Pavement Performance Research Articles

A Final Study: The Role of Plastic-Modified Bitumen in Enhancing Durability and Sustainability in Road Construction

Abstract: This study systematically evaluates the influence of integrating varying percentages of plastic waste into bitumen on the mechanical properties and performance characteristics of bituminous pavements. Experimental results indicate that the incorporation of plastic waste enhances the performance of bitumen up to an optimal threshold of 8% by weight; exceeding this concentration results in negligible improvements or deterioration in performance. Rigorous laboratory assessments, including Dynamic Shear Rheometer (DSR) analyses, demonstrate that plastic-modified bitumen exhibits a significantly elevated complex modulus (G*) and a reduced phase angle (δ) in comparison to unmodified bitumen, with the 8% modification yielding the most favourable outcomes. Enhanced Marshall Stability, improved flow values, reduced penetration, and increased softening points further signify superior resistance to load and thermal variations. The elevated viscosity of plastic-modified bitumen contributes to enhanced pavement strength and durability. Future investigations should encompass additional evaluations, such as ductility, elastic recovery, and flash/fire point tests utilizing the wet process, alongside an exploration of the dry process involving the coating of aggregates with shredded plastic. The findings substantiate that the incorporation of plastic waste into bitumen not only augments pavement performance but also presents a viable eco-friendly solution for plastic waste management, thereby fostering sustainable construction methodologies. The findings confirm that using plastic waste in bitumen improves pavement quality and offers an eco-friendly solution for plastic waste management, promoting sustainable construction practices.

Lime Stabilization of Tropical Soil for Resilient Pavements: Mechanical, Microscopic, and Mineralogical Characteristics.

Lime stabilization is a sustainable technique due to its use of local materials, increased durability, reduced maintenance, and improved resistance to water action. This paper examines the impact of lime stabilization on the mechanical, microscopic, and mineralogical properties of a tropical soil. Two types of lime, calcitic and dolomitic, were tested at 3% and 5% by weight. Compressive, indirect tensile and flexural test results and statistical analysis revealed that calcitic lime mixtures had higher strength and stiffness, whereas dolomitic lime mixtures exhibited greater deformability with higher tensile strain at break. Scanning electron microscopy indicated that the soil's porous matrix closed within 7 days for both lime types due to flocculation, with increased matrix interlocking over time. The calcitic lime mixture developed a more closed matrix compared to the dolomitic lime, which showed weaker cementing. X-ray diffraction analysis indicated higher consumption of clay minerals and a notable reduction in calcium hydroxide peaks in the lime-treated soils. The study concludes that calcitic lime provides better pavement performance for stabilizing the soil, enhancing its engineering properties while also being sustainable by reducing the need for raw material extraction and improving resilience to climate-related issues such as floods.

Fracture properties of asphalt mixtures containing high content of reclaimed asphalt pavement (RAP) and eco-friendly PET additive at low temperature

Low-temperature cracking is one of the main types of distress that affects asphalt pavement performance over its service life. At the same time, the accumulation of plastics, especially polyethylene terephthalate (PET), and the potentially harmful effects of these plastics requires special attention in order to find ways to reduce them. Previous studies have paid less attention to the impact of PET on low-temperature cracking in asphalt mixtures and the simultaneous interaction between PET and reclaimed asphalt pavement materials (RAP) on fracture behavior of asphalt mixture. In this study, a value-added substance called PET Additive (PA), which is extracted from chemical processing of PET was blended with asphalt binder at different dosages (1–3 %) to use in the mixture of hot mix asphalt (HMA). Reclaimed Asphalt Pavement (RAP) was also added to the HMA mixtures at rates of 25 and 50 % by aggregate mass and the resulting asphalt mixtures were tested to characterize the load carrying ability and cracking resistance indexes of the modified HMA mixtures. Circular shaped test specimens with different mixture types and different geometries were manufactured. Results showed that the asphalt mixture containing PA has better performance than the control mixture; among all mixture types, a mixture containing 2 % PA and 25 % RAP had the better fracture resistance at low temperatures. Finally, the results demonstrate that the fracture behavior in Edge Notch Disc Bend (ENDB) and Semi-Circular Bend (SCB) specimens had similar trends.

