Keywords: crosswind stability, characteristic wind curves, railway interoperability, railway vehicle dynamics, inverse model calibration, bayesian optimisation.

As high-speed rail networks grow, ensuring interoperability between different lines and vehicles has become a primary requirement, particularly in crosswind assessment where line-level analyses remain strongly dependent on the specific vehicles adopted, making the definition of a common reference particularly useful. To address this need, this work presents a methodology to define an equivalent “interoperable” vehicle model, intended as a TSI-consistent reference whose Characteristic Wind Curves (CWCs) directly reproduce the regulatory Reference CWCs under the operating conditions prescribed by the standards. Formulated as an inverse calibration task, the problem is solved through a two-stage Bayesian Optimisation (BO) framework constrained by realistic data from a representative fleet of European high-speed trains. Operating over an input space comprising both multibody and standard-derived wind tunnel aerodynamic coefficients, the BO jointly adjusts these properties, followed by a final refinement based on a reparameterisation strategy for the aerodynamic curves. Applied to a high-speed baseline train, this framework validates a robust approach to define a standardized reference vehicle model, offering a consistent vehicle representation of TSI regulatory limits and ultimately supporting railway interoperability.

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