An Open-Source Framework for Coupled Vehicle-Bridge Interaction Analysis Using OpenSees

TL;DR

This paper introduces an open-source Python framework based on OpenSees for coupled vehicle-bridge interaction analysis, supporting various vehicle models and validated against benchmarks, facilitating reproducible research.

Contribution

It provides a reusable, open-source tool for VBI analysis with multiple vehicle models and validation, advancing simulation capabilities and research reproducibility.

Findings

Close agreement with benchmarks (R2 > 0.998) validates the framework.

Parametric study identifies when decoupled mode is sufficient.

Open-source release supports reproducible vehicle-bridge dynamics research.

Abstract

Vehicle-bridge interaction (VBI) is important for simulating bridge response under moving vehicular loads and supports applications such as dynamic amplification studies, weigh-in-motion, and indirect bridge monitoring. Although VBI theory is well established, many existing implementations use custom finite element code or research-specific solvers, which limits their reuse. This paper presents an open-source Python framework for VBI analysis built on OpenSees. The bridge and vehicle are modeled as separate OpenSees subsystems and connected through an iterative scheme that exchanges displacement and force values at each time step until convergence. Five vehicle model types are supported, from a single axle spring-mass system to two-axle composite half-cars with body pitch and separate tyre and suspension elements. A decoupled mode is also provided: the vehicle static weight is applied as a moving load on the bridge, and the resulting bridge motion is then used as base excitation for the vehicle. Validation against three published benchmarks (quarter-car, half-car with pitch, and full composite models) shows close agreement, with R2 above 0.998 in all cases. A parametric study reports the accuracy of the decoupled mode as a function of vehicle-to-bridge mass ratio, span length, speed, road roughness class, and background traffic density, and indicates when the decoupled mode is adequate and when full coupling is needed. The complete framework and benchmark configurations are released as open-source software to support reproducible research in vehicle-bridge dynamics.