The integration of artificial intelligence (AI) and machine learning (ML) has revolutionised civil engineering, enhancing predictive accuracy, decision-making, and sustainability across domains such as structural health monitoring, geotechnical analysis, transportation systems, water management, and sustainable construction. This paper presents a detailed review of peer-reviewed publications from the past decade, employing bibliometric mapping and critical evaluation to analyse methodological advances, practical applications, and limitations. A novel taxonomy is introduced, classifying AI/ML approaches by civil engineering domain, learning paradigm, and adoption maturity to guide future development. Key applications include pavement condition assessment, slope stability prediction, traffic flow forecasting, smart water management, and flood forecasting, leveraging techniques such as Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Support Vector Machines (SVMs), and hybrid physics-informed neural networks (PINNs). The review highlights challenges, including limited high-quality datasets, absence of AI provisions in design codes, integration barriers with IoT-based infrastructure, and computational complexity. While explainable AI tools like SHAP and LIME improve interpretability, their practical feasibility in safety-critical contexts remains constrained. Ethical considerations, including bias in training datasets and regulatory compliance, are also addressed. Promising directions include federated learning for data privacy, transfer learning for data-scarce regions, digital twins, and adherence to FAIR data principles. This study underscores AI as a complementary tool, not a replacement, for traditional methods, fostering a data-driven, resilient, and sustainable built environment through interdisciplinary collaboration and transparent, explainable systems.

Following World War II, the rapid expansion of construction led to intensive use of natural resources, leading to resource depletion and accelerating climate change. Prioritising sustainability in structural design has therefore become essential. This study investigates three reinforced concrete (RC) slab systems typical of office buildings: flat slab, beam and slab, and two-way joist slab, using Eurocode 2 design principles. A 3 × 3 bay model with spans from 4 m to 14 m and three concrete grades (C25/30, C32/40, C40/50) was analysed through nonlinear finite element modelling. The methodology uniquely combines structural optimisation with embodied carbon and cost assessments across multiple slab typologies and span configurations, an approach rarely addressed in prior research. Results show that two-way joist slabs achieve the most favourable balance, reducing embodied carbon by 25–35% and construction cost by up to 15% compared to flat and beam and slab systems. This advantage is particularly evident at spans of 10 m or more, where the ribbed geometry significantly reduces concrete volume. Flat slabs are cost-efficient for short spans of up to 8 m but incur up to 40% higher carbon at longer spans due to increased thickness and punching shear reinforcement requirements. Beam and slab systems consistently recorded the highest cost and carbon values, offering limited environmental benefits despite their structural stiffness. The findings provide practical guidance for span-sensitive slab selection in early design, enabling the delivery of reinforced concrete buildings that are both cost-effective and environmentally responsible.

Following World War II, the swift economic growth in construction and the soaring demand in urban regions led to the excessive extraction of natural resources like fossil fuels, minerals, forests and land. To tackle significant global challenges, including the consumption of natural resources, air pollution and climate change, radical changes have been suggested over the past decades. As part of this strategic initiative, prioritizing sustainability in construction has emerged as a crucial focus in the design of all projects. In order to identify the most environmentally sustainable reinforced concrete (RC) slab system, this research investigates the carbon emissions associated with various slab systems, including solid, voided slabs and precast floor systems. The results demonstrate that beam and slab floor and solid slabs have the highest embodied carbon due to the significant use of concrete and related materials, whereas voided slabs and two-way joist floors exhibit lower carbon emissions. The results indicate that the two-way joist system is the most environmentally advantageous option. For precast floor systems, post-tensioned concrete and hollow-core slabs demonstrate the lowest embodied carbon levels. This research provides practical recommendations for architects and engineers aimed at enhancing sustainable design methodologies. It emphasizes the importance of incorporating low-carbon materials as well as pioneering flooring technologies in upcoming construction initiatives to support the achievement of global sustainability objectives.

In present study, an interface element with nonlinear spring is used to simulate cohesive zone model (CZM) in reinforced concrete (RC) beam for Mode I fracture. The virtual crack closure technique (VCCT) is implemented to model the propagation of the fracture process zone (FPZ). This model can be calculated the energy release rate by using new method from energy approach. Energy dissipation rate by steel bars is obtained to affect on the crack propagation criterion to implement in finite element method. The numerical results are compared with references result available in the literature. It is observed that the FPZ is increased linearly and then stay constant. It may be due to effect of steel bars or inherent behavior of FPZ. The results show that the proposed model does not depend on mesh size.

The literature identifies concrete and steel as the primary contributors to embodied carbon in building structures and highlights a strong relationship between sustainability and structural system geometry. However, existing studies predominantly focus on one-way systems and flat slabs, while research on two-way joist slabs remains limited and often centred on strength optimisation. In particular, there is a lack of systematic life cycle comparisons of alternative beam configurations within this system. This gap is critical, as early-stage design decisions largely determine the environmental impact of structural systems. This study presents a comprehensive, span-dependent evaluation of four beam configurations, namely Without Beam, Internal Beam, Perimeter Beam, and Full Beam, for reinforced concrete two-way joist slabs used in office buildings. A parametric framework was developed using Eurocode-compliant structural design and nonlinear finite element modelling to assess 36 span combinations ranging from 4 × 4 m to 14 × 14 m. Material quantities were extracted from the final designs and converted into embodied carbon values using cradle-to-gate (A1–A3) emission factors derived from the ICE database. The results demonstrate that beam configuration has a significant influence on embodied carbon and construction cost. For spans below approximately 8 m, beamless systems provide the most material-efficient solution. For spans exceeding approximately 10 m, full-beam configurations offer improved structural efficiency and reduced embodied carbon due to enhanced stiffness and load distribution.