In Iran, there are huge oil resources, and crude oil refining processes produce significant amounts of petroleum sludge (PS), so substantial quantities of this material are produced annually. Previous studies have indicated that the chemical compounds of the oil phase of PS are similar to those of bitumen. Additionally, the PS reduces the optimal bitumen content of the asphalt mixture and also contributes to energy savings by lowering the mixing and compaction temperatures. However, in previous studies, less than 10

The reuse of industrial waste materials in infrastructure projects presents a promising approach to reduce natural resource consumption and minimize environmental impacts. This study examines the performance of waste perlite powder (WPP) as a sustainable alternative to conventional natural fillers in slurry seal mixtures. Five mix designs were prepared by partially replacing the natural filler with WPP at 0%-10% total aggregate weight, corresponding to 0%-100% replacement of the original filler (constituting 10% of the aggregate). The mixtures were evaluated using a comprehensive set of standardized tests, including mixing time, wet cohesion, sand adhesion, wet track abrasion test (WTAT), and loaded wheel tracking (LWT), as well as determining the optimum residual bitumen content. The WPP at 75% (WPP75) achieved 28.4 kg & centerdot;cm of wet cohesion at 60 min, a 16% reduction in sand adhesion, and a greater than 50% improvement in abrasion resistance (355 g/m(2) versus 728 g/m(2) in the control). Wheel tracking tests indicated reductions of 25.7% and 42.3% in vertical and lateral displacements, respectively, highlighting improved deformation resistance. A higher WPP content increased water demand; all mixtures retained acceptable mixing times (> 180 s). Overlay analysis of WTAT and LWT results identified an optimal residual bitumen range of 8.03%-8.66%, with WPP75 showing the highest bitumen demand. A two-way analysis of variance showed that WPP content, bitumen dosage, and their interaction significantly affected performance, accounting for most of the response variability. Incorporating up to 7.5% WPP is technically viable and environmentally advantageous, enhancing the durability, cohesion, and sustainability of slurry seal pavements.

This study aimed to enhance asphalt-mix durability through microwave healing using magnetic fillers. Iron powder filler (IF) and magnetite filler (MF) were used to replace limestone filler (LF) to improve microwave thermal performance. The microwave heating rates, mechanical properties, and healing potential of these mixes were evaluated. The mechanical properties examined included indirect tensile strength, fracture toughness, fatigue life, and moisture sensitivity. A semicircular bending test at -20 degrees C assessed fracture healing potential, and fatigue healing potential was tested after a microwave heating-healing process. The fracture healing index decreased with advanced aging and a higher frequency of healing cycles. However, the positive impact of magnetic fillers on fracture healing was significant, especially as aging and recovery cycles progressed. Utilizing iron for 70% and 100% of the filler resulted in 22.9% and 24.8% fatigue healing, respectively, whereas 100% magnetite resulted in 20.1% fatigue healing. The microwave heating process significantly enhanced healing efficiency, contributing to the improved performance and durability of the mixtures. The magnetic properties of the fillers played a crucial role in this enhancement. Using 70% iron powder and 100% magnetite as total fillers was most effective for improving mechanical strength, durability, and healing capabilities.

The growing global concerns over environmental sustainability, particularly with respect to waste plastic accumulation and its impact on global warming, highlight the urgent need for innovative, eco-friendly solutions in civil engineering. Simultaneously, the demand for durable and sustainable infrastructure, especially asphalt pavements, has risen due to increased traffic and population growth. This study addresses these challenges by exploring the potential of warm mix asphalt (WMA) technology combined with recycled plastic waste, specifically from PET bottles, to develop a more sustainable pavement material. Recycled PET was used as an eco-friendly modifier for asphalt binder, alongside Sasobit (R) as a warm mix additive. Various asphalt mixtures containing 0 %, 1 %, and 2 % recycled PET were prepared and subjected to comprehensive mechanical tests, including dynamic creep (DC), indirect tensile strength (ITS), indirect tensile stiffness modulus (ITSM), and semi-circular bending (SCB) tests. These tests evaluated the mixtures' resistance to rutting, moisture susceptibility, and low-temperature cracking. The results demonstrated that incorporating 2 % recycled PET significantly enhanced the rutting resistance, moisture resistance, and low-temperature cracking performance of WMA pavements. Two-way ANOVA analysis further validated the effects of recycled PET and Sasobit (R) additives on the asphalt's mechanical properties. Additionally, the environmental and cost impacts of using these materials were assessed, highlighting their sustainability. The PET and Sasobit (R) combination, though initially costly, enhances durability, reduces maintenance, and lowers energy consumption, emissions, and hazardous waste, offering cost-effectiveness and improved sustainability. This study provides a promising, cost-efficient, and eco-friendly approach for developing durable asphalt pavements, offering a valuable solution for the future of road construction.

