Global bridge failure statistics indicate that hydraulic actions, particularly hydrodynamic forces and scour, play major roles in bridge failure during floods. The scenario is specifically critical for ageing bridges in harsh environments. Because of continuous exposure to such environments, RC bridges with time become more susceptible to load demands during flood events. Hence, appropriate retrofit strategies are essential that can be implemented at any instance during service lives of bridges. This study identifies potential flood retrofit strategies for bridges and develops a framework to measure their effectiveness by analysing a simply supported RC riverine bridge before and after retrofit. As the bridge experiences scour as well, opted retrofit strategies include superstructure and scour retrofit. Computational fluid dynamics simulations are performed to calculate hydrodynamic forces on bridge superstructure, whereas code provisions are followed to calculate the same for piers. Finite element analysis of the bridge at various life-cycle years under different combinations of inundation ratio and flood velocity found that the ageing bridge, without and with scour retrofit, fails to sustain during extreme floods; yet, it becomes safe when superstructure retrofit strategies are implemented. Thus, obtained results demonstrate the effectiveness of retrofit strategies in mitigating flood risk of ageing bridges.

This paper summarises observations and results obtained from diagnostic testing and a complementary finite element model of a 140-year old short-span open-deck metallic girder bridge. A purpose-built frame was constructed around the bridge in order to apply the load in a form that represents passenger train axle loading. Testing was carried out under different axle load positions on the bridge with and without the timber deck superstructure to quantify load distribution effects on the supporting bridge members. Minor asymmetries, due to the location of offset stiffeners on main girder webs, and imperfections in the timber deck, in the form of unintended camber in the solid beams, played a significant role in the recorded bridge response, manifested through U-frame action deformation profiles and cross-girder bending stresses. Prompted by these test observations and using appropriate finite element models, a novel numerical sensitivity study was undertaken to quantify, for the first time, the effect of these factors on fatigue damage for a typical train passage. It is demonstrated that the synergistic application of load testing and numerical modelling can add value to our understanding of bridge response and inform issues related to static and fatigue assessments leading to more reliable service life predictions.

Any disruption in bridge functionality significantly affects network performance and users’ daily lives, as bridges are one of the most vulnerable components of transportation networks. While previous studies often focus on either structural condition or network performance, this study presents an integrated risk-based framework that combines expert judgement (Delphi method), seismic fragility assessment, and GIS-based travel-time disruption modelling to assess collapse risk and network-level disruption consequences, supporting decision-making for maintenance and retrofit prioritisation. The framework incorporates both full and partial failure scenarios to improve realism in disruption modelling. As a proof-of-concept, the method is applied to 63 bridges in a district of Tehran, Iran, under seismic hazard conditions. The resulting priority matrix enables informed prioritisation of bridge maintenance and retrofit interventions, directly supporting risk mitigation efforts and contributing to enhanced urban resilience. The integrated framework addresses critical gaps in current practices by simultaneously considering vulnerability, consequence, uncertainty, and network functionality in seismic bridge management.

Post-earthquake residual bearing displacement is the primary earthquake-induced damage of highway bridges supported by unbonded laminated rubber bearings (ULRBs) and characterised by high variability, which is a critical damage indicator for the seismic resilience assessment of bridges. However, achieving a high-fidelity, computationally efficient seismic resilience assessment of ULRB-supported highway bridges that adequately accounts for the stochastic nature of residual displacement remains challenging. This study investigates the seismic behaviour and residual displacement characteristics of a ULRB‑supported highway benchmark bridge through numerical analyses that include girder–abutment pounding, structural parameter uncertainty, and record‑to‑record variability. Next, a high‑fidelity, computationally efficient fragility‑based method for estimating residual bearing displacement is proposed for use in seismic resilience assessment. The proposed method is compared with classical incremental dynamic analysis (IDA) and cloud approaches. Finally, the seismic resilience of the benchmark bridge, quantified as equivalent downtime, is evaluated using an expert‑survey‑based bridge functionality recovery model. Results show that the residual bearing displacement of ULRB-supported bridges exhibits considerable stochasticity than peak girder and bearing displacements. The fragility-based residual bearing displacement estimation method proposed in this study for the seismic fragility and resilience assessment of ULRB-supported bridges balances the accuracy and computational costs, generally outperforming the IDA and cloud methods.

Researchers have developed and applied tuned liquid dampers (TLDs) to reduce the vibration of civil structures. Previous studies have focused on using a large number of identical TLDs (single-frequency TLDs) or many multi-frequency TLDs to reduce the structural dynamic response. In those works, the optimal parameters of TLDs were determined through the optimal parameter of equivalent tuned mass dampers. In this study, a new approach is proposed to directly determine the optimal parameters of multiple identical TLDs (MITLD). Furthermore, different aspects including the best configuration control effectiveness, robustness, and sensitivity to changes in the water level of MITLD are explored. Parametric studies are also conducted to find the fundamental characteristics of MITLD and the effective domains of the MITLD’s main parameters. The results obtained from this work agree well with those of earlier research works. Based on this fundamental research, recommendations given include: (1) MITLD is effective in controlling the dynamic response of structures with low natural frequencies, (2) MITLD is very sensitive to the variation of the water level height in TLDs, and (3) a difference in the natural frequency of the main structure leads to a significant performance decrease of the MITLD.