Evaluating the influence of flexural strength on rigid pavement performance under simulated aircraft traffic

A full-scale airfield pavement test section was constructed and trafficked by the US Army Engineer Research and Development Center to investigate the impact of substandard flexural strength portland cement concrete (PCC) on the pavement structural support requirements under simulated aircraft loading conditions. The substandard pavements were representative of those that may be encountered in remote locations where there may be a lack of locally available competent materials, standard construction equipment, or a skilled labor force. The test section consisted of two PCC surface thicknesses each constructed with a standard airfield flexural strength PCC mixture and a low flexural strength PCC mixture and both a dowelled and non-dowelled joint. The test items were trafficked with a dual-wheel P-8 aircraft test gear mounted on a heavy-vehicle simulator. The outcomes of the accelerated traffic tests showed a significant reduction in PCC pavement cracking performance resulting from the reduction in flexural strength. Instrumentation response data were analyzed to corroborate observed surface cracking. The field data were compared to current Department of Defense pavement design and evaluation procedures, and it was found that current procedures underpredicted observed performance in excess of 90 percent. These estimations may be overly conservative and may exceed a level of conservatism appropriate in a remote environment. The observed conservatism was attributed to simplifying assumptions and empirical correlations made in early development of the design and evaluation procedure.

Multi-Criteria Decision-Making Framework (AHP-TOPSIS): Pavement Preventive Maintenance Case Study for Ordinary National Trunk Highways

Pavement maintenance and rehabilitation decision-making needs to weigh multiple strategic goals to achieve sustainable development through the pavement maintenance management system. Making decisions regarding pavement preventive maintenance is both intricate and costly. This study introduces a multi-criteria decision-making framework aimed at enhancing the scientific basis of such decisions. The framework first establishes an evaluation system for preventive maintenance strategies by considering three primary evaluation criteria—service functionality, pavement performance, and economic benefits, and then identifies nine specific evaluation indicators to influence these criteria, with a comparison matrix constructed to determine the weight of each indicator in relation to the maintenance decision hierarchy. Following this, the technique for order preference by similarity to ideal solution (TOPSIS) is employed to prioritize four commonly utilized preventive maintenance strategies. The results reveal that pavement condition and maintenance costs are the most influential factors in determining the appropriate preventive maintenance strategies for national highways. The priority rankings for the four strategies—slurry seal, micro-surfacing, chip seal, and ultra-thin overlays—are found to be 56.12%, 63.86%, 12.12%, and 83.52%, respectively, with ultra-thin overlays identified as the optimal choice for second-class highways. The decision-making model utilized in this study enables a multi-dimensional analysis, reducing the subjectivity inherent in expert evaluations and facilitating the prompt identification of the most suitable maintenance strategy.

A Comparative Study of Pavement Roughness Prediction Models under Different Climatic Conditions

Predicting the International Roughness Index (IRI) is crucial for maintaining road quality and ensuring the safety and comfort of road users. Accurate IRI predictions help in the timely identification of road sections that require maintenance, thus preventing further deterioration and reducing overall maintenance costs. This study aims to develop robust predictive models for the IRI using advanced machine learning techniques across different climatic conditions. Data were sourced from the Ministry of Energy and Infrastructure in the UAE for localized conditions coupled with the Long-Term Pavement Performance (LTPP) database for comparison and validation purposes. This study evaluates several machine learning models, including regression trees, support vector machines (SVMs), ensemble trees, Gaussian process regression (GPR), artificial neural networks (ANNs), and kernel-based methods. Among the models tested, GPR, particularly with rational quadratic specifications, consistently demonstrated superior performance with the lowest Root Mean Square Error (RMSE) and highest R-squared values across all datasets. Sensitivity analysis identified age, total pavement thickness, precipitation, temperature, and Annual Average Daily Truck Traffic (AADTT) as key factors influencing the IRI. The results indicate that pavement age and higher traffic loads significantly increase roughness, while thicker pavements contribute to smoother surfaces. Climatic factors such as temperature and precipitation showed varying impacts depending on the regional conditions. The developed models provide a powerful tool for predicting pavement roughness, enabling more accurate maintenance planning and resource allocation. The findings highlight the necessity of tailoring pavement management practices to specific environmental and traffic conditions to enhance road quality and longevity. This research offers a comprehensive framework for understanding and predicting pavement performance, with implications for infrastructure management both locally and worldwide.

