Construction Control of Long-Span Combined Rail-Cum-Road Continuous Steel Truss Girder Bridge of High-Speed Railway

The construction of long-span continuous steel truss rail-cum-road bridges for high-speed railways presents significant challenges, primarily due to structural complexity, stringent deformation tolerances, and intricate construction sequences. This paper presents a comprehensive construction control methodology developed and implemented for such bridges. Using a real-world bridge project in China as a case study, the methodology integrates mechanical analysis of key construction stages, deformation prediction, real-time monitoring, and adjustment techniques. Furthermore, the application of machine learning (ML) for camber prediction is explored. Key findings indicate that the longitudinal displacement (X-direction) of the top chord at the upper-deck closure segment is highly sensitive to temperature variations, with a differential of about 10–12 mm observed under a 15 °C temperature change. Consequently, closure welding is recommended near the design reference temperature, with field measurements guiding final fit-up adjustments. A comparative analysis between ML predictions and theoretical methods for member elongation revealed that the Extra Trees (ET) model and K-Nearest Neighbors (KNN) model achieved excellent accuracy, with errors within 2 mm, demonstrating the feasibility of ML-based camber setting. The proposed integrated approach, combining finite element analysis, real-time monitoring, and detailed sensitivity analysis of closure accuracy, proves effective in ensuring structural safety and meeting precise alignment requirements, particularly for high-speed railway track. The findings offer valuable insights for the construction control of similar long-span steel truss rail-cum-road bridges.