Search

This research study evaluates the impact of low-density polyethylene (LDPE) modified asphalt binder on the mechanical performance and economical feasibility of asphalt concrete (AC) mixtures. LDPE-modified mixtures were compared with conventional mixes prepared with various binders commonly used in India, i.e., VG 30, VG 40, Polymer-Modified Binder (PMB), and Crumb Rubber Modified Binder (CRMB). LDPE-modified mixtures exhibit superior mechanical performance, increasing the stiffness of AC mixtures by 171% and 125% at 25 °C and 35 °C, respectively, compared to VG 30 base binder. Additionally, the indirect tensile strength (ITS) improved by 51% over VG 30. LDPE-modified mixtures also showed improved resistance to permanent deformation, with RTIndex values up to 133.46% higher than VG 30, and higher fatigue resistance, as indicated by increased CTIndex values compared to VG 30 and CRMB. However, the CTIndex values for LDPE-modified mixtures were 26.32% and 56% lower than those for VG 40 and PMB, respectively. Pavement analysis using 3D-Move showed lesser deflections at pavement layer interfaces, resulting in higher rutting and fatigue life for LDPE-modified pavements. Furthermore, LDPE-modified pavements showed up to 57% higher fatigue life (Nf) and up to 42.33% higher rutting life (Nr) than other pavements. The economic analysis showed that the cost of LDPE-modified pavements is comparable to VG 40 and around 10% more economical than pavements containing PMB. Using LDPE also offers environmental benefits by repurposing up to 750 kg for every kilometer of single-lane pavement section having 50mm thick surface course. Overall, LDPE-modified asphalt mixtures present a sustainable and high-performance solution for asphalt pavement construction. [ABSTRACT FROM AUTHOR]

During the construction and maintenance of asphalt pavement, a lot of non-renewable resources are consumed, which discharge a variety of waste gasses and smoke, causing a serious impact on the environment. Reducing society's reliance on non-renewable resources is therefore key to improving sustainability. It is found that phase change materials (PCMs), as environmentally friendly materials, can spontaneously store and release heat energy by changing the phase state, thus reducing the adverse effect of temperature on asphalt pavement, reducing the occurrence of high-temperature stress, minimizing the cost of road construction and maintenance, and saving resources. In order to promote the application of PCMs in asphalt pavement, to promote self-controlling temperature technology for asphalt pavement, and to improve the sustainable development of asphalt pavement, this paper reviews the research status of PCMs in asphalt pavement, both domestically and abroad. The results show that the thermal conductivity of the modified asphalt binder can reach 0.29–0.39 W/mK, and the thermal diffusivity can reach 0.2–0.3 mm2/s, but the influence on the viscosity of the asphalt is limited, and both are less than 2000CP. The durability and thermal stability of the modified asphalt mixture are improved, and the maximum temperature can be lowered by 9 °C, which effectively reduces the occurrence of hightemperature stress. This review will help to better understand the function of PCMs and promote the sustainable development of green and environmentally friendly asphalt pavement. [ABSTRACT FROM AUTHOR]

The length of basalt fibers affects the performance of asphalt mixtures. To explore the influence of different lengths of basalt fibers on the performance of asphalt mixtures, this study selected basalt fibers with lengths of 6 mm, 9 mm, and 12 mm to design gradations that were incorporated into asphalt mixtures to prepare specimens. High-temperature rutting tests, immersion Marshall tests, freeze-thaw splitting tests, and low-temperature splitting tests were conducted, resulting in 11 test mix designs and 12 test indicators. Then, a multi-objective grey target decision method was used to optimize the optimal combination ratio of basalt fiber lengths. The results indicate that compared to asphalt mixtures with single-length basalt fibers, incorporating well-combined basalt fibers significantly enhances the high-temperature, low-temperature, and water stability performance of asphalt mixtures. According to the grey target decision method, this study determined that a basalt fiber combination ratio of 3:4:3 for lengths of 6 mm, 9 mm, and 12 mm provides the best overall performance of asphalt mixtures. Additionally, when designing asphalt mixtures with graded basalt fibers, the inclusion of 9 mm fibers should be the primary control point. These research findings provide important guidance for the enhanced application of basalt fibers in road engineering. [ABSTRACT FROM AUTHOR]

The accurate characterization of fatigue life affects the durability and reliability of asphalt pavement for the asphalt mixtures. This paper proposed a new fatigue test method and analysis method which, in addition to increasing the accuracy of fatigue characterization, reduces the time and cost consumed in laboratory tests of asphalt mixtures. According to the loading speed corresponding to different loading frequency and stress levels, the corresponding strength value is selected to determine the stress ratio in the fatigue equation. Therefore, the stress ratio can truly reflect the fatigue loading stress conditions and correspond to the fatigue loading speed one by one, avoiding the unscientific fatigue resistance design problem caused by the traditional S-N fatigue equation stress ratio, which takes a single strength value at a constant loading speed as the standard. Since the stress ratio takes into account the influence of loading speed under different loading frequencies and stress levels, a unified representation model of the fatigue equation of the asphalt mixture under different loading frequencies can be established; that is, the fatigue performance of the asphalt mixture under different loading frequencies can be normalized. The results showed that the loading rate in the strength test differed from the loading rate in the traditional fatigue test, which means that the fatigue curve could not be extended to point (1,1) when the fatigue equation was extended to a fatigue life N f = 1. The fatigue test related to the velocity-dependent stress ratio in multiple experimental works, and data discreteness had a remarkable influence on fatigue characterization. The fatigue curve obtained by the fatigue equation under a constant loading rate was consistent with the fatigue curve under different loading rates. This method can reduce the duration of strength tests and the impact of the strength results of discreteness on fatigue characterization. The fatigue characterization model under constant loading rates considered the viscoelasticity of asphalt mixtures and guaranteed the correspondence of test conditions among stress level t, standard strength St, and fatigue life N f . The stress levels and loading rates of the asphalt mixtures were confirmed to be equivalent. Furthermore, this paper established the relationship between strength and fatigue and obtained the fatigue life curve of the strength values. The fatigue performance of the asphalt mixtures is evaluated comprehensively. [ABSTRACT FROM AUTHOR]

