Abstract Link slabs have emerged as an effective alternative to traditional expansion joints in bridge systems, helping mitigate durability issues associated with water infiltration and joint deterioration. Expansion joints accelerate the degradation of bridge superstructures due to water infiltration and inadequate drainage. The use of link slabs eliminates expansion joints, creating a continuous deck while maintaining simply supported boundary conditions. In this paper, a systematic and critical review of link slabs is presented, synthesizing more than two decades of research on structural behavior, material selection, design methodologies, and life cycle performance. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses–based methodology was used to identify and evaluate key studies, enabling a structured assessment of trends and knowledge gaps. Link slab behavior has been verified through field testing, experimental testing, and numerical modeling. Researchers have investigated the use of engineered cementitious composite and ultrahigh-performance concrete (UHPC) as alternatives to traditional concrete and have found favorable results. Similarly, fiber-reinforced polymer is an acceptable alternative to steel reinforcement. Fatigue, freeze–thaw, and seismic behavior are also examined. Life cycle analyses show economic benefits in addition to the documented structural benefits, including increased service life for bridge bearings and the superstructure. This review identifies critical gaps, particularly the lack of long-term in situ performance data and limited field validation of emerging materials such as UHPC. Future research is proposed, with an emphasis on field monitoring, fatigue characterization, and material optimization. The findings will provide insights for bridge engineers and agencies seeking to implement durable jointless bridge systems.
Abstract This study develops a novel artificial intelligence (AI)-based methodology to enable risk-based, long-term-focused decision support for bridge asset management. This methodology features three key modules: (1) a bridge condition simulation module integrating Markovian state transition dynamics, (2) a lifecycle cost analysis module to holistically quantify and aggregate the direct and indirect costs incurred due to bridge condition deterioration and intervention actions over a prolonged planning horizon, and (3) an AI-based decision-support module for optimal sequential maintenance actions at individual bridge level. The proposed methodology can flexibly accommodate the decision needs of different individual bridges within a bridge portfolio under various sources of uncertainty in near real time. Compared with traditional reactive, condition-based decision policies, the proposed AI-based policies are found to offer more proactive and adaptive decisions and to demonstrate superior performance in minimizing the life cycle costs. To further enhance risk-averse stakeholders’ trustworthiness in the AI-based decision policy, practical action constraints and decision reasoning are introduced, and the effect of action override is also investigated.
Abstract This study proposes a novel bonded straight iron-based shape memory alloy (Fe-SMA) plate system using hybrid anchorage for the shear strengthening of reinforced concrete (RC) T-beams and presents a comprehensive experimental evaluation of its structural performance. Unlike existing Fe-SMA shear-strengthening configurations that rely on mechanically complex anchorage or exhibit limited prestress transfer, the proposed hybrid-anchored configuration enables the reliable application of active prestressing without hydraulic anchorages while allowing flexible vertical or diagonal strengthening layouts. Fifteen specimens were tested under three-point bending to evaluate the effects of shear-span ratio ( λ = 1.0, 1.5, 2.0), activation temperature (150°C, 250°C), Fe-SMA inclination angle ( β = 90°, 45°), and bonding condition. The results demonstrate that the proposed system significantly improves the shear behavior of RC T-beams. Compared with unstrengthened specimens, activated Fe-SMA plates increased the maximum shear capacity by up to 43%, reduced internal stirrup stress, and enhanced postcracking stiffness by approximately 30%. The system also significantly improved crack-control performance, reducing the maximum diagonal crack width by more than 60% and increasing the initial cracking shear force by up to 116%, which effectively delayed crack propagation and mitigated brittle failure. Diagonal strengthening ( β = 45°), oriented perpendicular to the principal tensile stress direction, produced more uniform crack distributions and superior confinement. Bonded configurations provided additional advantages, ensuring a more uniform transfer of self-prestress and achieving shear capacity increases up to three times greater than those in unbonded specimens. The theoretical values closely matched the experimental results, confirming that the contribution of the activated Fe-SMA exceeded that of the stirrups by more than a factor of 2. Overall, the proposed bonded Fe-SMA strengthening system offers active crack control, substantial shear performance enhancement, and ease of installation, providing a practical and durable solution for upgrading existing concrete bridges and structural members.
Abstract To investigate the evolution of mechanical behavior in concrete box girder bridges during cantilever construction under the coupled influence of stochastic environmental temperature and humidity, a novel simulation method is proposed. This method integrates a temperature–humidity coupling analysis method for the internal fields of concrete and a constitutive model that accounts for multifactor interactions, including temperature-induced stress, drying shrinkage, creep, and the sensitivity of elastic modulus. The proposed method was applied to simulate and analyze the construction process of the Yuanhe Bridge in Jiangxi Province, China. Based on the statistical analysis of nearly two decades of daily historical meteorological data from the region, it was verified through fitting tests and statistical assessments that the probability distributions of temperature, humidity, and wind speed conform to Gaussian (normal) distributions. The results systematically reveal the statistical influences of stochastic environmental factors on the bridge’s camber, shear-lag effect, and prestress loss. The results indicate that the maximum camber and the shear-lag coefficient at the bottom slab–web junction exhibit slightly asymmetric distributions and can be well described by Bigaussian fitting curves, whereas the shear-lag coefficient at the top slab–web junction follows a Gaussian distribution. Increases in the daily temperature range and decreases in relative humidity are found to amplify the camber and the prestress loss. No discernible influence of wind speed on the camber, shear-lag effect, or prestress loss is observed. This study provides a crucial theoretical foundation and technical support for the refined control and optimization of cantilever construction of bridges under stochastic environmental conditions.
Static and dynamic load tests were conducted on an anonymized in-service prestressed concrete box girder bridge constructed in 1972 and designed for Bridge Class 30 according to DIN 1072. The bridge is instrumented as part of the DTEC-SHM research initiative with a permanent structural health monitoring system comprising 128 sensors, including accelerometers, strain sensors, inclinometers, displacement transducers, embedded temperature sensors, and weather stations. The test program includes long-term static loading with stepwise added masses of 680 kg, 1420 kg, and 2160 kg, short-term static truck parking positions, and repeated dynamic truck crossings under loaded and unloaded vehicle configurations. The short-term static tests used a loaded truck of 21250 kg parked at three bridge positions, while the dynamic tests used loaded and unloaded truck configurations of 21250 kg and 12340 kg at speeds up to 13.9 m/s. The published load-test data are available on Zenodo in HDF5 format and include synchronized measurements from the monitoring system, temporary laser sensors used for vehicle-position and passage-time validation, and derived tracked eigenfrequency time series from the reference and long-term static-load-test period. The bridge geometry, sensor layout, acquisition system, load cases, truck geometry, and data hierarchy are documented to support reuse of the data. Plausibility checks are presented for the main response quantities, including laser-based validation of parking positions and passage windows, vibration spectra and tracked modal parameters, and repeatable strain and displacement response profiles under crawl-speed truck passages. The data set addresses the scarcity of publicly available full-scale bridge load-test data and supports applications such as finite element model calibration, neutral-axis tracking, influence-line extraction, and data-driven anomaly detection.
