Superpave Mixtures Research Articles

Mechanistic Pavement Modeling of Typical Brazilian Pavements: Cohesive Zone Fracture Modeling and Continuum Damage Modeling

Pavement performance evaluation with respect to fatigue cracking has seen a major shift toward more rigorous mechanistic models that can capture the complex damage response of the mixtures more accurately. This study utilized two mechanistic methods (cohesive zone [CZ]-based fracture modeling and continuum damage [CD] modeling) to study the cracking behavior of asphalt mixtures and subsequently predict the damage-associated performance of pavements. A Superpave mixture designed for Brazilian highway conditions was selected to evaluate the two modeling approaches for the performance of the mixture when utilized as a surface course within typical Brazilian highway pavements. The mixture was first evaluated for its linear viscoelastic properties, and then the damage characteristics of the mixture were obtained through two different experiments: the semi-circular bending (SCB) beam test and the cyclic fatigue (CF) test. The SCB tests performed at different loading rates were used to obtain the model parameters of the nonlinear viscoelastic CZ model with a Gaussian damage evolution criterion, while the CF tests were performed at different strain amplitudes, and the mixture-specific damage characteristic curve and the fatigue failure criterion were obtained using the simplified-viscoelastic continuum damage model. From a design perspective, three pavement structures that varied in geometry (pavement layer thickness) and underlying layer properties were selected while retaining the same asphalt mixture. The three pavement scenarios were evaluated for the fatigue cracking performance from each of the mechanistic modeling methods. The results indicate that both methods rank the performance of the pavement structures in a similar manner, while the damage initiation and progression were seen to be different because of the different mechanics in modeling cracks.

Impact of Clay Contamination on Rutting Performance of Asphalt Mixtures

Natural sands improve the sustainability of asphalt mixtures by enhancing workability and lowering the required asphalt binder and manufactured fine aggregates. One of the primary concerns with incorporating natural sands in a mixture is the potential for clay contamination. Harmful active clays swell when in contact with moisture and diminish the bonding between the aggregate and asphalt binder. This paper investigates the impact of clay contamination on the performance of asphalt mixtures with respect to rutting and moisture susceptibility. Twenty-one combinations of passing no. 200 sieve (minus 0.075 mm) material with various contamination levels were prepared using inactive (i.e., calcium carbonate and dolomite) and active (i.e., bentonite and natural) clays. The methylene blue value (MBV) was used to classify the level of chemical activity of those combinations. Each of the 21 permutations was added to a reference Superpave mixture to produce asphalt mixture specimens. The rutting and moisture susceptibility of each mix were then evaluated by subjecting them to Hamburg wheel tracking tests. X-ray diffraction (XRD) was also used to characterize the mineral composition of the inactive and active clay materials used for this study. The experimental results showed that mixtures having a MBV above 6 mg/g are most likely to suffer rutting and moisture damage. Moreover, XRD testing corroborated that the active clays used in this study contained detrimental minerals to asphalt mixture performance, such as sulfuric acid, quartz low, and microline.

Marshall Asphalt Mix and Superior Performance Asphalt Mix in Oman: A Comparative Study

The mix design procedure used in Superior Performance Asphalt Pavements (Super-pave) was created by the Strategic Highway Research Program (SHRP) in response to the limitations and empirical approach of Marshall methodology. This study aims to compare the Marshall asphalt mixture design method with the Super-pave asphalt mixture design procedures. Locally available aggregates commonly used in asphalt concrete mixtures in Oman were used. The asphalt mixtures were made with aggregate and asphalt-binder with a penetration grade of 60/70 and PG 64-10. Samples from two mixes were made accordingly. Volumetric properties analysis, flow, Marshall stability, and loss of Marshall stability tests were carried out. According to the study findings, the optimum asphalt composition was 4.5% when utilizing the Marshall methodology and 5.5% when using the Super-pave approach. Furthermore, the Super-pave specimens showed less loss of Marshall stability (22.22%) than the Marshall specimen (30.09%).