The goals of this study are to assess the viability of waste tire-derived char (WTDC) as a sustainable, low-cost fine aggregate surrogate material for asphalt mixtures and to develop the statistically coupled neural network (SCNN) model for predicting volumetric and Marshall properties of asphalt mixtures modified with WTDC. The study is based on experimental data acquired from laboratory volumetric and Marshall properties testing on WTDCmodified asphalt mixtures (WTDC-MAM). The input variables comprised waste tire char content and asphalt binder content. The output variables comprised mixture unit weight, total voids, voids filled with asphalt, Marshall stability, and flow. Statistical coupled neural networks were utilized to predict the volumetric and Marshall properties of asphalt mixtures. For predictive modeling, the SCNN model is employed, incorporating a three-layer neural network and preprocessing techniques to enhance accuracy and reliability. The optimal network architecture, using the collected dataset, was a 2:6:5 structure, and the neural network was trained with 60% of the data, whereas the other 20% was used for cross-validation and testing respectively. The network employed a hyperbolic tangent (tanh) activation function and a feed-forward backpropagation. According to the results, the network model could accurately predict the volumetric and Marshall properties. The predicted accuracy of SCNN was found to be as high value >98% and low prediction errors for both volumetric and Marshall properties. This study demonstrates WTDC's potential as a low-cost, sustainable aggregate replacement. The SCNN-based predictive model proves its efficiency and versatility and promotes sustainable practices. [ABSTRACT FROM AUTHOR]

Asphalt mixtures can include various recycled materials, which often replace some of the coarse and fine aggregate components. In some cases, a percentage of material called mineral filler, made up of particles that pass through a No. 200-sieve, is also admitted in the preparation of the mixture. With the increasing amount of packaging used as containers for various products, many of which need to be disposed of properly and become an environmental burden in warehouses without proper reuse, there is potential for including these elements in the sustainable modification of asphalt mixtures. This research suggests reusing plastic and aluminum coffee capsules, which are difficult to recycle. While most studies crush recycled materials to sizes smaller than 0.075 mm for use in mixes, this research focuses on assembling the waste capsules into a network of cells inside specimens subjected to bending to observe the mechanical behavior of the asphalt mixture. The findings indicate that incorporating capsule networks can lead to a significant enhancement in the flexural strength of the examined beams, with an increase of up to 200%. Moreover, the deformation is reduced by an average of 66% upon the emergence of the initial crack in the specimen. [ABSTRACT FROM AUTHOR]

Abstract This research study evaluates the impact of low-density polyethylene (LDPE) modified asphalt binder on the mechanical performance and economical feasibility of asphalt concrete (AC) mixtures. LDPE-modified mixtures were compared with conventional mixes prepared with various binders commonly used in India, i.e., VG 30, VG 40, Polymer-Modified Binder (PMB), and Crumb Rubber Modified Binder (CRMB). LDPE-modified mixtures exhibit superior mechanical performance, increasing the stiffness of AC mixtures by 171% and 125% at 25 °C and 35 °C, respectively, compared to VG 30 base binder. Additionally, the indirect tensile strength (ITS) improved by 51% over VG 30. LDPE-modified mixtures also showed improved resistance to permanent deformation, with RT Index values up to 133.46% higher than VG 30, and higher fatigue resistance, as indicated by increased CT Index values compared to VG 30 and CRMB. However, the CT Index values for LDPE-modified mixtures were 26.32% and 56% lower than those for VG 40 and PMB, respectively. Pavement analysis using 3D-Move showed lesser deflections at pavement layer interfaces, resulting in higher rutting and fatigue life for LDPE-modified pavements. Furthermore, LDPE-modified pavements showed up to 57% higher fatigue life (Nf) and up to 42.33% higher rutting life (Nr) than other pavements. The economic analysis showed that the cost of LDPE-modified pavements is comparable to VG 40 and around 10% more economical than pavements containing PMB. Using LDPE also offers environmental benefits by repurposing up to 750 kg for every kilometer of single-lane pavement section having 50mm thick surface course. Overall, LDPE-modified asphalt mixtures present a sustainable and high-performance solution for asphalt pavement construction.

This study investigated the performance of rubberized asphalt mixtures through Marshall and wheel track tests. The optimal binder content for rubberized asphalt specimens containing 6 and 8% rubber was determined to be 4.9 and 5%, respectively, while the control asphalt required 4.6% binder content. The results indicate that modifying the binder with crumb rubber improves the properties of the asphalt mixture. The wheel track tests show that the rubberized asphalt samples have far shallower ruts than the control samples, demonstrating successful protection against long-term distortion. Rubberized asphalt is more resistant to rutting at higher temperatures, with lower sustained strain rates and shallower ruts. Adding crumb rubber enhances the stiffness and viscosity of the asphalt binder, contributing to the improved rutting resistance of the rubberized asphalt mixtures. This study emphasized the potential of rubberized asphalt as a sustainable solution for enhancing pavement durability and longevity. The findings highlight the benefits of using rubberized asphalt in pavement engineering and provide valuable insights for optimizing binder content and improving performance. Incorporating crumb rubber in asphalt mixtures can reduce rutting and enhance the overall sustainability of pavement surfaces.

