Prediction of load–slip behaviour in composite beams with varying configurations using experimental, numerical and machine learning approach

Composite beams consist of profiled steel decking topped with in-situ reinforced concrete. This research investigates the load-slip behaviour of steel–concrete composite beams with different configurations of shear connectors and steel decking. Composite beams combine steel and concrete to create structures with superior strength, durability, and load-bearing capabilities, frequently employed in high-rise buildings and bridges. The study focuses on the role of shear connectors and steel profiles, which are essential for effective load transfer and slip resistance between the materials. By examining various shear connector types (e.g., channel, stud, and bolted connectors) and steel decking shapes (trapezoidal, rectangular, and re-entrant), the research aims to determine their impact on the load-slip performance and ultimate strength of composite beams. The project methodology includes experimental testing and numerical analysis to assess bond strength, slip behaviour, and structural performance under load. Advanced modelling techniques, including finite element analysis and machine learning algorithms, are employed to predict structural characteristics like load capacity and slip resistance. The study contributes to optimizing composite beam design, providing insights for construction applications that demand high strength, durability, and efficient material usage.