This study examined the effects of microwave treatment on the durability and mechanical characteristics of asphalt mixtures with magnetite as filler. The moisture susceptibility of asphalt mixtures was evaluated using the adjusted Lottman test. The healing capability of asphalt mortars was assessed by performing flexural failure tests, microwave heating, and repeated bending failure. For asphalt mixtures, two approaches were utilized to evaluate healing capacity: one focused on fatigue, assessing microwave healing after subjecting samples to 50 % fatigue life, and the other focused on fracture, measuring strength recovery in semicircular samples through repeated breaking and healing cycles. Results indicated that the increased magnetite filler enhanced Indirect Tensile Strength (ITS) and tensile strength ratio (TSR), demonstrating improved moisture susceptibility. In addition, the magnetite filler improved the fatigue life, strength, and microwave healing rate. Specifically, fracture toughness increased by 24.5-71.7 % across multiple cycles, whereas the fracture-based healing indices improved by 12.3 %, 13.4 %, and 16.6 % in subsequent cycles. The fatigue healing indices also improved significantly with increasing the magnetite content. The study concludes that replacing all mineral fillers with magnetite is optimal for enhancing the mechanical and self-healing ability of asphalt mixtures.

This study investigates the effects of incorporating nano-carbonate calcium (NCC) on the temperature-dependent fracture performance of hot mix asphalt mixtures. Testing was conducted at 0 degrees C, 10 degrees C, and 20 degrees C using indirect tensile strength, resilient modulus, dynamic modulus, and three-point semicircular bending tests on mixtures containing two distinct neat asphalt binders and NCC particles at concentrations of 4% and 6% as binder additives. Fracture characteristics were assessed through dissipated creep strain energy, maximum cohesive strength, and cohesive fracture energy using a finite element cohesive zone model (CZM). Results indicate that the addition of NCC enhances the crack resistance and flexibility of modified asphalt mixtures, particularly evident in dissipated creep strain energy. CZM parameters, validated through three-point bending monotonic fracture tests, demonstrate increased cohesive strength values at all testing temperatures. However, cohesive fracture energy exhibits enhancement only at 20 degrees C, declining at the other two testing temperatures across all mixtures.

Asphalt mixtures play a critical role in transportation infrastructure, with cracking representing a significant challenge in asphalt pavements. This literature review delves into the field of fracture mechanics within asphalt pavement engineering, highlighting the various factors that influence the fracture resistance of asphalt mixtures. The choice of materials in asphalt composition is vital; incorporating coarser aggregates, stiffer binders, fibers, and specific additives can enhance the mixture's fracture resistance. Additionally, the geometry of test specimens and the loading conditions during testing significantly affect the measured fracture resistance, with thicker specimens generally demonstrating improved fracture toughness. Environmental factors also play a crucial role; phenomena such as freeze–thaw cycles and rising temperatures can substantially reduce the overall fracture toughness of asphalt pavements. A comprehensive understanding of these factors is essential for developing effective pavement design and maintenance strategies, ultimately contributing to the longevity and durability of asphalt pavements.

Pavement researchers have sought to develop more environmentally friendly asphalt that effectively mitigates the consumption of natural resources and maintenance costs. They have noted that using durable asphalt with improved self-healing can achieve these goals. Technologies like warm-mix asphalt or calcium capsules can help the economy and substantially reduce environmental impact. These aims can be attained with technologies such as warm-mix asphalt (WMA) and calcium alginate capsules. This study evaluates the effect of Sasobit, which is utilized as a typical modifier for WMA, long-term aging (LTA) and calcium alginate capsules on the self-healing performance and mechanical properties of asphalt mixture by using different tests such as resilient modulus, indirect tensile strength (ITS), fracture test on semicircular bending (SCB) specimens and edge notched disk bend (ENDB) specimens. According to Findings, long-term aging and Sasobit negatively affect the self-healing performance of mixtures, although capsules improve it. Also, ENDB specimens have lower healing values than SCB specimens; however, due to longer crack length, ENDB specimens have more capsules incorporated in healing performance compared to SCB specimens. As a result, this paper notes that the properties of asphalt binder not only have a great effect on the self-healing performance of the mix but also have a significant impact on the action of capsules on healing cracks.

