Track-Bridge Interaction Effects in Ballast Superstructures: Large-Scale Experiments as a Basis for SHM-Driven Bridge Models

Abstract

Railway bridges are crucial key components of railway infrastructure. The steady increase in traffic volume (intensification of train traffic along with increasing axle loads) poses a major challenge for infrastructure operators in ensuring the resilience of existing structures and assessing their service life realistically and economically. The application and combination of digital twins and structural health monitoring (SHM) are essential for mastering these challenges. A realistic assessment and prognosis of railway bridge conditions and performance requires detailed information on the actual system parameters. In this context, the computationally implemented interaction between the track and supporting structure significantly influences the generated results and the resulting condition assessments of the railway bridge system. A wide range of mechanical modelling options with different levels of complexity are available for implementing track-bridge interaction (TBI) effects in computational models. However, the considerable range of model-related stiffness and damping parameters makes it particularly more challenging to consider TBI effects realistically in practical applications. Based on this background, the research activities of the Institute of Structural Engineering at TU Wien focus on the experimental investigation of TBI effects in ballast superstructures. This contribution presents the key results of the investigation of vertical and longitudinal TBI effects. Using two large-scale test facilities, the interaction effects occurring in ballast superstructures can be investigated separately in both the vertical and longitudinal directions in an isolated manner. The test setup allows the stiffness and damping properties of the ballast superstructure to be precisely determined, taking into account time-dependent and environmental influences. The overarching goal is to generate a holistic and physically based mechanical model with precisely defined stiffness and damping characteristics for describing TBI effects, which can be implemented as simply as possible in corresponding digital bridge models. This contributes significantly to the reliable condition assessment and condition prognosis of railway bridges.