Identifying the stress-strain state of railroad overpass spans

2025

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DOI 10.15587/1729-4061.2025.327147
Data confidence 70 medium
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Abstract

This paper presents the results of the study of stress-strain state of reinforced concrete spans of two overpasses. With increasing volumes of cargo transportation by rail, the axle load increases up to 25 tons. Bridges and overpasses built about 100 years ago have acquired hidden defects during the years of operation. The safe operation of artificial structures requires additional research using the TENZO software and hardware complex, which processes digital records from primary transducers based on strain gauges. In 2018 and 2023, deflections, strains and stresses were obtained for typical beam spans of 11.5 m and 16.5 m of two reinforced concrete overpasses, from static and dynamic loads. For example, in 2018, the “spread” of stresses from the test load (TEM18) for the right-hand blocks of the 11.5 m spans ranged from 3.7 MPa to 3.71 MPa at different loading stages, and for the left-hand blocks of the 11.5 m spans ranged from 3.46 MPa to 3.9 MPa at different loading stages. In 2023, the stress range was from 2.58 MPa to 4.65 MPa for the right span blocks of 11.5 m span and from 2.67 MPa to 4.7 MPa for the left span blocks at different stages of loading. The 2018 data show uneven loading of the span blocks, indicating that the track axis is offset from the axis of the transportation structure. In 2023, the span structure blocks worked uniformly, which indicates that the track axis and the axis of the transportation structure are aligned (coincide). The obtained dependences “deformations and stresses” for typical beam spans of 11.5 m show the technical condition of the structures of the investigated objects, confirming the possibility of increasing the passage through them of a larger tonnage of transported cargo (increase in axial load up to 25 tons per axle). The spans have demonstrated reliable behavior under dynamic loads, with no signs of significant degradation in the period from 2018 to 2023. The use of data from scientific monitoring methods with the use of digital hardware and software systems will significantly reduce the cost of maintaining artificial structures on railroads and improve the safety of transportation infrastructure