Adaptive construction approach for virtual samples of hot mix asphalt based on 3-D structural characterization of laboratory compact specimens

Marshall and Superpave gyratory compactor (SGC) methods are widely applied in pavement engineering. Laboratory samples derived from the two methods have great difference in aggregate structure, which should be adequately characterized and considered to generate virtual samples of Marshall and Superpave mixture. To characterize the aggregate structure in realistic samples of asphalt mixture, six laboratory-compacted samples, three Marshall and three SGC, are prepared under SMA-13 gradation and then three-dimensionally (3-D) reconstructed. Next, the statistical indicators of the aggregate structure are extracted, analyzed, and characterized to develop an algorithm for adaptive construction of virtual samples conforming to the structural characteristics of realistic samples. Four virtual samples, two Marshall and two SGC, are generated to verify the control effect of the proposed approach on the aggregate structure to simulate the internal structure of realistic samples. Results indicate that virtual samples capture close structural characteristics with laboratory samples of Marshall and SGC, which validates the effectiveness of the proposed approach.

Investigating the Superpave Mixture Design Approach for Hot-Mix Asphalt in Kazakhstan

The purpose of this research was to assess the feasibility of constructing high-performance paving (Superpave) for Kazakhstan with only locally sourced ingredients. Similarly, a standard Marshall technique combination that meets the technical requirements of Kazakhstan was compared. One granite aggregate supplier, 2 aggregate grading, and 2 types of asphalt binder made up the test design. Consensus and source aggregate characteristics requirements met with the Superpave design mix method using locally manufactured granite aggregate. Also, the mixtures volumetric parameters indicated that the asphalt binder content of the superpave combination has shown lower than locally-traditionally Marshall mix. The combinations of Superpave fared better in rutting and moisture resistance tests than those made in the conventional manner. After the ITS values from both samples were averaged, the decrease in significance for the superpave mixtures was 9.1%. It was below the 20% loss level required by the Superpave guidelines. Also by rutting resistance results were significantly differences for 85.5% PG70 with 9.5mm NMAS. All of these results point to the superiority of new method Superpave over the Marshall method.

Experimental investigation of superpave mixtures for optimum and rich mixes

Population growth and economic status in the nation lead to improved infrastructure, and thereby, the number of commercial vehicles on the road increases, leading to the early deterioration of pavement layers. The structural failures of the pavement demand rehabilitation and reconstruction of the pavement layers, leading to significant construction costs. The distress in the pavement layers observed can be minimized by using superpave mixtures. This paper compares the volumetric and mechanical properties of optimum and rich superpave mixes using viscosity grade (VG) 40 as the binder. Nominal maximum aggregate sizes (NMAS) of 25 mm and 19 mm, abbreviated as G1 and G2, respectively, were used. The mechanical properties, including fatigue test, Indirect Tensile Strength (ITS), and moisture susceptibility, were performed on both optimum and rich mixes, and a comparative analysis of mixes was done. G1 graded mixes showed better performance in all aspects compared to G2. Rich mixes were observed to have more fatigue resistance than the optimum mixes, while optimum mixes have better ITS.

High-compactability asphalt mix design framework based on binary aggregate packing

High compactability is desired for asphalt mixtures to ensure adequate field density and, therefore, the overall quality of asphalt pavements. However, compactability is typically not considered in standard mix design procedures, and existing methods for improving compactability are largely empirical. This paper proposes a mix design framework that considers the compactability of mixtures, anchored by a rational method to adjust aggregate gradation. The method is developed based on the binary aggregate packing model. The proposed mix design is applied to modify four traditional Superpave mixtures into high-compactability mixtures, to demonstrate the concept. The proposed method is compared with two empirical methods used to adjust aggregate gradation: the maximum density line (MDL) and the Bailey method. The results show that the proposed method provides a theoretical explanation of the two empirical methods and reveals their limitations. Mechanical properties related to rutting resistance, low-temperature cracking, and structural capacity of the mixtures are checked by laboratory performance tests to validate the high-compactability mix designs. The results show that, due to their denser aggregate packing, the high-compactability mixtures outperform the traditional Superpave mixtures. Therefore, the proposed high-compactability mix design framework provides a rational and practical approach to improve the field density and the overall quality of asphalt pavements.