The goals of this study are to assess the viability of waste tire-derived char (WTDC) as a sustainable, low-cost fine aggregate surrogate material for asphalt mixtures and to develop the statistically coupled neural network (SCNN) model for predicting volumetric and Marshall properties of asphalt mixtures modified with WTDC. The study is based on experimental data acquired from laboratory volumetric and Marshall properties testing on WTDC-modified asphalt mixtures (WTDC-MAM). The input variables comprised waste tire char content and asphalt binder content. The output variables comprised mixture unit weight, total voids, voids filled with asphalt, Marshall stability, and flow. Statistical coupled neural networks were utilized to predict the volumetric and Marshall properties of asphalt mixtures. For predictive modeling, the SCNN model is employed, incorporating a three-layer neural network and preprocessing techniques to enhance accuracy and reliability. The optimal network architecture, using the collected dataset, was a 2:6:5 structure, and the neural network was trained with 60% of the data, whereas the other 20% was used for cross-validation and testing respectively. The network employed a hyperbolic tangent (tanh) activation function and a feed-forward backpropagation. According to the results, the network model could accurately predict the volumetric and Marshall properties. The predicted accuracy of SCNN was found to be as high value ​>98% and low prediction errors for both volumetric and Marshall properties. This study demonstrates WTDC's potential as a low-cost, sustainable aggregate replacement. The SCNN-based predictive model proves its efficiency and versatility and promotes sustainable practices.

It is commonly known that mineral fillers significantly affect the asphalt mixture's performance. Superior flexible pavement performance can be ensured by gaining a deeper understanding of the function of filler. This research investigates the influence of three different fillers: granite dust, cement, and hydrated lime, at Australian asphalt mixtures. The testing program includes Marshall testing, moisture damage resistance, indirect tensile strength (ITS), and indirect tensile stiffness modulus (ITSM) tests of asphalt mixtures. Analysis of variance (ANOVA) was used to statistically assess the results obtained, besides damage analysis. The results indicate that using natural granite dust yields the highest resistance to moisture, while cement produces the highest stability, ITS, and ITSM. Unexpectedly, using hydrated lime filler decreases the stability/stiffness and moisture resistance of asphalt mixtures. ANOVA tests indicate that the type of filler affects ITS, TSR, and ITSM results (i.e., the p-value

Ground-penetrating radar (GPR) has been widely used for subsurface detection and testing. Numerical simulations of GPR signal are commonly performed to aid the interpretation of subsurface structures and targets in complex environments. To enhance the accuracy of GPR simulations on heterogeneous medium, this paper proposes a hybrid modeling method that combines the discrete element method with a component fusion strategy (DEM–CFS). Taking the asphalt pavement as an example, three 3D stochastic models with distinctly different porosities are constructed by the DEM–CFS method. Firstly, the DEM is utilized to establish the spatial distribution of random coarse aggregates. Then, the component fusion strategy is employed to integrate other components into the coarse aggregate skeleton. Finally, the GPR response of the constructed asphalt models is simulated using the finite-difference time-domain method. The proposed modeling method is validated through both numerical and laboratory experiments and demonstrates high precision. The results indicate that the proposed modeling method has high accuracy in predicting the dielectric constant of heterogeneous media, as generated models are closely aligned with real-world conditions. [ABSTRACT FROM AUTHOR]

Copyright of Transportation Science & Technolgy is the property of Transportation Science & Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The construction and maintenance of road infrastructure is required for the sustained economic growth of communities and societies. Nonetheless, these activities imply the tangible risk of boosting the depletion of non-renewable resources (e.g., aggregates and binders). A widely used strategy for preserving as much of these natural resources as possible is the design of high-performance composite materials. For instance, antistripping agents (ASAs) are employed to mitigate the loss of adhesive bonding between asphalt binders and aggregates, enhancing the mechanical behaviour of hot-mix asphalts (HMAs). There is still no consensus on the effectiveness of ASAs. In this regard, the present research aims to contribute to the literature by conducting a case study on the influence of three different ASAs (hydrated lime, an amines-based liquid additive, and a silanes-based liquid additive) on the moisture susceptibility, stiffness, and rutting resistance of HMA. For these purposes, indirect tensile strength, indirect tensile stiffness modulus, and uniaxial cyclic compression tests were carried out. Overall, the involved experimental protocol drew the main conclusion that the incorporation of hydrated lime as a mineral filler (at a content of 1.68% by dry weight of aggregates) is capable of improving the mechanical performance of HMAs through decreases in humidity sensitivity and permanent deformation, together with a slight increase in rigidity. [ABSTRACT FROM AUTHOR]

With the progressive reduction in virgin material availability and the growing global concern for sustainability, civil engineering researchers worldwide are shifting their attention toward exploring alternative and mechanically sound technological solutions. The feasibility of preparing both cold and hot asphalt mixtures (AMs) for road pavement binder layers with construction and demolition wastes (C&DWs) and reclaimed asphalt pavement (RAP) partially replacing virgin materials like limestone aggregates and filler has already been proven. The technical suitability and compliance with technical specifications for road paving materials involved the evaluation of mechanical and volumetric aspects by means of indirect tensile strength tests and saturated surface dry voids, respectively. Thus, the main goal of the present study is to train, validate, and test selected machine learning algorithms based on data obtained from the previous experimental campaign with the aim of predicting the volumetric properties and the mechanical performance of the investigated mixtures. A comparison between the predictions made by ridge and lasso regression techniques and both shallow (SNN) and deep neural network (DNN) models showed that the latter achieved better predictive capabilities, highlighted by fully satisfactory performance metrics. DNN performance can be summarized by R2 values equal to 0.8990 in terms of saturated surface dry void predictions, as well as 0.9954 in terms of indirect tensile strength predictions. Predicted observations can be thus implemented within the traditional mix design software. This would reduce the need to carry out additional expensive and time-consuming experimental campaigns. [ABSTRACT FROM AUTHOR]

