Computational modeling of vehicle-bridge interaction with experimental validation under moving loads for structural health monitoring.

Valašková, V; Kotrasova, K · 2026 · PubMed Central

DOI: 10.1038/s41598-026-49413-2

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Summary

This study addresses the need for accurate, computationally efficient models of vehicle–bridge interaction (VBI) to support structural health monitoring (SHM). As global bridge infrastructure ages, reliable assessment of dynamic responses under realistic traffic loads is critical for detecting degradation and estimating service life. Existing modeling approaches present a trade-off: reduced-order beam models offer efficiency but neglect transverse and torsional effects, while high-fidelity three-dimensional finite element models capture complex behavior but are too computationally expensive for iterative SHM workflows. The authors aim to bridge this gap by developing and validating a slab-based reduced-order model that captures spatial response characteristics without the cost of full 3D simulations. The methodology combines numerical modeling with experimental validation. Two computational approaches were developed: a classical Euler–Bernoulli beam model and a Kirchhoff–Love plate (slab) formulation. Both were coupled with multibody vehicle dynamics, represented by 2D planar (8 degrees of freedom) and 3D spatial (15 degrees of freedom) models, respectively, to simulate realistic wheel–deck contact forces. These models were validated against in situ measurements from a 29-meter span, 11-meter wide reinforced concrete slab bridge. The bridge was instrumented with displacement sensors and accelerometers to capture quasi-static deflections and dynamic vibrations under operational traffic. Data were sampled at 500 Hz, allowing for the analysis of longitudinal, transverse, and torsional responses induced by varying vehicle speeds and lane positions. Results indicate that the beam model accurately reproduces the global quasi-static longitudinal bending response but fails to capture transverse deformation and bending–torsion coupling. In contrast, the slab-based model successfully resolves these additional spatial effects, which are critical for understanding lane-dependent excitation. After a model updating procedure to calibrate structural parameters, the slab formulation achieved close agreement with measured responses across various vehicle speeds and transverse load positions. The study demonstrates that the slab-based approach provides a mechanically consistent intermediate alternative, offering superior spatial resolution compared to beam models while maintaining the computational efficiency necessary for real-time or iterative applications. The significance of this work lies in providing a validated, efficient modeling framework for SHM applications. By bridging the gap between simplified analytical models and complex finite element simulations, the proposed slab-based formulation is well-suited for model updating, inverse load identification, and condition assessment under moving loads. This approach enables engineers to accurately monitor bridge health and detect damage-induced changes in dynamic characteristics using realistic traffic data, thereby supporting the resilience and maintenance of aging infrastructure.

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• simulator validity fidelity