Pavement is one of the essential foundational elements of transportation infrastructures. Ensuring the durability and significant quality of pavement surfaces is crucial for both road agencies and users globally. Stone mastic asphalt (SMA) has emerged as a global choice, presenting high quality. SMA mixtures necessitate additives due to their coarse aggregate and bitumen drainage tendencies. This research addresses the challenge of water infiltration compromising bitumen-aggregate bonds to investigate the impact of antistripping nanomaterials on the moisture susceptibility and rutting resistance of SMA by employing limestone and silica aggregates, bitumen, and Evonik and Zycotherm as nanomaterial additives. Various tests on asphalt samples encompassed resilient modulus, indirect tensile strength, dynamic creep, and the Texas boiling test. The results affirmed that these materials act as antistripping additives, successfully reducing the moisture susceptibility of asphalt mixtures. Adding these additives has a less significant effect on limestone aggregates than on silica aggregates because limestone aggregates generally have suitable moisture resistance, and the effect of Evonik on limestone aggregates is negligible. However, these additives improve the performance of silica aggregates against moisture susceptibility. Additionally, the samples with 0.1% Zycotherm and 0.35% Evonik increased the load-bearing capacity of these mixtures due to better bonding between aggregates and bitumen, finally resulting in a thinner pavement design. Therefore, based on comprehensive evaluations in this research, opting for 0.1% Zycotherm proves more advantageous than opting for 0.35% Evonik to optimize SMA properties, which contributes to advancements in sustainable pavement technologies.

Comprehensively evaluating the fracture behavior of asphalt pavement is a crucial method that helps pavement engineers consider factors such as the effects of materials, environmental conditions, and traffic loading during the design and construction process, with the ultimate goal of creating a durable asphalt pavement resistant to cracking. This study introduces the potential of incorporating recycled Polyethylene Terephthalate additive (PA) into Warm Mix Asphalt (WMA) as a promising and innovative strategy in pavement engineering to enhance the cracking resistance of asphalt pavement. Three primary objectives of this study: first, to reduce the accumulation of PET by recycling and reusing them; second, to use green and eco-friendly methods and materials, such as WMA technology and PA in mixture design; and third, to achieve an ecofriendly, durable asphalt pavement that resists cracking by combining WMA and PA. For these aims, mixtures were prepared with varying PA content (0 %, 1 %, and 2 % by binder weight) and Sasobit (R) (3 % of binder weight). The modified asphalt mixtures were tested for fracture performance using the Edge Notched Disc Bend (ENDB) test. Two loading modes (Mode I and Mode II) were applied at three temperatures (-15 degrees C, 0 degrees C, and +25 degrees C) to evaluate fracture properties, including fracture toughness, fracture energy, balanced cracking index, and tensile strength. The results demonstrated that mixtures containing Sasobit (R) and PA, either individually or in combination, exhibited significantly superior cracking resistance compared to conventional mixtures. Additionally, various loading and environmental conditions were found to have a substantial impact on the cracking resistance of Hot Mix Asphalt (HMA) and WMA mixtures. Statistical analysis identified the optimal formulation as 3 % Sasobit (R) and 2 % PA, which provided the best cracking resistance across different conditions. This sustainable approach not only prolongs the lifespan of pavements but also contributes to reducing environmental impact by repurposing plastic waste.

This study focuses on predicting the number and severity of rural accidents using nine accident-related variables by the multi-layer perceptron (MLP) approach as a type of artificial neural network modeling method. The models were developed using the input parameters of shoulder width, roadway width, roadside hazard, access density, passing zone ratio, speed limit, pavement condition index, shoulder rumble strips, and centerline rumble strips. MLP models were created based on accident data that occurred from 2019 to 2020 on the Tehran–Qom and Tehran-Saveh rural roads in Iran. In order to achieve the highest accuracy, twenty MLP models have been built with various structures. The MLP model, consisting of a multilayer feedforward network with hidden sigmoid and softmax output, has been used in this study. In this regard, an attempt was made to present an optimum theory to select the best model. The most accurate model was chosen based on the R-value and root mean square error (RMSE), mean absolute error (MAE), f, SD, and R2. Results indicated that the R-value obtained from the optimum model was 0.912, representing the accurate performance of the selected model. In addition, access density, roadside hazard, and roadway width were identified as the most significant variables.