STUDI KOMPARASI PREDIKSI UMUR PELAYANAN ANTARA CAMPURAN SUPERPAVE DAN AC-WC MENGGUNAKAN PERMODELAN VISKOELASTIK DAN ELASTIK

The performance of a pavement depends on a load of passing vehicles; in anticipation of these problems, alternative solutions are needed. One solution is using a Superpave mixture as a type of pavement. Previous studies concluded that the Superpave mixture performed better in receiving or distributing vehicle loads and resistance to submersion conditions. However, to strengthen this opinion, exploring it from another point of view is necessary. One of them is the mechanistic-empirical analysis of the KENPAVE program, which is needed to determine the prediction of service life. In this study, the AC-WC mixture was used as a comparison. The analysis started by calculating the stiffness modulus value for both types of pavements, determining the alternative pavement design plans to be applied using Bina Marga 2017 method, and ending the mechanistic-empirical analysis process using two modeling forms, namely viscoelastic and elastic. As a result, the Superpave mixture has a relatively higher predictive value of service life compared to the AC-WC mixture. This result applies to both the viscoelastic and elastic models. Suggestions for using an alternative with Bina Marga 2017’s design chart 3-B on FFF7 criteria are given regarding maximizing the performance of the Superpave mixture in the field. The mechanistic-empirical analysis of the design alternative shows that the predicted service life is above the 20-year design age limit, which is 30.7 years in the viscoelastic model and 40.9 years in the elastic model before the prediction of the first damage.

Evaluation of the Validity of a Minimum VMA Requirement in Superpave Mixtures

Evaluation of the Validity of a Minimum VMA Requirement in Superpave Mixtures

Permanent deformation of dry and wet asphalt mixture contained crystalline waterproofing additives

This study was conducted to investigate rutting performance of asphalt mixture containing few percent of CWA as an additive. In total, four different asphalt mixture containing 0%, 50%, 75% and 100% crystalline waterproofing additive (CWA) replacement from the total weight of filler were tested. The asphalt mixture NMAS 12.5 were prepared based on Superpave mixture design method. The rut depths of dry and wet asphalt mixture samples were measured using wheel tracking test machine and compare with control samples. The result show that rut depth of wet asphalt mixture containing 100% CWA is the lowest compare to other samples. In conclusion, replaced the asphalt mixture filler with CWA can improve it resistance to rutting compare to control sample.

Development of Cost-Effective High-Modulus Asphalt Concrete Mixtures Using Crumb Rubber and Local Construction Materials in Louisiana

One of the emerging solutions to enhance the durability of asphalt pavements is the use of a French asphalt mix known as “High-Modulus Asphalt Concrete (HMAC).” This mix uses a hard asphalt binder, high binder content (about 6%), and low air voids content as compared with Superpave mixtures. The key objective of this study was to develop a cost-effective HMAC mixture using crumb rubber and local materials in Louisiana. To achieve this objective, four HMAC mixtures were prepared using two asphalt binders (PG 82-22 and PG 76-22 plus 10% crumb rubber) and two Reclaimed Asphalt Pavement (RAP) contents (20% and 40%); additionally, a conventional Superpave mixture in Louisiana was prepared as a control mixture. The laboratory performance of these five mixtures was evaluated in relation to workability, dynamic modulus, rutting resistance, and cracking resistance. The AASHTOWare Pavement ME Design software was also used to estimate the long-term field performance of these mixtures. Results indicated that the HMAC mixture prepared with 10% crumb rubber and 20% RAP successfully met the French mix design specifications for HMAC and LaDOTD specifications. This HMAC mix outperformed the control Superpave mix in relation to dynamic modulus, rutting resistance, and cracking resistance. Additionally, this HMAC mixture can reduce the required asphalt thickness by 1.5 or 2 in. based on traffic level. The cost-effectiveness analysis indicated that this HMAC mixture was more cost-effective than conventional Superpave mixtures in Louisiana. In addition, this mixture is environmentally friendly as it can reduce the disposal of scrap tires in landfills.

