the attenuation of vibration acceleration is normally distributed with the distance from the SmartRock. Lastly, an empirical relationship was developed between the maximum acceleration and pavement compaction degree and can be used to provide reasonable estimations for the in-situ density. The findings are expected to shed light on the compaction mechanism of asphalt pavement, and to provide a potential approach/basis for improving the on-site quality control and decision-making during compaction.

Data sensing and compaction condition modeling for asphalt pavements

Asphalt pavement compaction is a process of rearranging asphalt particles to reduce voids and increase density. Current empirical methods can sometimes cause compaction problems, particularly when new materials are implemented. This paper develops an innovative monitoring system to determine the compaction condition of asphalt pavement based on particle kinematics. Eleven asphalt mixtures were compacted in the laboratory, and two field compaction projects were carried out. A particle-size wireless sensor, SmartRock, was used to collect the particle kinematic behaviors during compaction. A compaction classification model and a density prediction model were established to predict the compaction condition. Similar particle rotation characteristics were identified under gyratory compaction and roller compaction, allowing the predictive models developed in the laboratory to estimate the field compaction. The predictions are in agreement with the measurement densities, which verifies the applicability of using the particle kinematics and intelligent model to predict the compaction of asphalt pavement.

Investigation on the compaction process of steel bridge deck pavement based on DEM-FEM coupling model

ABSTRACT Compared with the compaction of general highway asphalt pavement, that of steel bridge deck pavement (SBDP) is more complicated and vulnerable due to special supporting conditions and severe construction environment. Besides, the existing simulation models are not suitable for the analysis of SBDP compaction. To clarify the compaction mechanism and characteristics of SBDP under unfavorable construction conditions, the particles were generated using a random particle generation algorithm and the asphalt mixture layer was simulated through the discrete element method (DEM); the steel bridge deck with weld seam was taken as an example of unfavorable external conditions and simulated through the finite element method (FEM). On this basis, the spatial movement and contact state of the particles during the compaction process were tracked and investigated using the DEM-FEM coupling model. Results show that the DEM-FEM coupling model is effective and feasible to simulate SBDP compaction process. The spatial movement and contact state of the particles are described. The findings could contribute to improving SBDP compaction quality. The coupling of DEM-FEM also provides the method reference to the research of other SBDP compaction problems, such as the influence of temperature field variation and bridge vibration.

The Stiffness Behavior of Asphalt Mixtures with Different Compactness under Variable Confinement.

The dynamic modulus is a key property determining the short- and long-term performance of asphalt pavement, and its strong dependence on confining pressure and material density (mixture compactness) has been clearly indicated in the literature. It is always challenging to reproduce three-dimensional in situ stress conditions in the laboratory. To alleviate this difficulty, in this study, a convenient experimental setup was developed, in which the lateral confinement was made present and variable as a concomitant reaction of the surrounding materials to the vertical loading. Three dense-graded mixtures were prepared to a set of four different densities and then subjected to the confined dynamic modulus test. The results indicated a significant dependence of the confined modulus on the three factors of temperature, frequency, and compactness and that the mixture with coarser gradation demonstrated a less sensitivity to these parameters. A mathematical model was developed for the dynamic modulus master curve unifying these factors by means of horizontal shifting due to the time-temperature superposition principle (validated against the variable confinement at different compactness) and the vertical shift factor as a function of reduced frequency and compactness. The adequacy of the model was demonstrated using the experimental data, and its potential application in field pavement compaction was discussed.

