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In order to further explore the performance of mixture with waste tire rubber (WTR) and amorphous poly alpha olefin (APAO) modified asphalt, the 12%WTR+4%APAO and 15%WTR+4%APAO modified asphalt mixtures were selected as research objectives. The asphalt mixtures with matrix asphalt, WTR modified asphalt, and SBS modified asphalt were prepared for comparative analysis. Through the mixture design, the optimum asphalt-aggregate ratio of five asphalt mixtures was determined respectively. The volumetric parameters and resilient modulus were studied. The laboratory performances were studied by standard Marshall stability test, wheel tracking test, immersion Marshall test, freeze–thaw splitting test, indirect tensile strength test, indirect tensile fatigue test, and Marshall stability after long-term aging test. Compared with the other three asphalt mixtures, the results showed that the 12% WTR+4%APAO modified asphalt mixture had the highest Marshall stability and high-temperature performance. While the 15% WTR+4%APAO modified asphalt mixture had better permanent deformation resistance at high temperatures, moisture stability, aging resistance, and relatively good fatigue performance. The statistical hypothesis test results also confirmed that WTR/APAO modified asphalt has a significant effect on mechanical properties. Based on the results of various performance, the 15% WTR+4% APAO was the optimal content for asphalt mixture. [ABSTRACT FROM AUTHOR]

• WTR/APAO modified asphalt was applied to the stress-absorption interlayer. • Physical, durability, shear resistance, reflection cracking resistance were investigated. • OT and Paris' Law were used to evaluate the reflection cracking resistance of the stress-absorption interlayer. Stress-absorption interlayer (SAI) is one of the most important methods to prevent reflection cracking. This paper analyzed the properties of SAI with the waste tire rubber (WTR) and amorphous ploy alpha olefin (APAO) complex modified asphalt binder. Research found that WTR/APAO modified asphalt works excellently as a binder in SAI. The SAI with base asphalt, WTR/APAO, WTR and SBS modified asphalt mixture were prepared for comparative analysis. The mechanical properties and durability of four SAIs were determined using Marshall stability, Indirect tensile (IDT) strength, immersion Marshall and Marshall stability after aging procedure. The bond strength and shear resistance of three SAIs with modified asphalt were determined using slant shear tests under different conditions. The overlay tests (OT) were used to characterize the fatigue and anti-reflection cracking performance. Besides, the Paris' Law was used to characterize the fracture properties based on OT. Research found that WTR/APAO SAI had the strongest high temperature stability, deformation resistance, bond strength and shear resistance. WTR/APAO and SBS SAIs had excellent water stability and anti-aging performance. WTR/APAO SAI had the highest bond strength at both high and normal temperatures. The OT number of cycles of all three SAIs reached 1200 times. This indicator showed that all three SAIs had excellent fatigue and anti-reflection cracking performance. Further research found that the fracture properties n in Paris' Law showed that WTR/APAO and SBS SAIs had better cracking resistance. The addition of APAO improved the cracking resistance of WTR SAI. [ABSTRACT FROM AUTHOR]

• The aging resistance of WTR/APAO modified asphalt and asphalt mixture were investigated. • The evaluation indexes of the effect of long-term aging on performance was proposed. • The incorporation of WTR and APAO improves the resistance of asphalt to long-term aging. • The high and low temperature performance of 15%WTR + 4%APAO asphalt mixture after long-term aging are better than SBS asphalt mixture. The aging resistance of asphalt mixture has an important impact on the long-term quality and service life of asphalt pavements. This research aims at studying the effects of long-term aging on waste tire rubber (WTR) and amorphous poly alpha olefin (APAO) modified asphalt binder and mixtures. The prepared compounds included, 12%WTR + 4%APAO and 15%WTR + 4%APAO modified asphalts, were used as experimental objects. Base asphalt binder (70 penetration grade), 15%WTR modified asphalt and styrene–butadiene-styrene (SBS) modified asphalt were the reference objects. First, pressure aging vessel (PAV) and long-term oven aging (LTOA) were used to simulate the long-term aging of asphalt binder and mixture, respectively. Secondly, the performance tests of asphalt binder and mixture were carried out, and the evaluation indexes of the effects of long-term aging on performance were proposed. For the asphalt binder, the results show that the incorporation of WTR and APAO significantly improves the post-aging conventional properties, rheological properties and fatigue properties. The Fourier transform infrared spectroscopy (FTIR) results were found to correlate to the physical tests results. In the asphalt mixture part, the results show that 15%WTR + 4%APAO modified mixture has better high temperature and fatigue performance after aging, among the rubber-based asphalt mixtures. The low-temperature performance of WTR/APAO asphalt mixture was not compromised after aging. Compared with the SBS modified asphalt mixture, the high and low-temperature performance of 15%WTR + 4%APAO asphalt mixture after aging are better. Overall, 15%WTR+4% APAO asphalt mixture has better advantages to counteract the influence of oxidative aging. [ABSTRACT FROM AUTHOR]