Study on Fatigue Performance and Rutting Prediction Model of Steel Slag Asphalt Mixture

Steel slag, a significant industrial waste, poses environmental and land issues due to its accumulation. This research explores using steel slag to replace natural aggregates in steel slag asphalt mixture (SSAM) at varying levels by weight: 25%, 50%, 75%, and 100%. The research evaluated the pavement and fatigue performance of SSAM, noting that dynamic stability (DS) peaked at a 75% slag content. Although low-temperature flexibility decreased, it remained within acceptable limits. The mixture met or exceeded Chinese specifications for resistance to water and traffic stress. Fatigue life varied with slag content, decreasing at high levels due to increased stiffness and stress. A rutting prediction model for SSAM was developed, utilizing a back propagation neural network for accurate rut depth forecasts, demonstrating the model's precision with a fit of 0.99744. This study suggests optimized slag content enhances SSAM performance, offering a sustainable approach to managing steel slag.

Trends in the incorporation of nanomaterials in asphalt binders to improve rheological properties

Asphalt binders play a significant role in the performance of pavements. The current volume of traffic and loads on highways contribute to the occurrence of damages that affect the performance and lifespan of the asphalt mix. In this context, the development of optimized materials can help reduce damages and increase the lifespan of the pavement. One way to improve asphalt performance, that is, improving rheological, mechanical, and durability properties, is by incorporating nanomaterials. Through a systematic literature review and bibliometric analysis, this study aimed to verify the recent scientific scenario on the subject, aiming to identify trends and prospect content for future work. Thus, bibliometric indexes were analyzed, and the selected articles from the systematic search were summarized, which allowed the identification of the research objectives, the incorporated materials, and their optimal contents. Additionally, the asphalt matrices used, the tests performed, and the highlights regarding mechanical and rheological gains were identified. Finally, it was concluded that the study achieved its objective, contributing to decision-making in the prospecting of themes for future research.

A novel life-cycle analysis approach using pavement performance curves with cost and performance considerations

ABSTRACT The life-cycle duration (TLC) is typically assumed constant in pavement life-cycle analysis. The added scientific value of this paper is that (TLC) is considered a variable parameter to be estimated from the performance curve using a variable terminal condition rating. A variable (TLC) requires using the equivalent annual value (EAV) instead of the net present value for cost estimation. The life-cycle performance (LCP) curve is constructed using two routine maintenance cycles separated by one major rehabilitation action. The time parameters associated with LCP curve are estimated from the inverse performance function based on the initial, present and terminal condition ratings. The equivalent annual cost and performance associated with a particular LCP curve are used to compute cost/performance (C/P) ratio for optimal maintenance and rehabilitation (M&R) plan selection. The EAV represents the costs of two routine maintenance cycles and one major rehabilitation action. Sample results obtained from three case studies have indicated the reliability of the proposed LCA approach in yielding optimal M&R plans. At the project-level, the optimal M&R plan associated with 7 m/km terminal IRI value resulted in (0.949) minimal (C/P) value. However, the optimal M&R plan with 3.25 terminal PSI yielded (1.50) minimal (C/P) value.

Microwave self-healing characteristics of the internal voids in steel slag asphalt mixture subjected to salt-freeze-thaw cycles

Microwave heating technology can be used to repair freeze-thaw (F-T) cycle damage and cracks caused by the use of snow melting salts and de-icers in winter. This study utilized three different gradations of asphalt mixtures: AC-13, SMA-13, and OGFC-13, and enhanced their microwave absorption performance with steel slag (SS). The heating uniformity was evaluated through surface and internal temperature tests. Additionally, the mechanisms of damage and healing of the asphalt mixtures under salt freeze-thaw (S-F-T) damage conditions were explored using S-F-T cycles test and X-ray computed tomography scans (CT). The results showed that OGFC-13 exhibits a significantly higher rate of temperature increase compared to the other two types due to its stronger wave absorption capacity. The thermal hysteresis caused by steel slag leads to uneven spatial temperature distribution. The study recommends an optimal microwave heating time of 40 s for SS asphalt mixtures, which has minimal impact on the mixture structure, by defining an evaluation method for the uniformity index and local overheat ratio. After undergoing S-F-T cycles, the porosity of all three asphalt mixtures increased, particularly at the top and bottom of the specimens. Among them, OGFC-13 exhibited the poorest durability under S-F-T conditions, with the S-F-T cycles having a significant impact on medium-sized voids (0.15–0.6 mm). After microwave heating, AC-13 and SMA-13 showed good repair effects, with porosity levels returning to their initial states. For large voids (>2.36 mm) in OGFC, microwave heating may not effectively reduce the number of voids. Additionally, the healing rate of mixture specimens at certain mid-height ranges is higher due to elevated surface temperatures in these areas, making it especially effective in repairing F-T damage. This study shows that microwave heating of SS asphalt mixtures can improve the durability of pavement in cold regions. However, implementation challenges include the need for specialized equipment and potential uneven heating. Future research should explore optimizing microwave heating techniques to minimize local overheating and investigate the long-term performance of microwave-repaired asphalt pavements under various environmental conditions.