This study investigates the acoustic performance and dynamic response of cracked, viscoelastic porous asphalt pavements under moving loads and variable thermal conditions. Realistic pavement cracks are modelled using an advanced line spring model with fracture compliance coefficients. The novelty lies in the synergistic integration of a heterogeneous triple-porosity media model, a non-uniform depth-dependent temperature profile, and an advanced fracture mechanics-based line spring model with arbitrary crack orientation. Variations in temperature that are uniform, linear, and nonlinear with respect to the thickness layer axis are taken into account. The governing equations are derived by Hamilton's principle and solved analytically via Fourier-Laplace transforms. The acoustic pressure is first-time predicted through Rayleigh integral analysis. Durbin's numerical inversion validates the model's accuracy versus sophisticated finite element simulations. Parametric analysis offers new insights into the effects of crack length, pore size distribution, loading frequency, and thermal gradients on noise pollution and fatigue cracking. The integrated chemo-thermo-mechanical modelling enables optimal structural design and accelerated pavement testing to limit acoustic radiation and premature failure in porous asphalt pavements. It allows for the development of noise-reducing porous asphalt mixtures by modifying aggregate gradation, binder content, and air void distribution.

Since asphalt pavement bleeding and raveling are significant threats to road safety, comfort, and service life, timely and accurate detection of them is desirable and cost-effective to develop pavement maintenance programs. Moreover, due to the fact that both of these distresses (i.e., raveling and bleeding) affect the texture of pavements, simultaneous classification of these distresses can provoke challenges. Thus, this study explores efficient texture analysis of 2D images for bleeding and raveling detection using tree-based ensemble methods. To this end, two scenarios of feature extraction are taken into account using Histogram Equalization (HE), Local Binary Pattern (LBP), and Gray-Level Co-occurrence Matrix (GLCM) techniques. Based on these two feature sets, four tree-based ensemble methods were evaluated for classifying the three classes of Bleeding, Raveling, and NoBleeding & No-Raveling. The results confirmed that Feature Set B which derived from the integration of HEGLCM and LBP-GLCM feature extraction provided the most favorable outcome, and gained the high performance of F1-Score congruent to 97 %. Finally, Convolutional Neural Network (CNN) models were constructed using the collected dataset and compared to the proposed method.

This study evaluates the cracking resistance of recycled asphalt pavement (RAP) mixtures including waste engine oil (WEO), crumb rubber (CR), and steel slag aggregates using the Illinois flexibility index test (I-FIT). Performance indices, derived from both this study and another, were predicted by comparing deep neural network (DNN), linear, and polynomial regression models via a k-fold cross-validation process. I-FIT test results demonstrated that WEO, steel slag aggregates, and specific CR proportions enhance cracking resistance while RAP utilisation decreased it. In terms of modelling, it was found that the most appropriate prediction model for the dataset structure of this study is the deep neural network model. The DNN model sensitivity analysis identified WEO as key for high and intermediate temperature (I-FIT) performance. Meanwhile, CR significantly impacted intermediate temperatures (IDEAL-CT), while RAP influenced moisture susceptibility. This model proves reliable and efficient, suggesting its potential for predicting the performance of recycled mixtures.

The reason for conducting this research was to examine asphalt mixtures and the influence of additives obtained from recycled Polyethylene Terephthalate (PET) on their mechanical properties. Due to this, after the chemical recycling of PET, the substance resulting from the chemical reaction was added to the asphalt binder in different contents. In order to evaluate the mechanical performance of mixtures containing additives, a variety of different mechanical tests were carried out. In order to accomplish this goal, tests including dynamic creep, indirect tensile strength (ITS), and indirect tensile modulus (IDTM) were carried out to determine rutting, moisture susceptibility, and resilient modulus, respectively. The SCB test is used to determine how well a material resists cracking when subjected to low temperatures. The results showed that the addition of an additive derived from recycled PET could increase the rutting resistance, significantly improve resistance against moisture damage and increase cracking resistance at low temperatures. In accordance with the findings of the indirect tensile strength tests, indirect tensile modulus and SCB was the best performance related to the asphalt mixture containing 2% recycled PET. However, this result was different in the dynamic creep test, and the asphalt mixture containing 1% additive showed the best performance. The results of data analysis with one-way analysis of variance showed that all the data obtained in this study are statistically significant considering the confidence factor of 95%, so it can be said that the addition of recycled PET additive has a significant effect on the mechanical properties of the asphalt mixture.