The construction and maintenance of asphalt pavements is a resource-consuming sector, where the continuous rehabilitation of the superficial layers demands large volumes of non-renewable resources. The present work focuses on the design and characterization of asphalt mixtures for the binder layer of an asphalt pavement containing 50% reclaimed asphalt (RAP), in which seven different bio-based additives, identified as R1A, R1C, R2A, R2B, R2C, R3A, and R3B, were added to improve the workability, strength, and stiffness properties. The experimental program envisioned the hot mixing of aggregates and RAP with either a 50/70 or a 70/100 bitumen and, in turn, each of the seven bio-additives. The asphalt mixtures underwent the characterization of their densification properties; air voids; indirect tensile strength (ITS); indirect tensile stiffness modulus at 10, 20, 40, and 60 °C; and rutting resistance at 60 °C. The results highlighted that the performance in terms of workability and ITS of the resulting mixtures depends on the type of bio-additive and largely on the fresh bitumen type, while the stiffness at high temperature is not significantly affected by the presence of the bio-additives. [ABSTRACT FROM AUTHOR]

Asphalt mixtures are widely used as a surfacing material for pavements due to their several advantages. For this reason, robust numerical models still need to be developed to improve the understanding of their fracture behaviour. Recently, an incremental generalised Kelvin (GK) contact model that relates increments in contact displacements with increments in contact forces was proposed to assess the viscoelastic behaviour of asphalt mixtures within a discrete element method (DEM) framework. In this work, the contact model is extended to allow its application to asphalt mixture fracture studies. Two damage models—a brittle and a bilinear softening—coupled with the GK contact model are proposed to consider damage initiation and propagation. A parametric study is presented that assesses the impact of the GK-Damage parameters, showing a sensitivity to the loading velocity and the Maxwell elements, particularly its viscosity element, on the stress–strain response of a single contact. A reduced-size numerical mastic is initially used to speed up the calibration process of the GK-Damage contact parameters, with subsequent validation on a specimen with real experimental dimensions. It is shown that the proposed calibrated damage models can successfully reproduce the time-dependent behaviour, peak stress, and crack path observed in experimental results, highlighting the benefits of the adopted methodology. For the GK-Bilinear model, the fracture energy and maximum contact tensile stress are shown to adjust both the peak stress and softening response. Uniaxial tensile tests on asphalt mixtures indicate that the GK-Bilinear model provides a more realistic characterisation of fracture development. A higher susceptibility to damage at aggregate-to-mastic contacts compared to contacts within the mastic phase is identified. [ABSTRACT FROM AUTHOR]

Copyright of Roads & Bridges / Drogi i Mosty is the property of Road & Bridge Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The large temperature differences between day and night in winter at plateau areas can lead to the reduction of skid resistance of roads. However, most of the traditional salt storage and deicing fillers are chlorides, and their long-term usage will cause damage to the ecological environment. In order to achieve green deicing of asphalt pavement, this paper developed efficient and environmentally friendly salt storage fibers for the anti-icing of asphalt pavement, and the optimal components of salt storage fibers were determined. On this basis, the morphology and rust resistance of salt storage fibers were characterized, and the ice suppression and deicing performances were also determined. The experimental results show that the optimal component ratio of anti-icing reagent for sodium acetate, potassium acetate and sodium formate follows 7∶2∶1 and the optimal component ratio of organic salt and fiber is 3∶1 , which can achieve a better ice-melting effect and sustainable economy. According to the scanning electron microscope (SEM) images, the salts in the salt storage fiber are fully absorbed, which has a certain slow-release performance due to the resin package. In addition, the effective anti-icing components of the salt storage fiber are less corrosive to the metal materials, and the asphalt mixtures doped with salt storage fibers can melt ice at the rate of (1,022 g/ h·m2) under relatively low temperatures. This can effectively weaken the freeze-bond strengths and ice–road interface adhesion. [ABSTRACT FROM AUTHOR]

The study of the behavior of bituminous mixtures is a very old subject in the specialized literature, many specialists in the field trying to explain the causes of the degradations, considering different factors. The bituminous mixtures were initially used in the construction of road structures for roads, so that a few years ago they also started to be used in the road structures of airport surfaces. The subject of the current research study is a priority worldwide and contributes, through the obtained results, to the enrichment of knowledge regarding the behavior of airport bituminous mixtures. The complexity of this study was based on the multitude of laboratory tests carried out on the designed airport bituminous mixture, BBA 16, using complex modern and high-performance equipment and equipment that lead to the determination of the stiffness modulus at different temperatures and frequencies both on trapezoidal samples and on prismatic samples. [ABSTRACT FROM AUTHOR]

