@inproceedings{c1bb41f8b3f94c3aa0073d85cc81dbad,
title = "Contact Law Discovery via Symbolic Regression in Rotordynamics",
abstract = "This study integrates symbolic regression (SR) with rotor-bearing-impact dynamics for contact force identification. A hydrodynamic Jeffcott rotor is modeled using Kr{\"a}mer{\textquoteright}s approximation and the Hunt \& Crossley contact law with Coulomb friction. Using a physically-constrained loss function in PySR, the algorithm successfully recovers the exact Hunt \& Crossley functional form and parameters (stiffness and restitution) from clean data. Under 1\% Gaussian noise, the fundamental equation structure remains robust with minor parameter deviations. The results validate SR as an automated, interpretable approach for governing equation discovery in rotordynamics.",
keywords = "Contact mechanics, Hydrodynamic bearings, Impact modeling, Rotordynamics, Symbolic regression, System identification",
author = "Vianna, \{Vinicius S.\} and Machado, \{Tiago H.\} and Santos, \{Ilmar F.\}",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.; 12<sup>th</sup> IFToMM International Conference on Rotordynamics, IFToMM 2026 ; Conference date: 22-06-2026 Through 26-06-2026",
year = "2026",
doi = "10.1007/978-3-032-29033-5\_32",
language = "English",
isbn = "9783032290328",
series = "Mechanisms and Machine Science",
publisher = "Springer",
pages = "367--376",
booktitle = "Proceedings of the 12th IFToMM International Conference on Rotordynamics - Volume 1",
}