This research investigates the application of plastic fiber reinforcement in pre-tensioned reinforced concrete railway sleepers, conducting an in-depth examination in both experimental and computational aspects. Utilizing 3-point bending tests and the GOM ARAMIS system for Digital Image Correlation, this study meticulously evaluates the structural responses and crack development in conventional and plastic fiber-reinforced sleepers under varying bending moments. Complementing these tests, the investigation employs ABAQUS’ advanced finite element modeling to enhance the analysis, ensuring precise calibration and validation of the numerical models. This dual approach comprehensively explains the mechanical behavior differences and stresses within the examined structures. The incorporation of plastic fibers not only demonstrates a significant improvement in mechanical strength and crack resistance but paves the way for advancements in railway sleeper technology. By shedding light on the enhanced durability and performance of reinforced concrete structures, this study makes a significant contribution to civil engineering materials science, highlighting the potential for innovative material applications in the construction industry.

Railway tracks at bridge approaches experience significant vertical stiffness transitions, leading to adverse effects such as settlement and increased dynamic loads, accelerating track degradation. This study explores various structural solutions, including geosynthetics, reinforced ballast, transition slabs, under sleeper pads (USPs), under ballast mats (UBMs), jet grouting, and special rail fasteners. Despite their application, these solutions often fail due to their static nature. This paper introduces an adaptive approach using special rail fastenings with real-time adjustable stiffness. This system dynamically modifies rail support characteristics based on train speed and track conditions, improving track durability, ride quality, and maintenance strategies. The findings demonstrate the potential of adaptive systems to enhance railway infrastructure performance.