To propose a constitutive model that can accurately characterize the three stages of asphalt mixture creep, the fractional Burgers damage creep model is constructed based on the Burgers model by combining the fractional calculus theory and damage mechanics theory. The effect of stress on the viscoelasticity of the asphalt mixture is analyzed by the uniaxial compression creep test. Through the sensitivity analysis of the model parameters, the regulatory role and physical significance of each parameter are clarified. Based on the fractional Burgers damage creep model, a method is proposed to predict the creep considering time-varying stress. The results show that the fractional Burgers damage creep model can accurately fit the creep curve of the whole process. The fractional Kelvin element of damage is closely related to the rheological time of the model. The larger the value of α, the stronger the viscous flow ability of the model, which is consistent with the results of the parametric analysis considering stress. The prediction method considering time-varying stresses has some rationality and correctness. [ABSTRACT FROM AUTHOR]

The aging of asphalt mixes affects the durability of the pavement. The characteristics of the mixture interact in a complex way with the temperature and service time on site, so the use of the cumulated degree-days (CDD) criterion is possible. The work's objective is to analyze the aging of the mixtures in the Coastal and Andean regions, through the application of the CDD related to the stiffness modulus at 20 °C in the NAT equipment, obtained from cores sampling in roads built in different years and to make observations regarding existing damages associated with durability. Seven sections were selected from similar mixtures placed between 0 and 14 years ago, made with crushed alluvial materials and AC-20 asphalt from the Esmeraldas refinery. The results show that the aging evaluated through the stiffness modulus presented a greater impact in the Coastal region than in the Andean region due to its higher temperatures, allowing the use of the CDD to unify the behaviors in the two regions into a single relationship. Observations show that the probable range of the progressive evolution of damages, from its beginning to its critical phase, is from 45.000 to 80.000 °C-days. [ABSTRACT FROM AUTHOR]

Usually, aggregates used for asphalt mixtures consist mainly of natural aggregates. Sometimes the natural aggregates are substituted with limited amounts of industrial and construction wastes. The current paper deals with evaluating the mechanical performance of new developed hot asphalt mixtures made of up to 98% industrial and construction by products. In this project, different types of industrial by-products, namely, RAP, foundry sand, and steel slag in addition to biobased rejuvenators have been used to find the composition of the best asphalt mixtures made mainly of wastes that can substitute the asphalt mixtures made of natural aggregates. Fourteen selected asphalt mixtures have been evaluated using the circular road simulator test at VTI. The CRS testing program has been set up to allow different measurements, e.g. surface deterioration and wear, friction, and visual inspection. The test results demonstrated that it is possible to obtain paving mixtures with high content of recycled materials. [ABSTRACT FROM AUTHOR]

The Response Surface Methodology (RSM) is a collection of methods used to create various experiment designs, determine relationships between experimental variables and responses, and use these relationships to identify the ideal conditions. This study uses RSM to forecast the mechanical characteristics of mixtures modified with steel slag and lime. Using the Box Behnken Design (BBD) method for the mix proportion, steel slag (0-100%), lime (0-4%), and bitumen content (4-8%) were considered independent variables, while the responses were the resilient modulus, indirect tensile strength, flexural stiffness, and compressive strength. Analysis of variance showed that the steel slag was the most influencing factor for the flexural stiffness property of the steel-slag and lime-modified asphalt mixtures. Also, the regression coefficient (R2) of 0.9214, 0.8380, 0.7412, and 0.8266 was obtained for the stiffness, Mr, compressive strength, and ITS, respectively. Some interaction effects on the responses were found between the steel slag and lime. The optimization findings show that 25.01% steel slag, 2.43% lime, and 5.51% bitumen content are the best values to satisfy the design criteria. The optimized mixture design will offer a cost-effective and environmentally friendly solution, promoting resource conservation and sustainable development in the construction industry. [ABSTRACT FROM AUTHOR]

Recently, the feasibility of using bio-materials to reduce or completely replace the use of bitumen in asphalt mixture has gained increasing attention. Amongst others, an interesting solution is represented by the use of wood co-products with mineral or vegetable oils. This research focuses on the development of bio-binders using vegetable resin (VR) in unmodified form and waste olive oil (WOO) as the main components; in order to optimize the rheological properties of the blends, crumb rubber from end-of-life tyres (CR), Styrene-Butadiene-Styrene (SBS) and polyethylene waxes (PEW) are used as additives. In particular, this investigation focuses on studying different oil/rosin ratios and polymer contents to provide a clear framework on this bio-binder solution; conventional bituminous binders are taken as a reference. The alternative binders are characterized in terms of conventional properties such as penetration depth and softening point, as well as rheological response. Finally, two of the bio-binders studied are selected with the aim of assessing the mechanical properties of the resulting sustainable asphalt mixture using the Marshall Stability test and the Indirect Tensile Strength test, comparing the results with the threshold values set by an Italian road agency. Thus, this research represents a preliminary analysis of the potential application of bio-binder mixtures within the specification limits imposed by road agencies. Although this research represents a first attempt, the results are promising and prove to be worthy of further investigations. [ABSTRACT FROM AUTHOR]