Evaluation of Compaction Uniformity of Asphalt Pavement Based on Construction Depth Variation

The continuous monitoring and real-time feedback on the uniformity of the mixture after paving and compaction is important to guide the construction and improve the life of the asphalt pavement. Thus, in this study, the latest digital image technology was used to collect images of asphalt pavement after paving and compaction according to the set parameters. The images collected were preprocessed in steps such as binary grayscale, filtering, histogram, and small particle filtering, which established the method for calculating the construction depth H P of the digital images of pavement. Moreover, a method was proposed to evaluate the uniformity of asphalt pavement using the construction depth coefficient of variation. The coefficients of variation were computed based on 100 images of the dependent project and compared with the actual images. The results indicated that the construction depth coefficient of variation of the digital images obtained by the developed calculation procedure was in agreement with the actual situation and combined the correlation degree of the calculation results. Small areas of 42 are recommended as the division of the asphalt pavement compaction uniformity evaluation method based on construction depth variation, and the use of C v 4 ≥ 8.0 as the evaluation standard for the segregation of asphalt pavement is recommended. The method proposed is a new and rapid test to evaluate and detect the asphalt pavement uniformity.

Characterizing asphalt emissions under in-service conditions

Recent studies have suggested that asphalt related emissions at environmentally pertinent conditions are a major contributor of volatile organic compounds ubiquitous to the environment. Many variables such as temperature/viscosity of asphalt binder, solar irradiance of the asphalt binder, and geometric constraints including film thickness, the act of coating aggregate to produce Hot Mix Asphalt, and compaction into pavements influence the magnitude and composition of measured emissions. Continuous films of asphalt binder were used to determine how temperature/viscosity and film thicknesses can influence measured emissions. The magnitude of emissions scaled with the inverse of viscosity, whereas the composition of emissions varied with film thickness and age of the asphalt binder sample. Asphalt binder exposed to solar irradiance showed short term impacts on emissions in the first hours of exposure. Compacted asphalt pavements were used to simulate real world new in-service conditions. The emissions from a freshly compacted asphalt pavement were compared to a 17-year-old pavement sample collected from the field to determine how the act of compacting asphalt binder coated in aggregate influenced emissions over a 17-year period. An increase in the complexity of the system caused slowing in the total emissions profile. While lower than what was observed in the freshly compacted samples, emissions were still observed in the 17-year-old pavement. The composition of emissions indicated that smaller and more volatile compounds are capable of being released from deeper within the compacted pavement, whereas the larger and less volatile compounds tend to remain trapped. • Asphalt emission generator used to measure emissions under in-service conditions. • The effects of solar irradiation on asphalt pavement emission. • Solar irradiation of asphalt binders generates short term increases in emissions. • Effects of asphalt pavement compaction on released emissions.

Prediction of Primary Deformation Modulus Based on Bearing Capacity: A Case on Forest Road with a Light Falling Weight Deflectometer Zorn ZFG 3000 GPS

Bearing capacity and compaction are among the most important and frequently used geotechnical parameters in road construction. The aim of this study was to determine the possibility of predicting the value of the primary deformation modulus E1 (obtained from measurements using a static plate load test—PLT) based on measurements with a Zorn light falling weight deflectometer (LFWD), type ZFG 3000 GPS, with a drop weight of 10 kg. A regression analysis was performed on 245 bearing capacity measurements that were taken on 46 forest road sections with various road surfaces. Different regression models were tested, from linear to logarithmic, polynomial, exponential and power models, but excluding polynomials of fourth and higher degree. The results showed that the prediction of E1 values (PLT) from the dynamic deformation modulus values Evd (LFWD) was possible. However, the reported unsatisfactory strength of the relationship between the two parameters was associated with a high risk of error (r = 0.64, R2 = 0.41, Se = 49.78). Neither the use of more complex non-linear regression models, nor the use of multiple regression by introducing an additional estimator in the form of the s/v ratio, significantly improved estimation results. The quality of the prediction of the E1 value was not constant. It varied, depending on the type of forest road, the use of geosynthetic reinforcement and the type of road subgrade. During the study, it was also found that the quality of the prediction of the E1 value could be improved by limiting the range of Evd values tested from above. It is advisable to continue this type of research, as the obtained results could form the basis for future development of national standards for the use of LFWDs to control the bearing capacity and compaction of forest road pavements.

Analysis of the Key Points of Subgrade and Pavement Compaction in Municipal Road Construction

Analysis of the Key Points of Subgrade and Pavement Compaction in Municipal Road Construction