Pavement performance and model studies with modified bitumen binder

Flexible pavements experience premature deterioration due to several factors, such as high volumes of traffic, repeated wheel loads, overloading, adverse weather conditions, inferior quality of materials, and other related issues. One of the most commonly found types of distress is rutting, which severely affects pavement performance; hence, the prediction of rutting behaviour is crucial. Research has been done by adding various industrial wastes, chemicals, additives, and modifiers such as rubber, natural rubber, polymers, and waste plastic into the bitumen. These materials are expected to have a substantial impact on enhancing the strength, durability, and performance of pavement while simultaneously reducing the cost of construction. The present research deals with a laboratory investigation of bituminous mixes using both Marshall stability and rutting tests. The performance tests were carried out by Roller Compactor cum Rut Analyzer (RCRA) equipment and Finite Element (FE) analysis in ABAQUS. The experimental findings show that the modified bitumen exhibits 48% greater strength and 20% more resistance to rutting than the conventional bituminous mixes. The model analysis was successfully validated by experimental results. The findings of the research resulted in the development of a mathematical equation that helps to calculate in-service pavement rut depth.

Resilient roads in challenging terrain: a case study of Siddhartha highway in Nepal

Nepal is a country known for its diverse and challenging topography, and it relies heavily on a robust road infrastructure network to connect its remote regions and urban centers. This study addresses the critical need for enhanced road safety and infrastructure resilience on the Siddhababa road section of the Siddhartha Highway, Nepal, notorious for its high accident rates and susceptibility to landslides. Given the road's strategic importance in connecting remote regions and its challenging topographical conditions, our research aimed to identify the most suitable pavement type to mitigate these issues. Through a detailed examination incorporating eight different soil tests, alongside evaluations of traffic loads, weather conditions, and existing pavement performance, we adopted a comparative analysis methodology to assess the viability of flexible versus rigid pavements within this unique context. Results revealed that the soil composition and environmental conditions of the Siddhababa section significantly influence pavement performance, with specific gravity, moisture content, and California Bearing Ratio (CBR) tests indicating a nuanced suitability for both pavement types under varying circumstances. Our analysis concluded that, despite the economic and staged reinforcement benefits of flexible pavements, the durability, safety, and maintenance considerations favor the adoption of rigid pavement for the Siddhababa road section. However, acknowledging the economic constraints, a hybrid approach is recommended, emphasizing rigid pavements for the most vulnerable sections and flexible pavements elsewhere. This study contributes to the pavement engineering field by providing a model for pavement type selection in mountainous regions, aiming to enhance road safety and durability amidst challenging environmental conditions.

A state-of-the-art assessment in developing advanced concrete materials for airport pavements with improved performance and durability

Concrete materials, as the main component of airport pavement, provide essential attributes such as strength and toughness required by airport pavement. With the rapid development of air transportation, the compression and cracking resistance performances required by airport pavement are dramatically boosted with the ever-growing weight and the frequency of aircraft. In recent years, high-performance concrete materials with excellent properties have shown great potential in improving durability and extending the service life of pavement. This review presents a-state-of-the-art assessment guided by the pavement performance requirement, material design mechanism, application cases and future application guidance of advanced cementing materials in airport pavement improvement. Firstly, the functions of each structural layer of airport pavement and their effects on the surface layer are summarized. Then, the design mechanism and application cases of advanced concrete materials were summarized with the future application guidance to be given. Finally, the application scenarios, testing mechanism and testing effect of nondestructive testing methods for airport pavement performance evaluation are summarized. This review provides a comprehensive assessment of the development and applications of advanced concrete materials for airport pavement, paving avenue to achieve high performance and long service life of airport pavement.