This manuscript presents a comprehensive study on the sustainable optimization of asphalt mixtures tailored for regions prone to flooding. The research addresses the challenges associated with water damage to asphalt pavements by incorporating innovative additives. The study centers on incorporating recycled Low-Density Polyethylene (LDPE) and a tailored Carnauba–Soybean Oil Additive, advancing asphalt mixtures with a Control mix, LDPE (5%) + Control, and LDPE (5%) + 3% Oil + Control. A critical aspect of the research involves subjecting these mixtures to 30 wetting and drying cycles, simulating the conditions prevalent in tropical flood-prone areas. The incorporation of innovative additives in asphalt mixtures has demonstrated significant improvements across various performance parameters. Tensile Strength Ratio (TSR) tests revealed enhanced tensile strength, with the LDPE (5%) + 3% Oil-modified mixture exhibiting an impressive TSR of 85.7%. Dynamic Modulus tests highlighted improved rutting resistance, showcasing a remarkable increase to 214 MPa in the LDPE (5%) with a 3% Oil-modified mixture. The Semi-Circular Bending (SCB) test demonstrated increased fracture resistance and energy absorption, particularly in the LDPE (5%) with 3% Oil-modified mixture. Hamburg Wheel-Tracking (HWT) tests indicated enhanced moisture resistance and superior rutting resistance at 20,000 cycles for the same mixture. Cantabro tests underscored improved aggregate shatter resistance, with the LDPE (5%) + 3% Oil-modified mixture exhibiting the lowest weight loss rate at 9.820%. Field tests provided real-world insights, with the LDPE (5%) + 3% Oil mixture displaying superior stability, a 61% reduction in deflection, and a 256% improvement in surface modulus over the control mixture. This research lays the groundwork for advancing the development of sustainable, high-performance road pavement materials, marking a significant stride towards resilient infrastructure in flood-prone areas. [ABSTRACT FROM AUTHOR]

The performance of asphalt roads is affected by many factors such as temperature, water, loads and materials characteristics. These factors cause thermal cracking, permanent deformation (rutting) and fatigue distresses on asphalt concrete layers. In the last years, many researchers studied improving the performance of asphalt concrete by using polypropylene synthetic fibers (PPF). This paper describes a laboratory study on the mechanical characteristics of asphalt mixtures by reinforcing them with polypropylene fibers and improving their characteristics and durability. The physical characteristics of the asphalt binder (Penetration at 25°C, ductility, softening point) were carried out on reinforced and unreinforced asphalt binders with polypropylene fibers. It was found that the PPF reinforced asphalt can improve the consistency and characteristics of asphalt concrete. Asphalt concrete specimens were prepared with varying contents of polypropylene fibers (0%, 3%, 4%, 5% and 6% by weight of asphalt binder). In total, sixty specimens were prepared by using Marshall Mix design method (fifteen specimens were used to determine the optimum asphalt binder content and the remaining specimens were used to investigate the effect of reinforcing the asphalt mixtures with PPF. The mechanical characteristics of the reinforced asphalt mixtures with polypropylene fibers were compared with a reference asphalt mixture. The results show that increasing the amount of PPF in the asphalt mixtures led to increases in Marshall Stability and air void in the total mix, while the flow values decreased for all mixtures. It is noticed that the use of 5% PPF shows the highest stability value with flow and air voids values within specification limits [ASTM].

This experimental study aims to assess the water sensitivity and fracture toughness of asphalt Mixtures subjected to thermal cycling, using different types of aggregates and incorporating hydrated lime as an additive. To achieve this, two types of aggregates were used: limestone and schist aggregates, each with distinct characteristics. These aggregates were mixed with pure grade 35–50 bitumen to create two asphalt Mixtures. In addition, 2 % hydrated lime was added to both Mixtures as a filler to assess its impact on asphalt mixture properties.The water sensitivity of the asphalt Mixtures was assessed using the water resistance test, in accordance with NM EN 12697-12, method B. A total of 40 samples were tested, divided into ''dry specimens'' and ''humid specimens''. The former were kept under controlled conditions (temperature 18 °C and 50 % humidity) for 7 days, while the latter were subjected to a water saturation process beforehand, then kept immersed in water at a temperature of 18 °C for the same period. Water resistance was calculated by comparing the compressive strength of the two types of specimens.To evaluate the specimens' fracture toughness, the Semi-Circular Bending (SCB) test was employed. Cracks were introduced into the center of each semicircular specimen to measure their resistance to crack propagation. This test was carried out after the samples had been subjected to a water-saturated degassing process and the application of thermal cycles.Thermal cycles were applied using temperatures based on Moroccan climatic conditions to simulate actual road conditions. Three conditioning methods were used: freeze-thaw cycles (-5–20 °C), heating-cooling cycles (20–40 °C) and a combination of both. SCB samples were tested at a temperature of 20 °C after a number of thermal cycles, ranging from 15 to 120. A total of 160 SCB samples were tested for resistance to temperature-induced cracking.The results showed that asphalt Mixtures based on schist were generally more sensitive to thermal cycling than those based on limestone. However, the inclusion of hydrated lime as an additive has proved to be beneficial for both types of asphalt mixtures, particularly for those based on schist by attenuating the decrease in their strength and sensitivity to water. The primary goal is to enhance the durability of Moroccan roads while minimizing maintenance costs.

The Response Surface Methodology (RSM) is a collection of methods used to create various experiment designs, determine relationships between experimental variables and responses, and use these relationships to identify the ideal conditions. This study uses RSM to forecast the mechanical characteristics of mixtures modified with steel slag and lime. Using the Box Behnken Design (BBD) method for the mix proportion, steel slag (0–100%), lime (0–4%), and bitumen content (4–8%) were considered independent variables, while the responses were the resilient modulus, indirect tensile strength, flexural stiffness, and compressive strength. Analysis of variance showed that the steel slag was the most influencing factor for the flexural stiffness property of the steel-slag and lime-modified asphalt mixtures. Also, the regression coefficient (R2) of 0.9214, 0.8380, 0.7412, and 0.8266 was obtained for the stiffness, Mr, compressive strength, and ITS, respectively. Some interaction effects on the responses were found between the steel slag and lime. The optimization findings show that 25.01% steel slag, 2.43% lime, and 5.51% bitumen content are the best values to satisfy the design criteria. The optimized mixture design will offer a cost-effective and environmentally friendly solution, promoting resource conservation and sustainable development in the construction industry.

