Flexible Pavement Performance Research Articles

Performance prediction for network-level flexible pavements using an optimised ANN approach

ABSTRACT Considering that the road network shares traffic flow as a system, this study aimed to predict the network-level flexible pavement performance, using an optimised artificial neural network (ANN) approach to predict the pavement performance of each individual road, and the Ford-Fulkerson algorithm to determine the weight coefficients of roads. ANNs were developed to predict distress conditions, functional conditions and structural performance using the inputs of the pavement age and structural, traffic and climatic conditions. ANNs were trained with Long-Term Pavement Performance (LTPP) program data, and almost all the coefficient of determination values between ANN outputs and measured results are larger than 0.9. This ANN approach was optimised by establishing grey models to provide predictive short-term performance data for training ANNs, and employing Kalman Filter to modify the long-term performance prediction. Applications in typical LTPP sections validated the effectiveness of the optimisation method. This study used the reduction in road network capacity due to the assumed unavailability of a certain road to quantify its role (weight coefficient), which was calculated using the Ford-Fulkerson algorithm. This network-level performance prediction approach was applied in a 25-expressways network in Shanghai, which validated the good generalisation capabilities of ANNs and feasibility of the Ford-Fulkerson algorithm.

Mutual impacts of changing climate and flexible pavement performance considering resilience and sustainable aspects

Roads play a vital role in transportation systems, and their construction and maintenance expenses are high. Those reasons make crucial the examination of factors that accelerate road deterioration and those factors' negative impacts on societies. Climatic-related elements, especially temperature and precipitation, significantly affect the quality and lifespans of roads. The Intergovernmental Panel on Climate Change has reported that increasing greenhouse gas (GHG) emissions is causing changes in climate and that the rate of change has accelerated during the past several decades. To assess the impacts of changing climatic parameters on flexible-pavement performance, this study used 32 climate models to evaluate the performance of interstate, primary, and secondary roads across 11 diverse locations with varying traffic and climatic conditions. The study's findings reveal that changing climate exacerbates pavement distresses, leading to reduced pavement lifespans and increased numbers of reconstruction projects, which in turn raise demands for materials and equipment and contribute to higher GHG emissions. The effects of changing climate and changing climate's associated economic and environmental costs make the application of various engineering solutions to enhance pavement resilience essential, as described in this paper, in the absence of comprehensive emissions reduction strategies.

Ensemble Learning Approach for Developing Performance Models of Flexible Pavement

This research utilizes the Long-Term Pavement Performance database, focusing on devel-oping a predictive model for flexible pavement performance in the Southern United States. Analyzing 367 pavement sections, this study investigates crucial factors influencing asphaltic concrete (AC) pavement deterioration, such as structural and material components, air voids, compaction density, temperature at laydown, traffic load, precipitation, and freeze–thaw cycles. The objective of this study is to develop a predictive machine learning model for AC pavement wheel path cracking (WpCrAr) and the age at which cracking initiates (WpCrAr) as performance indicators. This study thoroughly investigated three ensemble machine learning models, including random forest, extremely randomized trees (ETR), and extreme gradient boosting (XGBoost). It was observed that XGBoost, optimized using Bayesian methods, emerged as the most effective among the evaluated models, demonstrating good predictive accuracy, with an R2 of 0.79 for WpCrAr and 0.92 for AgeCrack and mean absolute errors of 1.07 and 0.74, respectively. The most important features influencing crack initiation and progression were identified, including equivalent single axle load (ESAL), pavement age, number of layers, precipitation, and freeze–thaw cycles. This paper also showed the impact of pavement material combinations for base and subgrade layers on the delay of crack initiation.