Fatigue crack growth (FCG) in welded joints of orthotropic steel decks (OSDs) is highly stochastic, which complicates the accurate assessment of fatigue reliability. To consider the stochastic factors affecting fatigue performance in welded joints, this study proposed a stochastic FCG analysis method that incorporates machine learning to evaluate the fatigue reliability. Firstly, a probabilistic model for fatigue stress spectrum in welded joints was developed using site-specific traffic data. Subsequently, stochastic FCG analysis method assisted by a random forest model was developed to replace the time-consuming finite element solution. Finally, a fracture limit state function was established to evaluate fatigue reliability with consideration of the stochastic FCG process. Results indicate that a lognormal distribution accurately fits fatigue characteristic of the equivalent stress intensity factor range, with mean values consistently lower at the crack tip compared to the crack edge. Additionally, the deterioration rate of welded joints accelerates significantly at a crack depth of 5 mm, resulting in a shift of the remaining fatigue life distribution from lognormal to exponential. The reliability indices decrease significantly under overloading conditions. A 20% increase in vehicle weight reduces the fatigue life from the expected 100 years to 82 years.

Although numerous studies have investigated sustainability in construction engineering focusing on eco-efficiency factors, it is crucial to assess sustainability across the entire life-cycle of buildings, bridges and other infrastructure facilities, by taking into account the time-variant structural performance while incorporating environmental, economic and social considerations. Structures and infrastructure systems are exposed to natural and human-made hazards, whose potential impact is exacerbated by the detrimental effects of ageing and structural deterioration processes worsened by climate change, reducing in this way the operational service life with inherent consequences on sustainability. This review paper promotes the central role of structural engineering in the sustainability implementation process and emphasises the importance of integrating sustainability with resilience, risk, reliability and safety, throughout the life-cycle of structures and infrastructure systems. The various stages of a structure’s life-cycle – material selection, design, construction, operation, maintenance, decommissioning, dismantling, waste management, recycle and/or reuse – are examined highlighting how sustainability can be incorporated at each phase to mitigate adverse impacts and improve efficiency. Metrics, tools and rating systems for quantifying sustainability are also discussed, addressing challenges in adopting sustainable practices. Finally, implications and future research directions are provided to advance sustainable constructions and infrastructure systems under a life-cycle perspective.

Developments in indirect monitoring of bridges demonstrated practical solutions for network-level life-cycle bridge assessment and evaluation. Utilizing mobile robots is a new area for indirect monitoring, offering scalable approaches to data collection and assessment. This study investigates and experimentally validates a drive-by monitoring methodology using a four-wheeled robot equipped with a sensing system. The methodology employs a simple yet practical and effective approach to isolate the bridge vibration response from interfering factors (road roughness, vehicle dynamics, noise) by applying frequency-domain filtering using data collected from the adjacent roadway. Using the methodology, the study explores the effect of varying driving speeds, drive-stop scenarios, and the robot’s trajectory on different sides over the bridge to determine optimal conditions for precise bridge mode (frequency) identification. Nine experiments conducted on a real-world bridge under jumping excitation demonstrate the identification of up to six modes, with an average variation of 2% compared to reference monitoring data. Driving trajectories showed minimal impact on results, though runs on all sides suggest comprehensive identification. Robot’s dual-capability for real-time mode identification and visual analysis is a promising approach for local assessments in bridge networks, complementing large-scale monitoring by Connected Vehicles in a multi-tiered reliability framework.

The load distribution of heavy vehicles on the bridge deck is an important indicator for bridge evaluation. The current vehicle load distribution detection using traffic flow videos equates the vehicle with a concentrated load, which is inconsistent with the actual wheel load distribution on the bridge deck. Therefore, this paper proposes a heavy vehicle wheel load distribution detection method based on computer vision. In this method, firstly, a dual-mask-based projection method of heavy vehicles on the bridge deck is proposed to improve the accuracy of vehicle projection (the projection of a vehicle onto a bridge deck). Secondly, a positioning method of nearby wheels on the bridge deck based on image conversion is proposed to solve the problem of partial wheel occlusion. Thirdly, an acquisition method of distant wheels distribution on bridge deck based on vehicle tracking is proposed to solve the problem of wheels that are too far and cannot be identified due to fuzzy. Finally, the wheel load distribution of heavy vehicles on the bridge deck was obtained by integrating the wheel distribution and ETC system database. The proposed method is successfully applied on a single tower cable-stayed bridge, and the maximum error of the wheel diameter calculated by wheel distribution is only 5.78%.

The North Gyeongsang region in South Korea has demonstrated significant seismic activity over the past two decades. This study assessed the zone-specific performance and vulnerability of lined tunnels, incorporating structural material properties and surrounding geological conditions as primary influential parameters, along with variations in tunnel lining, to develop intensity–response relationships. For Zone E, the seismic fragility curves (SFCs) generated for minor, moderate, and extensive damage levels for both shallow and deep tunnels indicate a high level of catastrophic risk. These proposed SFCs are employed to assess tunnels planned for a proposed road network in Pohang. The findings revealed that Route P2 represents the optimal choice, whereas Route P3 is the least suitable for ensuring the safest design. This analysis includes the formulation of a tunnel-specific risk matrix, which is utilized to define the functionality of each route in post-seismic scenarios within the study area. The combined use of SFCs, risk matrices, and road functionality maps provides a valuable engineering resource for professionals engaged in the earthquake-resistant design and assessment of underground structures in South Korea. This methodology will assist disaster management authorities in risk mitigation and ensuring safe traffic flow on transportation networks.