Comparative life cycle assessment of three types of crumb rubber modified asphalt under different system boundaries

This study employs a life cycle assessment (LCA) to quantify the environmental impacts of three crumb rubber recycling technologies in asphalt rubber (AR) mixtures: wet, dry, and terminal blend. The analysis identifies key factors affecting their environmental performance across the life cycle. Results were characterized into climate change, stratospheric ozone depletion, fine particulate matter, terrestrial acidification, marine eutrophication, freshwater ecotoxicity, human toxicity, and Land use. Dynamic rankings of the three AR technologies along their life cycle stages in each impact category would enable identification of the influencing factors and provide reference for the further improvement. This study reveals that dry technology is likely to have the most significant environmental impacts across all categories (51.85 %-100 %), whereas terminal blended technology generally presents the lowest impact (51.85 %-88.89 %), with the exception of freshwater ecotoxicity (33.33 %) and human toxicity (22.22 %), where wet technology shows the least impact. The analysis underscores the importance of asphalt mixture designs, with appropriate binder content, potential reduction in surface course thickness, and reduced maintenance frequency, as strategies to enhance the environmental performance of AR technologies. The study concludes that the environmental performance of AR pavement is highly dependent on their in-service durability, with scenario-based analysis indicating that adequate durability ensures environmental effectiveness.

Machine learning modeling of pavement performance and IRI prediction in flexible pavement

Machine learning modeling of pavement performance and IRI prediction in flexible pavement

Performance evaluation of surface treatment waste glass as aggregate in asphalt mixture

Surface modification is a crucial strategy for enhancing the pavement performance of waste glass hot mix asphalt (HMA) mixtures. This study conducts a comparative analysis of various surface modification techniques to pinpoint the key factors that influence the interfacial interaction between waste glass and asphalt. To assess the performance of asphalt mixtures containing surface-treated waste glass, the study employed methods such as Energy Dispersive X-ray Spectroscopy (EDS), boiling water tests, and contact angle measurements, which helped to quantify surface morphology and the effectiveness of different treatments. The evaluation also included assessments of water stability, dynamic stability, small beam bending, and anti-skid properties. Findings revealed that applying a silane coupling agent to the waste glass significantly enhanced adhesion with asphalt, resulting in markedly improved pavement performance. The study identified that incorporating surface-treated waste glass at an optimal proportion of 6 % within the asphalt mixture led to a 42.3 % increase in dynamic stability and a 38.6 % enhancement in anti-skid performance compared to standard mixtures. This research offers a comprehensive evaluation framework for surface modification techniques of waste glass, underscoring its potential to considerably improve road performance.

Evaluating dynamic modulus of cold in-place recycling mixture with foamed bitumen using field core samples

This study evaluates the dynamic modulus of Cold In-Place Recycling with Foamed Bitumen (FB-CIR) pavements, focusing on the influence of various recycled materials—reclaimed asphalt pavement (RAP), reclaimed inorganic binder stabilized aggregate (RAI), and their combination (RAP+RAI). Core samples from three representative FB-CIR projects in China were tested using the MTS-130 system across temperatures of −10°C, 5°C, 20°C, 35°C, and 50°C, and frequencies ranging from 25 Hz to 0.1 Hz. Statistical analysis and the Sigmoidal model were employed to analyze the viscoelastic behavior and establish the master curve for the FB-CIR dynamic modulus. The dynamic modulus of the three FB-CIR mixtures showed pronounced frequency-dependence, decreasing with reduced frequencies, and exhibited temperature sensitivity, with lower values at elevated temperatures. FB-RAI consistently demonstrated higher modulus values due to the hydration of previously unhydrated cement particles, while FB-RAP and FB-RAP+RAI displayed lower values, as RAP behaves similarly to unbound granular material. The construction of the master curve, based on the time-temperature superposition principle, enhanced our understanding of FB-CIR mixtures' mechanical behavior and enabled accurate extrapolation of dynamic modulus values across diverse conditions. Furthermore, FB-RAI's narrow phase angle variation indicates its superior mechanical stability and reduced sensitivity to external changes, making it ideal for areas with extreme climate fluctuations or heavy traffic. The study also identified three distinct phase angle variation patterns in FB-CIR mixtures, underscoring the importance of nuanced pavement design strategies that consider temperature, frequency, and material composition to optimize the performance and durability of FB-CIR pavements.