Long-Term Performance of Flexible Pavements Containing Crumb Rubber Modified Asphalt in Louisiana

The use of crumb rubber modifiers (CRMs) in asphalt mixtures plays a significant role in creating a sustainable circular economy. This study aims to evaluate the field performance of CRM asphalt sections with service years greater than eight. Five field projects were evaluated. Each project had one or two CRM sections constructed alongside a companion control section. Five types of CRM products were considered. A 16-mesh proprietary CRM, a Rouse-80 powder (R-80), and a Neste Wright powder were used in the wet blending process. Further, a 16-mesh generic crumb rubber, a PlusRideTM shredded rubber, and R-80 were used in a dry blend. Field performance data, including rutting, roughness, and cracking, were collected and analyzed. Moreover, economic analysis was performed to ascertain the cost-effectiveness (CE) of constructing CRM sections. Furthermore, laboratory performance indicators measured during construction were analyzed to ascertain their ability to rank field performance. Generally, CRM sections exhibited significantly similar or better ride quality, cracking and rutting resistance, and pavement condition index than their corresponding control sections. In some cases, the styrene-butadiene-styrene polymer modifier showed better cracking resistance in the control sections than the CRMs. CRM asphalt sections generally exhibited higher CE than their corresponding control sections because of their high initial unit costs. The Rouse wet CRM asphalt section in field project 4, which had a relatively lower unit cost, was found to be cost-effective compared to its corresponding control section. The limited laboratory mechanical performance parameters considered were ineffective in consistently ranking field performance indicators.

Experimental investigation of the geometry of geocell on the performance of flexible pavement under repeated loading

To evaluate the benefit of geocells of different geometrical configurations for pavement application, full-scale instrumented model tests were performed on pavement sections reinforced with geocells of different geometrical configurations subjected to monotonic and repeated loading. The responses studied were stress distribution in different pavement layers, induced strains in geocell walls, and settlement characteristics. The reinforced sections exhibited a significant reduction in rut depth as well as localized stress concentration compared to the unreinforced section. The reduction in rut depth was found to be influenced by the geocell height as well as weld spacing. The geocell reinforcement was found to distribute the stresses in the subgrade and subbase layers more efficiently, thus reducing the stress concentration in these layers. The strain measurements were found to be higher at the bottom of the geocell walls indicating a higher confinement effect on a lower part of the geocell. In the field, mostly geocells of 356 mm weld spacing and 150 mm height (SW356-H150) are used. However, this study suggests that a geocell of 330 mm weld spacing and 100 mm height (SW330-H100) having approximately 30% lower cost compared to SW356-H150 is as effective in reducing the rut depth and localized vertical stress distribution.

Induction heating and induced healing evaluation of the asphalt concretes incorporating conductive aggregates exposed to microwave radiation

This study investigates the application of aggregate-based conductive additives, including steel slag, Iron slag, and ferrosilicon, in asphalt concretes for induction heating and induced healing purposes. The research focuses on evaluating the mechanical properties, induction heating capabilities, induced crack healing, environmental impacts, and cost of various conductive asphalt concretes. The Gray Relation Analysis (GRA) technique is then employed to determine the sustainability ranking of these mixtures based on the aforementioned criteria. The mechanical properties of the asphalt concretes were evaluated through the Indirect tensile strength at intermediate temperature and semi-circular bending tests at intermediate and low temperatures. The homogeneous induction heating rate of the mixtures was also examined. Additionally, the healing indices for the breaking-healing cycles were investigated. The environmental impacts and fabrication cost of conductive asphalt concretes were compared to identify the most sustainable conductive mixture with optimal performance and durability. The results demonstrate that the addition of aggregate-based conductive additives significantly improves the mechanical properties and homogeneous heating rates under microwave radiation. Furthermore, the conducted tests indicate that the introduced conductive asphalt concretes possess the ability to heal and restore their mechanical properties after damage or cracking. Moreover, the sustainability analysis reveals that the mixtures incorporating steel slag, especially asphalt concrete incorporating fine steel slag, are more sustainable and cost-effective compared to conventional asphalt mixtures. These findings provide valuable insights for road infrastructure and pavement design, aiming to incorporate innovative and environmentally friendly materials and methods to enhance the healing competencies and performance of flexible pavements.