The accurate characterization of fatigue life affects the durability and reliability of asphalt pavement for the asphalt mixtures. This paper proposed a new fatigue test method and analysis method which, in addition to increasing the accuracy of fatigue characterization, reduces the time and cost consumed in laboratory tests of asphalt mixtures. According to the loading speed corresponding to different loading frequency and stress levels, the corresponding strength value is selected to determine the stress ratio in the fatigue equation. Therefore, the stress ratio can truly reflect the fatigue loading stress conditions and correspond to the fatigue loading speed one by one, avoiding the unscientific fatigue resistance design problem caused by the traditional S-N fatigue equation stress ratio, which takes a single strength value at a constant loading speed as the standard. Since the stress ratio takes into account the influence of loading speed under different loading frequencies and stress levels, a unified representation model of the fatigue equation of the asphalt mixture under different loading frequencies can be established; that is, the fatigue performance of the asphalt mixture under different loading frequencies can be normalized. The results showed that the loading rate in the strength test differed from the loading rate in the traditional fatigue test, which means that the fatigue curve could not be extended to point (1,1) when the fatigue equation was extended to a fatigue life Nf = 1. The fatigue test related to the velocity-dependent stress ratio in multiple experimental works, and data discreteness had a remarkable influence on fatigue characterization. The fatigue curve obtained by the fatigue equation under a constant loading rate was consistent with the fatigue curve under different loading rates. This method can reduce the duration of strength tests and the impact of the strength results of discreteness on fatigue characterization. The fatigue characterization model under constant loading rates considered the viscoelasticity of asphalt mixtures and guaranteed the correspondence of test conditions among stress level t, standard strength St, and fatigue life Nf. The stress levels and loading rates of the asphalt mixtures were confirmed to be equivalent. Furthermore, this paper established the relationship between strength and fatigue and obtained the fatigue life curve of the strength values. The fatigue performance of the asphalt mixtures is evaluated comprehensively.

The length of basalt fibers affects the performance of asphalt mixtures. To explore the influence of different lengths of basalt fibers on the performance of asphalt mixtures, this study selected basalt fibers with lengths of 6 mm, 9 mm, and 12 mm to design gradations that were incorporated into asphalt mixtures to prepare specimens. High-temperature rutting tests, immersion Marshall tests, freeze-thaw splitting tests, and low-temperature splitting tests were conducted, resulting in 11 test mix designs and 12 test indicators. Then, a multi-objective grey target decision method was used to optimize the optimal combination ratio of basalt fiber lengths. The results indicate that compared to asphalt mixtures with single-length basalt fibers, incorporating well-combined basalt fibers significantly enhances the high-temperature, low-temperature, and water stability performance of asphalt mixtures. According to the grey target decision method, this study determined that a basalt fiber combination ratio of 3:4:3 for lengths of 6 mm, 9 mm, and 12 mm provides the best overall performance of asphalt mixtures. Additionally, when designing asphalt mixtures with graded basalt fibers, the inclusion of 9 mm fibers should be the primary control point. These research findings provide important guidance for the enhanced application of basalt fibers in road engineering.

This review explores the transformative impact of micromechanical modeling on flexible pavement design, addressing challenges posed by traditional uniform loading assumptions, particularly in the context of heavy truck tires. From the pioneering work of Chang and Meegoda in 1997 to recent studies by Al Khateeb et al. in 2021, micromechanical modeling explores the microstructural behavior of asphalt mixtures. Seminal contributions emphasize aspects such as shear fatigue performance, tire-pavement contact pressure, and inter-particle effects on asphalt microstructure. Notable works underscore the crucial role of tire-pavement interactions. Recent applications, such as studies on porous asphalt mixtures and coupling effects in asphalt microstructure, exemplify the diverse range of insights derived from micromechanical modeling. Beyond material characterization, the review explores the integration of these models into the pavement design process, promising resilient, sustainable, and cost-effective solutions that align with real-world pavement responses to heavy traffic loads. In conclusion, micromechanical modeling emerges as a powerful tool, empowering pavement engineers to design sophisticated systems for optimized performance and longevity in the evolving landscape of transportation demands. [ABSTRACT FROM AUTHOR]

With the increase in asphalt mixtures sustainability, the application of waste as a bitumen modifier has been encouraged. In addition, the asphalt mixtures produced considering only the engineering properties show degradation due to repetitive traffic loading and not the performance properties. Thus, necessitate the use of an alternative mix design considering various properties and considering alternative modifiers. Also, there are limited studies on the impact of long-term water immersion on the strength of asphalt mixtures, particularly the effects of both immersion-drying (I-D) cycles on Palm oil clinker fine-modified bitumen (POCF-MB). Thus, this study employed palm oil clinker fine (POCF) as a bitumen modifier. Response surface methodology (RSM) was used to evaluate an alternative engineering and performance mix design technique for asphalt mixtures was examined. Subsequently, the durability and strength of the optimized POCF-MB asphalt mixture for both I-D cycles were evaluated. Samples were vacuum saturated and immersed for 0 (dry) 1, 3, 5, and 7 days. Then assessed in terms of Marshall quotient (MQ), retained Marshall stability (RMS), swelling index (SI), indirect tensile strength (IDT), Indirect tensile strength ratio (ITSR), and subsequently redried at ambient temperature to evaluate the retained durability and strength. The RSM findings show that the synergetic effects of POCF dosage and bitumen significantly impact performance. Based on the high coefficients of determination (R2) values (> 0.95), high adequate precision values (> 4), and low p-values for all responses, the statistical models were determined to be significant and well-fitted. The optimum values of numerical optimization were 5.86% POCF dosage and 4.65% bitumen content. The validation test shows an error margin of < 5% for all responses indicating that the model and experimental values agree well and are closely aligned. With increasing conditioning time, all samples showed increased SI, flow, and a decline in MQ, RMS, IDT, and ITSR. However, POCF-MB samples showed minimal moisture durability reduction, which can be attributed to the hydration process of the POCF, making the mixtures stiffer. After redrying POCF-MB samples show a higher recovery of their initial durability, revealing that the durability and strength properties of the asphalt mixture are recoverable. [ABSTRACT FROM AUTHOR]