Optimizing asphalt mix design through predicting effective asphalt content and absorbed asphalt content using machine learning

Superpave mix design procedure is still empirical. Random and lengthy trials in a laboratory during the design procedure can consume immense manpower and materials resources. To simplify and accelerate the Superpave mixture design procedure, this study explored the use of machine learning models to achieve an automated and timesaving mix design method through predicting effective asphalt content (Pbe) and absorbed asphalt content (Pba). Five different machine learning (ML) algorithms including Support vector regression (SVR), bagging with ridge regression, Random Forest, Adaptive boosting (AdaBoost), and Gradient boosting were trained. The inputs related to mixture design include aggregates gradation, the bulk specific gravity of aggregates, blend absorption, air void, PG grade of the asphalt binder, and the number of gyrations (Ndes). The kernel density estimation was used to detect outliers of the datasets. The effect of different methods used to encode PG grade, which is categorical variables, on the performance of ML models was analyzed. The performances of ML models were evaluated by calculating different performance scoring metrics, such as coefficient of determination (R2), root means square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). The improved mix design procedure based on an ML model was proposed. The result showed that compared to other encoding methods, the ordinal encoding method used to encode the variables of PG grade can achieve the best performance of ML models. The Gradient boosting algorithm (R2 = 0.9479, 0.9459) was found as the best estimator to predict the Pbe, and Pba, respectively, compared with those obtained by other machine learning models. Furthermore, determining Pb through predicting Pbe and Pba indirectly with ML models was more accurate than predicting Pb directly with ML models. Therefore, the Gradient boosting model was used in the improved mix design procedure. A case study was implemented to verify the feasibility of the proposed mix design method. The gradation and the optimal asphalt content obtained from the proposed method with the Gradient boosting model was consistent with that obtained by the traditional Superpave method with laboratory tests.

SUPERPAVE design mixture performance evaluation using Epolene modifier for cold semi-arid climatic region of Saudi Arabia

Purpose: To evaluate the superpave design performance using Epolene (EE-2) as modifier, since SUPERPAVE design is a modified and sophisticated aspect as compared to previous mix design for asphalt mixtures. This is primarily due to the fact that superpave design mix also takes into consideration properties of materials beside asphalt. Design/methodology/approach: This study was conducted using Epolene (EE-2) as modifier in order to evaluate the performance of SUPERPAVE suitability for construction of roads in Alfaraa campus (King Khalid University) Abha, in Asir Province of Saudi Arabia. Glow number test, dynamic modulus test and indirect tensile strength test were conducted to evaluate the performance of EE-2 modifier against the control mixture. Findings: The mixture modified with EE-2 gave better performance in terms of temperature-based performance and resistance to moisture damage. Also, larger values of E*/sinφ were obtained for EE-2 modified mixture at various loading frequencies and temperature in comparison to control mixture. Research limitations/implications: The Epolene modifier successfully enhances and improves the SUPERPAVE mixture performance. Further studies are required to evaluate the performance of EE-2 modifier at much lower temperature ranges. Practical implications: The results of the study allow us to recommend the investigated asphalt mixture for applied for the construction of roads in the Alfaraa (new campus of King Khalid University), Abha, Asir province, Saudi Arabia. Originality/value: A modified asphalt mixture has been proposed that has better performance at higher and lower temperatures. The developed asphalt mixture is more resistant to moisture damage than the compared to control mixture.