Modelling the effects of flexible pavement distresses in the long-term pavement performance database on performance

Evaluating flexible pavement performance is mandatory for managing transport infrastructure. This study focuses on modeling the relationships between international roughness index (IRI) and a total of 10 types of pavement distress, including alligator, block, wheel path length, wheel path longitudinal, non-wheel path longitudinal, transverse crackings, patches, bleeding, raveling areas, and pumping. The data recorded under the Long-Term Pavement Performance was used to develop the models. Data sets covering General Pavement Studies from seven states of the United States were used in modeling. The study used modeling approaches, including nonlinear regression analysis, multivariate adaptive regression splines, and artificial neural networks (ANN), in which IRI was the dependent variable and pavement distress was the independent variable. In the developed models, 0.516, 0.623, and 0.684 regression coefficients values were obtained for nonlinear regression analysis, multivariate adaptive regression splines, and artificial neural networks approaches, respectively. The analysis results have determined that the artificial neural networks technique performs more successfully than the other techniques. The statistical error analyses of the root mean square error, Nash-Sutcliffe coefficient of efficiency, mean absolute error, and normalized root mean square error also showed that the same modeling approach performs more successfully. With these data generated from a universally used database, it has been determined once again that ANN is the most efficient mathematical approach in modeling the relationships between surface distresses and IRI.

Laboratory Model Test on The Sand Column for Reinforcement System of Flexible Pavement

Flexible pavement failures in Indonesia are primarily attributed to weak subgrade conditions, necessitating soil reinforcement measures. This study aimed to enhance soil-bearing capacity through soil reinforcement experiments utilizing a mixture of sand columns, rice husk ash, and cement. A prototype was constructed, including a 1×1×1 m steel box, an IWF steel frame, a dial gauge, a steel plate, and a proving ring, to apply a load to soil arranged within the iron box using a 3-ton hydraulic jack. The study focused on a clay soil type (following the AASHTO method) and conducted soil reinforcement in four scenarios. The result shows that in all scenarios involving a sand column, Scenario 1: 3% sand, 3% rice husk ash, and 6% cement obtained a qult is 0.23 kg/cm2 and BCR 114.94%; Scenario 2: 3% sand, 6% rice husk ash, and 3% cement obtained a qult is 0.12 kg/cm2 and BCR 11.49%; Scenario 3: 6% sand, 3% rice husk ash, and 3% cement obtained a qult is 0.14 kg/cm2 and BCR 26.44%; Scenario 4: 6% sand, 6% rice husk ash, and 0% cement obtained a qult is 0.24 kg/cm2 and a BCR of 116.09%. Notably, scenario 4, featuring a column composition of 6% sand, 6% rice husk ash, and 0% cement, achieved a significant increase in bearing capacity (qult) with a value of 0.24 kg/cm2 and a high Bearing Capacity Ratio (BCR) of 116.09%. Scenario 1 was the most effective in reducing moisture content by 4% relative to the original soil moisture content, with a mixture comprising 3% sand column, 3% rice husk ash, and 6% cement. The findings suggest that applying soil columns can enhance the performance of flexible pavements.

A Review Study on the Improving the Hot Mixture Asphalt Properties by Using Different Types of Polymers as Additive for Asphalt Material

By integrating the design of high-performance material with solid structural design, flexible pavement performance can be increased and the service life extended. In the context of creating highways the topic of asphalt polymer modification and the incorporation of polymers in asphalt material by mechanical mixing or chemical reaction, has received substantial scholarly coverage. A wide range of polymers types are used in the method of changing asphalt material and subsequently enhancing hot mixed asphalt. The main objective of this paper is to review prior research on employing polymer materials to develop the qualities of asphalt cement and hot mixed asphalt. This study reviews three different types of polymers. These polymers are Styrene-butadiene-styrene (SBS), polytetrafluoroethylene (PTFE), and polyvinyl chloride polymers (PVC). According to earlier studies in this area, these polymers are elastomers and plastomers that are utilized to enhance the mechanical properties of hot-mix asphalt while also increasing the stability, elasticity, and stiffness of asphalt binders. The overall performance of asphalt pavement can be achieved by reducing the possibility of rutting in the summer and cracking in the winter.