This paper evaluates the influences of variations in asphalt mixture parameters during construction on the variations of pavement performance using back-propagation (BP) neural networks. The variations of gradation (V G) and asphalt-aggregate ratio (V R a) were assessed through a variability analysis. The influences of V G and V R a propagation were analyzed via BP neural networks and a sensitivity analysis. A reliability assessment was conducted to evaluate the joint effects of V G and V R a. Results illustrate that the V G and V R a during transportation are more severe than those during other processes. BP neural networks can precisely and robustly trace the influences of the V G and V R a. Pavement performance exhibits greater sensitivity to V R a and V G at sieve sizes of 0.075 mm and 2.36 mm. The joint effects of V G and V R a significantly degrade permanent deformation more than fatigue life. High-quality paving effectively mitigates the negative impacts of segregation during transportation. [Display omitted] • Variations of gradation (V G) and asphalt-aggregate ratio (V R a) are more severe during transportation. • BP neural networks effectively trace the fluences of V G and V R a on pavement performance. • The joint effects of V G and V R a degrade permanent deformation more than fatigue life. • High-quality paving mitigates segregation impacts during transportation. [ABSTRACT FROM AUTHOR]

Excessive and unregulated stacking of iron ore tailing (IOT) has created numerous environmental issues, which has drawn considerable attention to focus on the resource utilization of IOT. The present study attempts to investigate the feasibility of IOT as a filler alternative compared to limestone filler, from the perspective of asphalt mastic. To achieve that, the physical and chemical properties for two types of fillers (IOT and limestone) were tested by the laser particle size analyzer, X-ray fluorescence as well as scanning electron microscopy. Four filler/asphalt weight ratios (0.6, 0.8, 1.0, 1.2) were then selected to prepare asphalt mastics. The rotational viscosity test, temperature sweep test as well as multiple stress creep recovery test were conducted to assess the high-temperature performance for asphalt mastics. Furthermore, environmental and economical aspects were evaluated by the leaching toxicity and cost-benefit analysis. Results show that the IOT possesses a smaller particle size and larger specific surface area than the limestone, which contributes to the adsorption of asphalt on the particle surface. As for asphalt mastics, the replacement of filler by IOT can greatly enhance the viscosity, rutting factor as well as percentage of elastic recovery, and significantly reduce the non-recoverable creep compliance. Further, IOT has no risk of large-scale use as building material based on the leaching results, and considerable economic benefits (benefit-cost ratio >1) can be obtained from the utilization process. Consequently, IOT has a promising potential as an environment-friendly filler to replace the mineral filler in asphalt mixture in view of the pavement performance and environmental aspects. [Display omitted] [ABSTRACT FROM AUTHOR]

• A new perspective considering filler distribution was provided in micromechanical modeling of asphalt mastic. • Three viscoelastic micromechanical models of asphalt mastic were improved. • The effects of various parameters on the distribution of the shear modulus ratio were investigated. • The improved models can determine the spatial distribution characteristic of effective properties for asphalt mastic. • A key dimensionless diameter that has a significant effect on effective shear modulus of asphalt mastic exists. This study aims to provide a new perspective into the consideration of filler distribution characteristic in micromechanical modeling of asphalt mastic through combining fractal microstructure. To do this, three viscoelastic micromechanical models were improved by the preliminarily combination between micromechanical equivalence and fractal statistic principles. Particle size distribution (PSD) of filler was tested by a laser particle size analyzer. Asphalt mastics with different filler concentrations were fabricated. Dynamic shear moduli of asphalt and asphalt mastics was tested by a dynamic shear rheometer. The PSD of the circles intercepted by the plane and dimensionless area of the intercepted asphalt matrix were analyzed. The dynamic shear modulus ratio of asphalt mastic to binder were calculated based on the improved models. The effects of various parameters on the distribution of the ratio were investigated. Results show that the shifted R-R distribution function is capable of capturing the PSD of filler. The dimensionless area increases with increasing dimensionless diameter, but decreases with increasing filler volume fraction. The shear modulus ratio shows a three-stage reduction trend with dimensionless diameter, replying that the shear modulus of asphalt mastic appears as a random distribution in space. Meanwhile, the spatial distribution is influenced by filler volume fraction and thus there has difference between the stiffening effects of filler on various local regions in asphalt mastic. Poisson's ratio of binder plays an enhanced role in the stiffening effect of filler, which is affected by the spatial locations within asphalt mastic. Modulus and Poisson's ratio of limestone filler and modulus of binder have little effect on the distribution of the shear modulus ratio. The combination of micromechanical modeling and fractal characteristic is capable of determining the spatial distribution characteristic of effective properties for asphalt mastic. The local homogenization of asphalt mastic in terms of the modulus and its influence on properties of asphalt mixture should be focused on and conducted in future. [ABSTRACT FROM AUTHOR]

