Advances in Civil Infrastructure Engineering

1. Introduction

Civil infrastructure currently faces many challenges, mainly concerning the environment and society. Extreme events associated with climate change and the general degradation of natural habitats are becoming more frequent and significantly impacting society. The Sustainable Development Goals (SDGs) set by the United Nations are more urgent than ever. Civil engineering can make a significant contribution to meeting current and emerging natural and social needs [1,2,3,4].

Civil infrastructures represent an extremely valuable asset. The availability and quality of buildings, bridges, dams, tunnels, roads, railways, and airfields are crucial for the development of society. However, civil infrastructures are very exposed and susceptible to various natural actions. Green and intelligent technologies can promote sustainability and resilience, mitigating environmental and social impacts.

Digitization is currently a fundamental contribution to more sustainable and resilient infrastructures. Applications of artificial intelligence (AI) in the design, construction, and management of infrastructures have been identified as powerful tools to optimize resource use, predict risks, and support sustainability-oriented decisions [5,6,7]. The integration of building information modeling (BIM), geographic information systems (GISs), and digital twins (DTs), among other examples, has been shown to support decision-making and improve the efficiency and climate resilience of infrastructures [8,9,10,11,12,13].

The implementation of sustainable construction practices, supported by the principles of the circular economy and based on lifecycle assessment, are strategic approaches to reduce resource consumption, waste production, and greenhouse gas emissions. Studies on the circular economy in construction show its relevance to decoupling infrastructure development from environmental degradation and demonstrate its potential to improve sustainability [14,15].

The application of integrated and optimized planning mechanisms in the construction and management of infrastructures is also one of the paths for achieving not only better environmental performance, but also social and economic benefits [16,17,18].

This Special Issue aims to highlight the role of engineering in the global effort to address the challenges facing civil infrastructures to meet emerging environmental and societal needs. In particular, the articles address several critical gaps in the literature, ranging from the lack of real-time digital monitoring and in situ structural data to the insufficient level of detail in construction planning. The articles essentially cover three main advances in civil infrastructures and the built environment in general: (1) digital transformation and smart lifecycle management; (2) structural resilience and automated diagnostics; (3) optimized planning and sustainable infrastructure design.

2. Advances in Civil Infrastructure Engineering

2.1. Digital Transformation and Smart Lifecycle Management

Digital transformation is driven by the integration of various digital technologies (DT, BIM-GIS) to establish a connection between physical structures and digital management systems. The implementation of DT in underground tunnels, using multimodal image sensors such as LiDAR, has enabled the extraction of geospatial features and the detection of structural displacements in near real time. These systems are enhanced by advanced sensing technologies, such as UHF RFID tags used as markers to manage the location and history of communication lines and pipelines. By combining these digital tools, professionals can achieve smarter infrastructure lifecycle management, identifying structural irregularities and preventing potential collapses.

Intelligent lifecycle management is also characterized by the optimization of planning and execution processes through algorithmic scheduling and modular methodologies. The integration of BIM with design for manufacturing and assembly (DfMA) and lean construction, to reduce construction duration, costs, and waste production, has been demonstrated in large-scale bridge projects.

2.2. Structural Resilience and Automated Diagnostics

Structural resilience is being revolutionized through innovative reinforcement techniques, such as internal screw iron fixed with nuts, capable of increasing the strength of brick masonry. These advances improve the deformation capacity and structural integrity of buildings, allowing them to withstand extreme horizontal actions, such as earthquakes and floods. The most recent research on the in-plane rocking behavior of unreinforced masonry walls also identifies ductile performance curves and trilinear functions that accurately predict the final deformation capacity based on toe crushing points. To safeguard historic urban centers, it is possible to use multi-model macroseismic methodologies and interview-based forms to assess the seismic vulnerability of infrastructure and plan retrofitting interventions on a territorial scale.

Automated diagnostics have also seen significant advancements. The use of high-precision technologies, such as 3D terrestrial laser scanning, to assess geometric imperfections in steel arch bridges in situ has enabled advanced nonlinear buckling analyses. Innovation has progressed, reaching the point of modeling tactile information (haptic) by applying generative adversarial network (GAN)-based super-resolution to LiDAR data, allowing inspectors to objectively diagnose surface textures and cracks as if they were physically touching the bridge. The integration of Industry 4.0 tools, including IoT sensors, UAVs (drones), and convolutional neural network (CNN)-driven image analysis, facilitates structural health monitoring (SHM) to identify failure areas such as concrete delamination and excessive corrosion.

2.3. Optimized Planning and Sustainable Infrastructure Design

Optimized planning can be achieved through algorithmic frameworks and systematic integration of processes that bridge the critical gap between initial design and on-site execution. For earthworks, the development of a detailed activity-based database of earthwork in road construction (DADER), combined with dynamic programming (DP), allows for the subdivision of broad plans into highly detailed activities. This results in schedules that minimize costs while strictly adhering to established deadlines. Similarly, in road intersection projects, the use of project management body of knowledge (PMBOK)-aligned stages facilitates the identification of planning deficiencies, such as inadequate material estimates or lack of planner experience, allowing for the early mitigation of schedule and budget deviations. These approaches also include cyclic algorithms to automate complex turbo-roundabout geometries and the selection of end-around taxiway (EAT) layouts designed to reduce controller workload and eliminate runway crossing risks.

Sustainable infrastructure design focuses on resource conservation, rapid serviceability, and waste reduction through innovative materials and modular construction methodologies. The use of polyurethane resin binders for road paving is a milestone, as the mixture requires absolutely no water and allows roads to be opened to traffic in a short time. In large-scale bridge projects, the integration of BIM and DfMA allows modular parts to be manufactured off-site, which has been proven to reduce on-site waste and construction costs. Furthermore, sustainability is enhanced through underground EAT projects that use terrain to reduce land occupation and emissions, while the use of UHF RFID tags for managing underground utility history prevents accidental damage during excavation, thus reducing high social costs and public anxiety.

3. Conclusions

This Special Issue highlights advancements in civil infrastructure engineering, notably through the integration of digital intelligence, structural resilience, and processes optimization. Tools such as DT, BIM-GIS integration, and AI-driven conflict detection enable proactive infrastructure lifecycle management. Furthermore, algorithmic planning and sustainable materials improve construction efficiency and promote rapid serviceability. Collectively, these multidimensional advancements foster a more reliable, sustainable, and resilient built environment capable of meeting the complex environmental and operational demands of modern society. The research described in this Special Issue contributes to several United Nations Sustainable Development Goals (SDGs), particularly those focused on water conservation (SDG 6), digital transformation and advanced materials (SDG 9), seismic resilience and urban safety (SDG 11), materials durability and disaster adaptation (SDG 13), and social governance (SDG 16).

Moving forward, future research should focus on refining multimodal sensing, collecting larger in situ structural datasets, and formalizing data-driven project governance to meet the complex environmental and operational demands of modern civil infrastructure throughout its lifecycle.