Influence of Different Factors on Permanent Deformation of Hot Asphalt Concrete Mixtures

Abstract The performance of flexible pavements is significantly impacted by the permanent deformation (rutting) of asphalt pavements. The research aims was to evaluate the permanent deformation of asphalt mixtures under different conditions. To achieve this aim, 108 cylindrical specimens have been prepared and tested under repeated loading in uniaxial compression mode. Five factors were considered in this research. They include testing temperature, loading conditions (stress level and duration), and mixture properties (bitumen type and content). The permanent deformation is evaluated in term of the following parameters, permanent micro strain εp, resilient micro strain εr, initial permanent strain (intercept, a), accumulation rate of permanent deformation (slope, b), rate of decrease in permanent deformation α and constant of proportionality between permanent and elastic strains Mu. The test results showed that the εp and a are increased as the testing temperature increased. In addition, the εp value for load duration of 0.4 s is 1.64 times the value for 0.1 s. Finally, the findings showed that the resilient response of the material is comparatively more sensitive to bitumen content than the plastic response. Furthermore, the rutting resistance is highly affected by the variables considered in this research.

Utilization of recycled concrete aggregates for developing high-performance and durable flexible pavements

The objective of this research was to explore the feasibility of using recycled concrete aggregates (RCA) to construct flexible pavements with high performance and durability. The research is based on materials obtained from urban renewal projects in Istanbul, where RCA can be sourced from construction demolition waste. The grain diameter distributions of subbase and base samples, intended for road infrastructure implementation, were established to comply with the AASHTO Pavement Structures Design Guidelines specifications. Laboratory tests were conducted to determine the physical, mechanical, and stiffness properties of subbase and base samples prepared with RCA. In addition, the influence of freeze–thaw (F-T) cycles on the stiffness characteristics of RCA was examined experimentally through resilient modulus and permanent deformation tests carried out on base and subbase samples subjected to a range of 1 to 20F-T cycles. Also, numerical evaluations were undertaken using finite difference numerical modeling software to investigate the mechanical performance of flexible pavements built with RCA under significant loads, utilizing parameters derived after various numbers of F-T cycles. The findings suggest that the stiffness properties of RCA meet the required specifications for subbase and base materials after F-T cycles, indicating that RCA can potentially provide high performance in flexible pavement construction under varying environmental conditions.

Analysis of the Structural Performance of Flexible Pavement Constructed with Timber Raft as a Subbase Layer

Analysis of the Structural Performance of Flexible Pavement Constructed with Timber Raft as a Subbase Layer

Development of high performing hybrid hot mix asphalt mixtures

ABSTRACT In this study, mixture design volumetrics, moisture-induced damage and fatigue characteristics of hybrid hot mix asphalt (HMA) fabricated with crumb rubber (CRM) and polyvinyl alcohol (PVA) fibre were evaluated. Indirect tensile strength test was conducted to assess several tensile and fracture attributes of control, polymer-modified, CRM-modified, PVA-reinforced and hybrid HMA. Long-term performance of aged hybrid HMA was also assessed using flexural beam fatigue test. Comparison of mixture designs indicated a change in volumetric properties of hybrid mixture with acceptable resistance to stripping. Experimental results revealed that fracture energy and dissipated creep-strain energy of the HMA with 2%CRM and 0.2%PVA doubled relative to polymer-modified HMA. The developed hybrid HMA presented around 29 times higher resistance to repeated load failure with 90% reduction in crack propagation rate and over 12 times higher energy for unit crack propagation compared to conventional HMA. Additionally, effective fibre bridging across the crack and adequate coating of asphalt on CRM through image analysis revealed wider strain distribution, a perverse intricate fracture pattern and better adhesion. The higher fracture resistance, toughness indices, and resilience under repetitive traffic loading of hybrid mixtures could be effective in extending the service-life and enhancing long-term performance of flexible pavements.