Comparative Study of Marshall Properties and Durability of Superpave and AC-WC Pavement by Using Starbit E-55 and Pen 60/70

The challenges in high traffic volumes, excessive loads and environmental problems need to be anticipated through modification of pavement materials, both for gradations as well as for binding materials. This paper presents a comparative study of Marshall characteristics and its durability between Superpave and AC-WC graded mixtures using Starbit E-55 and Pen 60/70. The experimental laboratory begins with physical testing of aggregate and bitumen material, then, determination of optimum bitumen content for each of the mixture was conducted, and Marshall Standard and Index of Retained Strength (IRS) at optimum bitumen content were then run. Results show that in general Superpave mixture with Starbit has a significantly better Marshall performance in terms of its stability and Marshall Quotient, however, its volumetric properties, such as void in total mix, void filled with asphalt and density were slightly lower quality than AC-WC. It also has proven that Starbit E-55 gives a significantly better mechanical performance on Superpave mixture rather than on AC-WC, with only a slightly lower volumetric quality. Superpave mixtures tend to have a more durable performance then the AC-WC mixture. It also has been found that Starbit E-55 generates a more significantly durable mixture of Superpave rather than on AC-WC.

Novel Model to Predict Critical Strain Energy Release Rate in Semi-Circular Bend Test as Fracture Parameter for Asphalt Mixtures Using an Artificial Neural Network Approach

Growing use of recycled asphalt materials in asphalt pavement means the current volumetric-based Superpave mixture design may not address durability concerns arising from replacement of a proportion of virgin binder with recycled ones. To address this limitation, performance-based testing is introduced to supplement conventional volumetric mixture design in assessing cracking performance of asphalt mixtures. Louisiana Department of Transportation and Development’s Specifications for Roads and Bridges specify a criterion for the critical strain energy release rate, Jc, obtained from semi-circular bend (SCB) test as a complement of current practice to evaluate cracking resistance of asphalt mixtures. Quality control/assurance practices, however, require SCB samples to be long-term aged for five days at 85°C, which is a time-consuming process. Therefore, it is beneficial to be able to estimate SCB Jc for long-term aged asphalt mixtures based on SCB Jc measured from plant-produced asphalt mixtures. Asphalt mixture aging is complex, and various variables are involved in the aging process, including volumetric properties of asphalt mixture and chemical/rheological characteristics of asphalt binder. With the capability of artificial neural network (ANN) to address complex relationships between input and output variables, this study aims to predict the fracture parameter, SCB Jc, of asphalt mixtures using ANN. A total of 34 asphalt mixtures were selected for this study. SCB fracture test and asphalt binder tests for chemical and rheological characterization were conducted. Stepwise regression analysis was used to determine the significant parameters in the correlation with SCB Jc. With determined significant parameters, ANN using the gradient descent backpropagation approach was then applied to develop and validate the predictive model. It was shown that the developed ANN model was able to predict the fracture parameter, SCB Jc, of asphalt mixtures more accurately than linear and non-linear regression models.

A mixture design approach for mitigating cracking issue of asphalt concrete pavement

The traditional Superpave mixture (SP4) is designed at 4.0% air voids while the mixture is compacted at 7%-8% air voids in the field with the belief that the pavement will achieve its ultimate density after several years. Several studies have reported that the maximum density that a pavement can achieve is about 94%. This higher air voids provide an easy pathway for air into the pavement, which eventually accelerates the aging process and results in premature cracking of the pavement. To this end, this study provides an enhanced mixture design approach in which mixture will be designed at 5% air voids (SP5) and compacted at the same air voids in the field so that the higher in-place density will enhance the fracture strength of the mixture and minimize the aging process. First, the traditional SP4 mixture design has been completed using two different aggregates and binders. Then, the SP5 mixture design is accomplished by reducing the design number of gyrations from 100 to 55 and adjusting the aggregate gradation while keeping the effective binder content the same as SP4. The laboratory Hamburg Wheel Tracking Device (HWTD) and Semi-Circular Bending (SCB) tests have been conducted to evaluate the rutting and fracture properties of the SP4 and SP5 mixtures. In addition, Thermal Stress Restrained Specimen Test (TSRST) has also been conducted to observe the low-temperature cracking performance of the SP4 and SP5 mixtures. The HWTD test results reveal that the SP5 mixture has equal or better rutting resistance properties than the SP4. Based on the fracture energy obtained from SCB test data, the SP5 mixtures exhibit better-cracking resistance than that of SP4 mixtures, which implies that the SP5 mixture will delay in crack initiation and propagation. The TSRST test results show that the SP5 mixture has improved low-temperature cracking property compared to the SP4 mixture. Therefore, the SP5 mixture design procedure will mitigate the cracking issue of asphalt concrete pavement.

