The corrosion of prestressing steel in prestressed concrete bridges is a critical issue for bridge maintenance. To assess structures with corroded strands, it is necessary to define the mechanical properties of the strands and their influence on the structural behavior. In this study, corroded strands were taken from external tendons in existing post-tensioned concrete bridges and tested to determine the effects of corrosion on their tensile properties. Empirical equations for the tensile strength and ductility of the corroded strands were proposed using test results. The most corroded wire governs the mechanical properties of the strand. Experiments on prestressed concrete beams with a single corroded strand were conducted to investigate their structural behavior. A reduction in the flexural strength and maximum deformation was observed in these experiments. According to the section loss of a wire in a strand and its location in a beam, the flexural capacity can be evaluated using the proposed equation. The reduced ultimate strain of the corroded strand can be the governing factor of the flexural strength.

The corrosion of prestressing steel in prestressed concrete bridges is a critical safety issue. To evaluate the strength of a prestressed concrete beam with corroded strands, it is necessary to know the mechanical properties of the corroded strands in terms of their tensile strength and ductility. In this study, material models were suggested using tensile tests of corroded strands which had been taken from existing bridges. Five prestressed concrete beams with multiple internal corroded strands of different corrosion levels and locations were fabricated and tested using the three-point bending test. The beams with corroded strands near the support did not show meaningful flexural behavior changes, while the beams with corrosion in the mid-span showed significant strength reduction. In order to suggest the appropriate evaluation of the flexural strength of a prestressed concrete beam with corroded strands, material models of the corroded strands were divided into two model categories: a bi-linear material model and a brittle material model. Strength evaluations of the corroded prestressed concrete beams according to $f_{ps}$ approximation and strain-compatibility using OpenSEES were conducted. Results suggested the use of the strain compatibility method only when the section loss was greater than 5%.

The growing adoption of off-site construction methods has increased the critical role of mobile cranes within the construction sector. This study develops a Construction Digital Twin (CDT) framework to optimize crane lifting positions and capacities for the installation of prefabricated bridge decks. By integrating 3D site modeling, Building Information Modeling (BIM), and crane simulations within the Unity game engine, the CDT overcomes the limitations of conventional 2D-based planning by providing a three-dimensional representation of site conditions. An exhaustive search method identifies optimal crane configurations, enhancing precision and efficiency. Simulation calibration using video analysis of real bridge deck installations aligns crane speed and cycle times with actual operations, improving reliability. Case studies demonstrate the CDT’s ability to reduce crane operation costs by 27% when employing a smaller capacity crane while maintaining operational efficiency. Additional DFA-focused simulations with varying deck dimensions revealed a potential 10% cost reduction by optimizing crane operations and deck design strategies. The CDT framework supports early-stage planning, reduces operational risks, and contributes to cost-effective and safer construction practices, offering a scalable solution adaptable to various construction scenarios.

The corrosion of prestressing steel in prestressed concrete bridges is a critical issue for bridge maintenance. To assess structures with corroded strands, it is necessary to define the mechanical properties of the strands and their influence on the structural behavior. In this study, corroded strands are taken from external tendons in existing bridges and tested to define the effects of corrosion on the tensile properties of the strand. Empirical equations for the tensile strength and ductility of the corroded strand are proposed using test results. The most corroded wire governs the mechanical properties of the strand. Experiments on prestressed concrete beams with a single corroded strand are conducted to investigate the structural behavior. A reduction in the flexural strength and maximum deformation is observed from the experiment. According to the section loss of a wire in a strand and its location in a beam, the flexural capacity can be evaluated using the proposed equation. The reduced ultimate strain of the corroded strand can be the governing factor of the flexural strength.

To evaluate the structural safety of corroded prestressed concrete structures, it is necessary to define the deteriorated mechanical behaviors of corroded prestressing steel strands. However, no standard provides a quantified relationship between the level of corrosion and the residual mechanical properties, and no consensus for such quantification has been reached. The aim of this study was to provide a test database for the residual mechanical properties of corroded prestressing steel strands. Strands recovered from aged bridges were naturally corroded, and an evaluation method for the corrosion level was suggested. In addition, corrosion assessment criteria were suggested based on characteristics of the corrosion appearance.

Existing design codes for predicting the strength of stud shear connections in composite structures are limited when adapting to constant changes in materials and configurations. Machine learning (ML) models for predicting shear connection are often constrained by the number of input variables, resembling conventional design equations. Moreover, these models tend to overlook considerations beyond those directly comprising the connection. In addition, the data used in ML are often biased and limited in quantity. This study proposes a model using AutoML to automate and optimize the process for predicting the ultimate strength and deformation capacity of shear connections. The proposed model leverages a comprehensive dataset derived from experimental studies and finite element analyses, offering an advanced data-driven solution to overcome the limitations of traditional empirical equations. A digital twin model for the static design of pushout specimens was defined to replace existing empirical design codes. The digital twin model incorporates predictions of the geometry model, ultimate strength, and slip as input parameters and provides criteria for evaluating the limit state through a bilinear load–slip curve. This study advances predictive methodologies in structural engineering by emphasizing the importance of ML in addressing the dynamic and multifaceted nature of shear connection behaviors.