Evaluation of Airport Pavement Designs for Seasonal Frost and Permafrost Conditions

In recent years, the Alaskan Region of the Federal Aviation Administration (FAA) reported performance issues with some flexible airport pavements. The issues were attributed to changes in the thermal regime of the permafrost layers resulting from a warming trend. The poor pavement performance was also caused by such factors as improper design and construction. The FAA Airport Technology Research and Development Branch selected three runways with an asphalt surface from three airports in Alaska and reviewed the pavement failures, design, and construction histories to determine the causes and contributing factors of flexible pavement performance issues. The goal was to determine if and where modifications to FAA guidance concerning design and construction in frost and permafrost zones were needed. This paper focuses on identifying frost and permafrost issues at the airports, identifying the design criteria used at the airports, and determining how closely the design criteria and construction practices followed FAA guidance. The work also recreates the pavement design for each runway, following FAA guidance in effect at the time of the design. Researchers identified areas of the FAA frost and permafrost design criteria that are silent or subject to conflicting interpretation. The paper provides recommendations for possible improvements to current FAA guidance with respect to frost and permafrost design, based on findings from the design reviews. The recommendations target Advisory Circulars 150/5320-6G and 150/5270-10H and are intended to address the design- and construction-related issues.

Sugarcane Bagasse Fibers for Enhancing Moisture Susceptibility Properties in Stone Mastic Asphalt

Stone mastic asphalt (SMA) mix amended with sugarcane bagasse fibers (SBFs) as a stabilizer was investigated experimentally in the present study. The SBF content in the combination mix was varied (0, 0.15%, 0.30%, 0.45% and 0.60%) to produce different mixtures. The prepared mixtures were then assessed for different properties, such as the Marshall stability, tensile strength, and draindown, which are crucial for the performance of the mix in flexible/bituminous pavements. The experimental results revealed enhanced stability and flow value, greater filling of voids in the bitumen, and reduced air voids in the prepared SMA mix amended with SBF. In addition, improvement in the tensile strength of the SMA mix amended with SBF was observed. An increase in the tensile strength ratio of the amended SMA mix was also observed. The susceptibility to the entry of moisture into the pores of the SMA mix was assessed by performing the draindown test, which revealed that the amended SMA mix exhibited reduced draindown due to the presence of SBF. Therefore, it was inferred that the inclusion of SBF into the SMA mix was beneficial for enhancing the stability and tensile strength of the mix and achieving higher resistance to moisture penetration. The present study demonstrated that the use of sugarcane bagasse as an active ingredient in the SMA mix would result in improved performance of flexible pavements while also reducing the waste burden of landfills and aiding in effective waste management.

Evaluation of the structural performance of the geocell-stabilized flexible pavement

Geocell can provide sustainable solutions for the pavement infrastructure as it allows the utilization of reclaimed and inferior quality base aggregate materials as infill materials. The benefits of using geocell have been well established in the literature; however, lack of knowledge regarding the field performance hinders transportation agencies from designing flexible pavement with such products. This study aims to determine the contribution of geocell towards pavement system performance based on non-destructive field testing. The existing road section of a Farm to Market Road was replaced with different thicknesses of geocell-reinforced base layer filled with reclaimed asphalt pavement (RAP) material. The performance of the reinforced sections was verified with the profiler test and rutting measurements. Falling weight deflectometer (FWD) tests were conducted on different test sections to capture the pavement responses. Field data showed that geocell allowed the maximum usage of RAP material and enhanced its performance. The back-calculated in-situ modulus showed that the additional confinement provided by the geocell ranged between 8 and 20 psi. The increase in confinement indicated an increase in resilient modulus, which was further calculated for each geocell-reinforced section. Geocell also helped to restrict the differential movement of the subgrade by providing uniform support, which resulted in a smoother road structure with less rutting and longitudinal cracking.

High-Temperature Rheological Properties and Storage Stability of Bitumen Modified with the Char Produced from Co-Pyrolysis of Different Wastes

By enhancing the bitumen properties with the additives produced from waste, not only can the performance of flexible pavements be improved, but it can also contribute to the environment. This research aims to produce a novel pyrolytic char from different wastes and to investigate the usability of this char as an additive in bitumen. In this study, first, the pyrolytic char was produced from the co-pyrolysis of three different wastes, including waste paper cups, polypropylene (PP), and polyethylene terephthalate (PET) waste. Properties of the char were determined by using CHN (carbon, hydrogen, and nitrogen) and Fourier transform infrared spectroscopy (FTIR) analyses. The high-temperature rheological properties of binders were evaluated by using DSR (dynamic shear rheometer), RV (rotational viscometer), softening point, and penetration tests. Additionally, specific gravity, storage stability, high-temperature performance grades (PGs), and temperature susceptibilities of binders were determined. Test results showed that this pyrolytic char enhanced the high-temperature properties of neat bitumen by increasing softening point, viscosity, rutting resistance, and high-temperature PG of pure bitumen. Additionally, it can be said that the bituminous binder modified with this pyrolytic char had good storage stability when it was used at an 8% ratio in neat bitumen.