Increasing amount of plastic waste (PW) poses a global challenge that necessitates multifaceted strategies. Repurposing PW in asphalt pavement is a sustainable strategy with extensive benefits, but there are several challenges that need to be overcome. This systematic review aims to examine three significant aspects associated with plastic-modified asphalt: environmental and health considerations, performance and technical properties, and cost.-effectiveness and economic feasibility. The environmental and health impacts of using PW in asphalt were particularly focused on the release of carcinogenic compounds and harmful fumes like polyaromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs), microplastic pollution, and climate impact. Environmental challenges and potential health risks associated with the use of PW in asphalt production were analyzed and indicated. Afterwards, the effects of different plastic types on the fatigue and rutting resistance of asphalt pavement are investigated. While many types of PWs show potential for enhancing rutting and fatigue performance, conflicting results have been observed for certain plastics. Some PW types, such as polyvinyl chloride (PVC), polypropylene (PP), polystyrene (PS), low-density polyethylene (LDPE), and high-density polyethylene (HDPE), have been shown to yield inconsistent results. Lastly, factors that are recognized to have an impact on the cost-effectiveness of plastic-modified asphalt include the collection and processing costs, asphalt materials price and availability, incorporation method, and possible changes in the asphalt’s lifespan. The findings of this review help researchers to identify current gaps and aid stakeholders in making informed decisions towards more environmentally friendly, high-performance, and economically viable approaches to asphalt production.

The use of waste materials and Warm Mix Asphalt (WMA) technology in asphalt pavements has several advantages. Low-temperature cracking is one of the most common failures of WMA mixtures. Hence, the primary objective of this study is to evaluate the fracture toughness and fracture energy of asphalt mixtures containing a chemical WMA additive and steel slag aggregates. The steel slag aggregates were substituted at percentages of 0

Through experimental tests, this paper investigated the effectiveness of microwave healing on asphalt mixtures containing iron powder (IP) filler to improve durability and enhance mechanical properties. The moisture sensitivity of the asphalt mixes with varying iron powder filler contents was measured using the modified Lottman test. For evaluating the asphalt mixture healing ability, two complementary methods were used: the fatigue-based method, derived from the ability of microwave healing of asphalt mixture samples damaged up to 50% level of indirect tensile fatigue (ITF), and the fracture-based method, obtained from the strength recovery rate of broken semi-circular samples by applying consecutive breaking-healing cycles. The results showed that the greater the quantity of iron powder filler in the asphalt sample, the greater the sample’s indirect tensile strength and TSR ratio, indicating that IP had a positive effect on moisture sensitivity. The findings also indicated that utilizing iron powder as a filler positively strengthens the fatigue life, increases the toughness, and increases the microwave healing indices (both fatigue and failure approaches). Finally, according to the study results, substituting 70% iron powder as the filler is the most suitable option for improving the mechanical and self-healing characteristics of asphalt mixes.

The demand for nondestructive testing techniques (NDTs) that can be implemented continuously and cost-effectively for large-scale study purposes is increasing. Ground penetrating radar (GPR) as an NDT method permits the estimation of pavement materials characteristics without disrupting the serviceability of the system. This research used typical pavement materials for constructing load-bearing layers (base and subbase) for the GPR laboratory tests. A 2 GHz GPR antenna was applied to execute the tests by changing three essential variables of the material: water content, compaction and clay content. Machine learning and interactive methods were innovatively utilised to model the collected data. As a result, a multivariate non-linear empirical function is proposed by the interactive procedure. Furthermore, the machine learning modelling (SVM method) with R-2 of 0.91 indicates promising results to evaluate the pavement layers' properties. Machine learning can enhance the speed and accuracy of analysis when faced with multi-variables and extensive data.