The oil and gas (O&G) sector is a critical energy infrastructure to a Nation’s welfare. As developed as the O&G industry may seem, its aging infrastructure gradually shows numerous challenges to keep up with the growing energy demand, increasing operation costs, and environmental concerns. A robust O&G infrastructure that is risk-free, reliable, and resilient towards expected or unexpected threats can offer an uninterrupted supply of O&G to downstream stakeholders, competitive prices to customers, and better environmental footprints. With the shift towards renewable energy, the notion of sustainable development should be firmly embedded in O&G infrastructure and operations to facilitate the smooth transition towards future renewable energy generation. This paper offers a comprehensive and innovative approach to achieving sustainable development for O&G infrastructure by examining it from a holistic risk, reliability, and resilience (3Rs) perspective. The role of each individual concept and their collective influence on sustainable development in the O&G industry will be thoroughly discussed. Moreover, this paper will highlight the significant impact of the holistic 3Rs approach on sustainable development and propose future research directions. Given the complexity of O&G infrastructure, it is crucial to incorporate sustainable development practices into every dimension of the O&G infrastructure, iteratively and continuously, to achieve the ultimate goal of long-term sustainability. This paper makes a significant contribution to the field by providing valuable insights and recommendations for achieving sustainable development in the O&G industry.

Weather-related events are among the major causes of failure propagation in natural gas pipeline infrastructure. The interaction between multiple natural-force factors, such as temperature, precipitation, and wind, and their unpredictable simultaneous occurrence can intensify the vulnerability of pipeline infrastructure, increasing the likelihood of leaks, ruptures, and mechanical damage. This paper provides a comprehensive review of the combined effect of weather-related events on the failure propagation of pipelines, focusing on the impact of weather-related external force factors and climate change on sustainable pipeline integrity, including corrosion, erosion, and mechanical damage. Additionally, the paper examines various maintenance policies and strategies that can be implemented to mitigate the impact of weather-related failures. The review highlights gaps in existing knowledge and future research directions to enhance the understanding of weather-related failure propagation in natural gas pipeline infrastructure. This paper provides insights into the challenges and opportunities for improving the resilience and sustainability of pipeline infrastructure to weather-related failures.

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.

Pavement construction practices have evolved due to increasing environmental impact and urban heat island (UHI) effects, as pavements, covering over 30% of urban areas, contribute to elevated air temperatures. This study introduces heat-reflective pavements, by replacing conventional black bitumen with a clear binder and pigment-modified clear binders. Titanium dioxide white, zinc ferrite yellow, and iron oxide red pigments are used to give asphalt corresponding shades. The asphalt and bitumen specimens were subjected to thermal analysis in heat sinks, under varying solar fluxes. The pigment dosage was maintained at 4%, according to the weight of the total mix, for all pigment types. The samples were heated and cooled for 3 h and 2 h, respectively. Mechanical testing was conducted to ascertain the impact of temperature variations on both the neat clear binder (C.B) and pigmented C.B and asphalt mixture samples. Wheel tracking and dynamic modulus tests were conducted to evaluate their performance under high temperatures. The results indicate that non-black asphalt mixtures exhibit significant temperature reductions, up to 9 °C, which are further enhanced by pigmented binders, up to 11 °C. It was found that asphalt with a clear or transparent binder demonstrated lower temperatures and faster heat dissipation in extreme conditions. Moreover, C.B asphalt mixtures displayed a rut resistance of 15%, with the pigmented C.B asphalt mixture showing a remarkable rut resistance of 73%, outperforming conventional asphalt. Non-black mixtures, especially C.B + zinc ferrite, showed improved resistance to permanent deformation in dynamic modulus tests.