Variability of Reclaimed Asphalt Pavement (RAP) Properties within a State and Its Effects on RAP Specifications

Reclaimed Asphalt Pavement (RAP) is a highly recyclable material that provides a source of aggregates and asphalt binder to be re-utilized in new paving mixtures. State transportation agencies in the U.S. have constructed their specifications to allow for the use of RAP in new paving mixtures, but with conditions so that suitably performing mixtures are developed. These conditions are imposed because of concerns that the aged binder contained within the RAP may negatively impact the resultant mixtures performances. Many state transportation agencies have constructed their specifications with respect to the AASHTO guidance on utilizing RAP in Superpave mixtures. Questions remain as to the accuracy of these methods, especially if the RAP stockpiles’ properties vary greatly. The purpose of this study was to characterize and compare the properties of the RAP stockpiles being used throughout Massachusetts and to determine the impacts that these properties have on the currently utilized specifications for RAP. The properties of the RAP stockpiles within Massachusetts varied greatly. No geographical or regionalization of RAP properties could be made. By default, the current specifications for using RAP makes no distinction between RAP stockpile properties, especially at smaller percentages like <15% or at low RAP binder ratios (RAPBR). The data from this study demonstrated that this could lead to mixtures without the appropriate virgin binder grade and therefore they could exhibit subpar performance. Specifications should be revised to require more thorough testing of RAP for each mixture design, regardless of the allowable percentage or RAPBR, to ensure adequate mixture performance is maintained.

Effect of Recycled Concrete Aggregate on Rutting and Stiffness Characteristics of Asphalt Mixtures

AbstractThis study aims to evaluate the influence of the addition of coarse recycled concrete aggregate (CRCA) on the rutting and stiffness of Ontario Superpave mixtures. Mix designs of asphalt mix...

Understanding the Illinois Flexibility Index Test (I-FIT) using Indiana Asphalt Mixtures

Asphalt mixture cracking has become the dominant type of asphalt pavement distress in Indiana. In recent years, efforts have shifted away from the standard Superpave mixture design method in search of methods to improve the resistance of asphalt pavements to cracking-related distress. This paper presents a review of the applicability of the Illinois Flexibility Index Test (I-FIT) to evaluate the cracking potential of Indiana asphalt mixtures. In this study, two cracking indices were compared: the flexibility index (FI) and the cracking resistance index (CRI), both derived from the load-displacement curve. The applicability of quality assurance (QA) tests of laboratory-compacted and field-compacted samples was also explored to evaluate the cracking potential, and I-FIT was investigated for its applicability as a performance-related quality control (QC)/QA test. The results show that the FI values obtained from field-compacted samples were consistently higher than those of the lab-compacted samples. Both the FI and CRI values were significantly affected by variations in specimen thickness and air void content, with higher FI values observed with an increase in the air void content and a decrease in specimen thickness. The CRI values were less sensitive to I-FIT variability and more repeatable compared to the FI values. Finally, as an illustrative example, the cumulative distribution function of the FI values for a population of asphalt concrete (AC) mixtures was used to establish the different ranges for the quality thresholds of the materials.

Fracture Behavior Analysis of Semi-Circular Bending Test

The objective of this paper is to investigate the effect of air voids on the fracture properties of asphalt mixtures using SCB test in Discrete Element Method (DEM). Superpave and Coarse Matrix High Binder (CMHB) mixtures gradation were used to generate the percentages of aggregate, mastic, and air voids within the specimens. Aggregates and air voids were randomly generated for each asphalt mixture case. Model results illustrate that the crack initiation and propagation is controlled by the location of the aggregate particles and air voids in the mixture. Additionally, the absence of air voids above the tip of the notch increases the stiffness of the sample and increase its resistance to failure. The novelty of using DEM and the random generation technique for generating numerical specimens proved to be a useful approach in investigating the properties of the mastic, aggregate and interface as they relate to fracture of asphalt mixtures.