From ensemble learning to deep ensemble learning: A case study on multi-indicator prediction of pavement performance

Recently, Big data analytics approaches were combined with emerging machine learning techniques, which can provide more sophisticated insights into information-intensive activity. Compared to traditional shallow-architecture machine learning algorithms, Deep learning could excavate more potential information from the raw features. However, its powerful representational capacity relies on the support of enormous samples. The ensemble trees system performs superior on small sample problems due to better generalization capacity. To merge both benefits of deep learning and ensemble tree system, this paper developed a deep ensemble algorithm applied to multiple indicators prediction of pavement performance, including International Roughness Index and pavement 3-layer modulus. The deep ensemble algorithm is developed by merging a deep neural network (DNN) with the decision manifold property of the decision trees (TabNet) into a cascade ensemble system, combined with a sliding window algorithm to extract dependency information from raw data. During the training stage, the Bayesian Optimization Algorithm (BOA) is used to search for the optimal combination of sub-decision makers in the cascade ensemble. And equipped with GPU, it can speed up by 2.6–4.0 times. In the case study of pavement engineering, with sufficient training samples, it can achieve an average accuracy of 98.74 %, higher than DNN (97.49 %) and XGBoost (96.12 %) in predicting pavement indicators. With insufficient training samples, it can achieve an accuracy improvement of 12 % than XGBoost (75 %) and 24.5 % than DNN (62.5 %).

Laboratorial investigation on optical, thermal and pavement performance of biomimetic dark reflective coatings with composite structure for pavement cooling

The surface temperature of asphalt pavement in summer can reach up to 70 °C, which leads to poor outdoor thermal comfort and exacerbates the urban heat island effect. Reflective coatings can effectively reduce pavement temperature, but their intrinsic light color with high reflectance causes safety issues such as glaring. In this study, based on the biomimetic idea of chameleon skin structure, composite pavement coatings for cooling and anti-glare were developed. Their optical properties, thermal behavior, adhesion and skid-resistance performances were investigated. The results showed that near-infrared reflectance of black and grey double-layer reflective coatings could reach 0.66 and 0.70, respectively (58 % higher than single-layer coatings). The optimal mass fraction of perylene black in the upper black/grey coating was 2.94 % and 0.74 %, respectively. The double-layer dark coatings could decrease the temperature by 14 °C at the depth of 3 cm below road surface, which achieved cooling effect close to that of white single-layer reflective coatings. The adhesion between coating and stone was generally higher than the cohesion of asphalt, therefore, opening traffic for a period of time or carrying out micro-milling before coating could improve the abrasion resistance. Due to increase in the thickness of the double-layer coating, the microscopic texture of road surface was reduced, thereby reducing skid-resistance. However, it still met the standard requirements. This study intends to provide a reference for developing pavement coatings that balance cooling and visual safety to mitigate the heat island effect, and improve the sustainability of transportation infrastructure.

Rheological and Aging Properties of Nano-Clay/SBS Composite-Modified Asphalt.

Nano-organic montmorillonite (OMMT) not only inhibits the harmful asphalt fume generation during the production and construction processes of asphalt mixtures but also effectively improves the performance of asphalt pavements. In order to prepare asphalt materials with smoke suppression effects and good road performance, this study selects nano-OMMT and SBS-modified asphalt for composite modification of asphalt mixtures and systematically investigates its road performance. Through the temperature sweep test, the frequency sweep test, the multiple stress creep recovery (MSCR) test, the bending beam rheometer (BBR) test, and the atomic force microscope (AFM) test, the high-temperature rheological properties, low-temperature rheological properties, high-temperature properties and aging resistance of the modified asphalt are studied. The research findings indicate that OMMT can effectively reduce the sensitivity of modified asphalt to load stress and improve its high-temperature rheological properties. SBS-modified asphalt shows increased creep stiffness and a decreased creep rate after OMMT modification, resulting in reduced flexibility and decreased low-temperature crack resistance. After short-term and long-term aging, the complex modulus aging index of OMMT/SBS composite-modified asphalt is lower than that of SBS-modified asphalt, and the phase angle aging index is higher than that of SBS-modified asphalt, demonstrating that OMMT enhances the aging resistance of SBS-modified asphalt. OMMT inhibits oxidation reactions in the asphalt matrix, reducing the formation of C=O and S=O bonds, thereby slowing down the aging process of modified asphalt and improving its aging resistance.