This study addresses the imperative for enhancing asphalt mixtures tailored for rural pavements, focusing on optimizing RAP mixtures with styrene–butadiene–styrene (SBS)-modified asphalt binders incorporating petroleum resin and oil. Through systematic investigation, the study examines the impact of varying RAP content (25% and 50%) and two SBS-modified asphalt binder types (Type 1 and Type 2) on mechanical properties and sustainability. Laboratory tests reveal that the mix of 25% RAP + 75% Type 1 exhibits exceptional flexibility, evidenced by a high ductility value of 880 mm at 25 °C, enhancing pavement resilience. Conversely, the 50% RAP + 50% Type 2 mixture displays vulnerability to fatigue cracking, while 25% RAP + 75% Type 1 demonstrates superior resistance, with a fatigue vulnerability value of 1524 kPa. The Hamburg Wheel Tracking test highlights the influence of RAP content on rut depth, with the mix of 50% RAP + 50% Type 1 achieving the lowest rutting at 3.9 mm. Overlay test results show the mix of 25% RAP + 75% Type 2's resilience, with the lowest load reduction at 64.5%, while the mix of 50% RAP + 50% Type 1 exhibits substantial load reduction at 82.1%. Field tests unveil differences in pavement bearing capacities, with the mix of 25% RAP + 75% Type 2 demonstrating a remarkable elastic modulus of 58.5 MPa, indicating heightened bearing capacity. The investigation underscores the significant role of SBS-modified asphalt binders with incorporated petroleum resin and oil in enhancing fatigue resistance for sustainable rural pavements. [ABSTRACT FROM AUTHOR]

The construction and maintenance of road infrastructure is required for the sustained economic growth of communities and societies. Nonetheless, these activities imply the tangible risk of boosting the depletion of non-renewable resources (e.g., aggregates and binders). A widely used strategy for preserving as much of these natural resources as possible is the design of high-performance composite materials. For instance, antistripping agents (ASAs) are employed to mitigate the loss of adhesive bonding between asphalt binders and aggregates, enhancing the mechanical behaviour of hot-mix asphalts (HMAs). There is still no consensus on the effectiveness of ASAs. In this regard, the present research aims to contribute to the literature by conducting a case study on the influence of three different ASAs (hydrated lime, an amines-based liquid additive, and a silanes-based liquid additive) on the moisture susceptibility, stiffness, and rutting resistance of HMA. For these purposes, indirect tensile strength, indirect tensile stiffness modulus, and uniaxial cyclic compression tests were carried out. Overall, the involved experimental protocol drew the main conclusion that the incorporation of hydrated lime as a mineral filler (at a content of 1.68% by dry weight of aggregates) is capable of improving the mechanical performance of HMAs through decreases in humidity sensitivity and permanent deformation, together with a slight increase in rigidity.

Ground-penetrating radar (GPR) has been widely used for subsurface detection and testing. Numerical simulations of GPR signal are commonly performed to aid the interpretation of subsurface structures and targets in complex environments. To enhance the accuracy of GPR simulations on heterogeneous medium, this paper proposes a hybrid modeling method that combines the discrete element method with a component fusion strategy (DEM–CFS). Taking the asphalt pavement as an example, three 3D stochastic models with distinctly different porosities are constructed by the DEM–CFS method. Firstly, the DEM is utilized to establish the spatial distribution of random coarse aggregates. Then, the component fusion strategy is employed to integrate other components into the coarse aggregate skeleton. Finally, the GPR response of the constructed asphalt models is simulated using the finite-difference time-domain method. The proposed modeling method is validated through both numerical and laboratory experiments and demonstrates high precision. The results indicate that the proposed modeling method has high accuracy in predicting the dielectric constant of heterogeneous media, as generated models are closely aligned with real-world conditions.

The construction and maintenance of asphalt pavements is a resource-consuming sector, where the continuous rehabilitation of the superficial layers demands large volumes of non-renewable resources. The present work focuses on the design and characterization of asphalt mixtures for the binder layer of an asphalt pavement containing 50% reclaimed asphalt (RAP), in which seven different bio-based additives, identified as R1A, R1C, R2A, R2B, R2C, R3A, and R3B, were added to improve the workability, strength, and stiffness properties. The experimental program envisioned the hot mixing of aggregates and RAP with either a 50/70 or a 70/100 bitumen and, in turn, each of the seven bio-additives. The asphalt mixtures underwent the characterization of their densification properties; air voids; indirect tensile strength (ITS); indirect tensile stiffness modulus at 10, 20, 40, and 60 °C; and rutting resistance at 60 °C. The results highlighted that the performance in terms of workability and ITS of the resulting mixtures depends on the type of bio-additive and largely on the fresh bitumen type, while the stiffness at high temperature is not significantly affected by the presence of the bio-additives.