Effect of different platoon configurations on strains and fatigue performance of flexible pavements

This paper presents part of the studies developed in the European project ENSEMBLE. (ENabling SafE Multi-Brand pLatooning for Europe). The first part of the paper describes the validation of a numerical model based on comparisons with experimental results obtained from a test section subjected to the pass of 3 human-driven trucks simulating a platoon configuration. The numerical model is then used to predict the maximum and accumulated strains produced by the passage of each truck on the same test section at two different temperatures when the following platoon parameters are varied: (1) inter-truck time gap, (2) truck speed and (3) lateral deviation (wandering). The results confirm that the proper control of these parameters can help to keep the same level of fatigue damage as with trucks in individual configurations. In this way, the environmental, social and economic benefits of platooning can be attained without compromising the existing pavement structures.

Ultrasonic characterisation of the elastic properties of mineral aggregates used in asphalt mixtures

Mineral aggregates are the main constituent of asphalt mixtures by volume, having a significant influence on the performance and durability of asphalt materials and flexible pavements, but their elastic stiffness properties are rarely investigated in the scientific literature. Nevertheless, these properties represent important input to micromechanical models which are aimed at providing a better understanding of the behaviour of asphalt mixtures as the basis for optimising their design. Herein, the elastic properties of 55 cylindrical specimens representing six types of rock from two quarries are investigated using ultrasonic testing, in order to assess the variation of the results between different rock types and between different samples of the same rock type as well as the sensitivity to specimen length (50–150 mm) and frequency (0.05–5.00 MHz). Most of the elastic stiffness values of the investigated rocks are found to be larger than stiffness values frequently used as input to micromechanical models.

Temporal and spatial temperature predictions for flexible pavement layers using numerical thermal analysis and verified with large datasets

The pavement temperature patterns play a significant role in the performance of flexible pavements containing asphalt concrete surface layers for several reasons. Since asphalt concrete behaves as a viscoelastic material at medium to high service temperatures, the structural response of the pavement is affected by the temperature history and the magnitude and duration of the wheel loads applied on the pavement. Therefore, predicting the pavement temperature patterns in a scalable manner (i.e., daily, seasonal, annual) is vital for a more accurate simulation of pavement response and performance, particularly the permanent deformation (rutting). This can result in more effective pavement designs. A numerical model was developed in this paper to predict the temperatures in asphalt layers by using the heat transfer theory and the Finite Element method with the help of proprietary software. A model that can predict the pavement temperatures continuously for one year covering all four seasons at time intervals that allow pavement distress prediction for each axle load cycle and calibrated with high-quality measured data is the main contribution of this study. Among the parameters that significantly affect pavement temperature prediction, the convective heat transfer at the air-pavement interface is of utmost importance. Therefore, the Convection Heat Transfer Coefficient (CHTC) for the air-pavement interface was also selected as an exploratory focus area for this paper. Two approaches were used to estimate the CHTC needed for the heat-transfer model. An error analysis was conducted to assess the accuracy of the pavement temperature prediction by using a large, measured dataset from a field test. The error of temperature predictions for the whole year was found to be minimum when the value of CHTC was equal to 21 W/(m2K). The error observed in winter predictions with the wind speed model of CHTC was minimized when a constant value of 60 W/(m2K) was used for CHTC. The significance of the convective heat transfer component in the FE model was identified through the improvements obtained by adapting the value of CHTC. Correlation analysis also identified a connection between the prediction error and relative humidity. Further research is underway to improve the temperature prediction model using additional parameters (i.e., relative humidity, cloud cover) and more refined data analytics approaches.