• A novel methodological framework analyzing critical property of asphalt mastic was developed. • A novel method to calculate filler critical volume fraction was established. • Transformation from volume-based into number-based distribution functions for filler particles was conducted. • Nearest surface distance of filler particles in asphalt mastic was estimated through nearest surface functions. • Filler critical volume fraction of asphalt mastic under different temperatures was computed. This study aims to provide a new insight into the reinforcement effect of filler on stiffness of asphalt mastic through the probability theory, nearest surface function and micromechanics. To implement the consideration of microphysical mechanisms in the stiffening behavior of asphalt mastic composite, a general methodological framework was developed. A new method to calculate the filler's critical volume fraction (CVF) in asphalt mastic was constructed through the volume fraction of penetrable transition zone (PTZ) acting as a link. Particle size distribution (PSD) of filler was tested by a laser particle size analyzer. Asphalt mastics were fabricated with different filler concentrations. Distributions of filler particles in these mastics were tested by a scanning electron microscope. Complex stiffness moduli of asphalt binder and mastics were tested by a dynamic shear rheometer. Nearest surface distance (NSD) of filler particles in asphalt mastics was analyzed by nearest surface functions. Filler's CVF in asphalt mastics was calculated through the constructed method. Results show that the shifted Rosin-Rammler distribution function allows to describe the PSD of filler with a high accuracy. Void nearest-surface exclusion probability of filler particles allows to represent the volume fraction of free asphalt in asphalt mastic. The larger the filler volume fraction, the higher the proportion of NSD making particles intercontact. A filler particle with larger radius has more likely to contact with other filler particles, and thus large particles tend to dominate the interparticle interaction in asphalt mastic. The mean NSD of filler particles decreases with increasing the filler volume fraction. The volume fraction of PTZ has an increased first and decreased afterwards trend with the filler volume fraction. The filler's CVF decreases with the temperature increases. The constructed method is capable of determining the filler's CVF in asphalt mastic. [ABSTRACT FROM AUTHOR]

• New methods for the air voids of asphalt layers were developed. • The applicability of 7 prediction methods was evaluated to estimate the air voids. • The SVR algorithm was more suitable compared to other intelligent algorithms. • The proposed method by SVR algorithm can estimate the air voids in real time. The objective of the study was to give a suitable prediction method of air voids of asphalt layers in the process of construction. Seven different methods are utilized to predict the air voids of asphalt layers: nonlinear data fitting, Back Propagation neural network (BPNN) algorithm, Radial Basis Function neural network (RBFNN) algorithm, support vector machine for regression (SVR), Gaussian process regression (GPR), regression trees, and random forest regression. The results of laboratory experiments and field tests showed that the intelligent algorithm of SVR is more accurate and suitable for estimating the air voids of asphalt layers. The compaction quality of asphalt layers can be evaluated by this proposed new prediction method of air voids. [ABSTRACT FROM AUTHOR]

Variability of gradation for asphalt mixture is always the difficulty faced by the control of pavement construction, involving the pavement performance. The main purpose of this study is to improve the efficiency of detection for gradation variation and clarify the relationship between gradation variation and construction process. The variability of gradation for superpave asphalt mixtures was investigated with nominal maximum aggregate size (NMAS) of 13 mm, 20 mm, and 25 mm in construction. The correlation between the passing percentages at each sieve size and performance of asphalt mixture was first established by coupling grey relational analysis and entropy weight method. A digital image processing technology with multi-thresholds segmentation (DIP-MTS) was developed and verified through the experiment comparison. An approach to reversely calculate the gradation of cold aggregate was established. The mixture gradations during various construction stages were compared. Results illustrate that the passing percentages of sieves with NMAS, 4.75 mm, and 0.075 mm have a significant influence on the pavement performance and should be paid more attention during construction. The detection results of DIP-MTS are closer to the experimental value, and this technology is capable of detecting gradation for moving aggregate. The reverse calculation approach is proved feasible. Gradation variation in transportation is more severe than other construction processes. [Display omitted] • The critical passing percentages of gradation were determined. • A DIP-MTS technology was developed and verified. • An approach to reversely calculate the grading of cold aggregate was established. • Transportation process is the most sensitive process to the gradation variation. [ABSTRACT FROM AUTHOR]