Incorporation of high content of Reclaimed Asphalt Pavement (RAP) into fresh asphalt mixtures make them prone to thermal cracking and fatigue failure. Rejuvenators are usually recommended to overcome this problem by restoring the aged asphalt binder properties. This study aims to investigate the feasibility of using Mustard oil as a rejuvenator and to evaluate its effectiveness as a rejuvenator by determining the extent to which it restores the chemical and physical properties of aged asphalt binder extracted from RAP. The effect of Mustard oil on physical, rheological, chemical and thermal properties of aged asphalt binder was studied by employing Rotational Viscometer, Dynamic Shear Rheometer, Bending Beam Rheometer, Fourier Transform Infrared Spectroscopy, Thermogravimetric analysis, Gas-Chromatography-Mass Spectrometry and Rolling bottle equipment. Results indicated that Mustard oil effectively restores the properties of aged asphalt binder and can be used as a suitable rejuvenator. Ten per cent of Mustard oil is recommended as an optimum dose for rejuvenation of aged asphalt binder. This dose is based on restoring the RAP binder to match the properties of neat binder having PG64 and is specific to the stiffness of RAP material being used.

Structural health monitoring (SHM) plays an increasingly important role in managing aging, safety-critical infrastructure under growing environmental and operational demands. In recent years, fiber-optic sensors (FOSs) have attracted significant attention for SHM applications due to their immunity to electromagnetic interference, durability in harsh environments, multiplexing capability, and suitability for both localized and fully distributed measurements. In parallel, advances in machine learning (ML) have enabled new approaches for extracting actionable insights from large, high-dimensional sensing datasets. This paper presents a systematic review of FOS-based SHM systems integrated with ML across civil, transportation, energy, marine, and aerospace infrastructures. Following PRISMA 2020 guidelines, peer-reviewed studies were identified and synthesized to examine sensing principles, deployment configurations, data characteristics, and learning-based analytical strategies. Fiber optic technologies are categorized into point-based, quasi-distributed, and fully distributed systems, and their capabilities for capturing strain, temperature, and spatiotemporal structural responses are critically evaluated. ML approaches are examined from a task-oriented perspective, including damage detection, localization, severity assessment, environmental compensation, and prognosis, with emphasis on the alignment between sensing configurations and appropriate learning paradigms. Key challenges remain, particularly regarding large data volumes, environmental variability, limited labeled damage datasets, model generalization, and system-level integration. Emerging directions such as physics-informed and hybrid learning, transfer learning, uncertainty-aware modeling, and integration with digital twins are discussed as pathways toward more robust and scalable SHM systems. By jointly addressing sensing physics and data-driven intelligence, this review provides a structured reference and practical roadmap for advancing intelligent FOS-based SHM in next-generation infrastructure.

Climate change significantly impacts transportation infrastructure, particularly asphalt pavements. Similarly, the heat absorption of paved surfaces, especially conventional black pavements, significantly intensifies the urban microclimate. Paved surfaces, including asphalt pavements, account for over 30% of the covered surfaces and are vulnerable to rising temperatures, which cause not only pavement distress, such as rutting and cracking, but also urban heat islands (UHI). Sustainable pavement solutions, specifically colored pavements, have been investigated for their potential to mitigate these effects. This review presents an extensive overview of current pavement technologies, emphasizing conventional asphalt’s economic, environmental, and functional characteristics. A discussion of the benefits and challenges of colored pavements is also provided, including their ability to reduce UHI, enhance safety, and contribute to sustainable urban growth. This paper discusses advancements in pavement material science, the use of recycled materials, and the application of reflective coatings, providing insights into sustainable infrastructure development. Transitioning from conventional black pavements to sustainable colored alternatives is not merely a matter of material choice but a strategic transition toward resilient urban planning. Increasing demand for environmentally friendly infrastructure could prompt the construction industry to adopt colored pavements as a tool to promote environmental stewardship.

Adhesion and moisture damage are significant factors in the early failure of pavements. This study examined the adhesion and moisture resistance of three types of binders (40–50, 60–70, and 80–100 pen bitumen) modified with paraffin wax (PW), hydrated lime (HL), and low-density polyethylene (LDPE) at dosages of 1% and 2% by weight of the binder. The Bitumen Bond Strength (BBS) test was performed using the Pneumatic Adhesion Tensile Testing Instrument (PATTI) to measure Pull-Off Tensile Strength (POTS) and determine the type of failure following dry and wet conditioning. Additionally, the mixture was tested for moisture susceptibility using the Rolling Bottle Test (RBT). The RBT results showed that adding LDPE and HL to the control binder increased bitumen coverage, indicating greater resistance to moisture damage. In contrast, adding PW reduced bitumen coverage, indicating higher susceptibility to moisture damage. Based on the BBS test, LDPE and HL-modified bitumen developed greater bond strengths as POTS values increased, while PW-modified bitumen developed decreased bond strengths as POTS values decreased.