Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings

M.C. Wohlleben, J. Schütte, M.B. Berkemeier, S. Peitz, W. Sextro, (2025).

Download
No fulltext has been uploaded.
Preprint | Published | English
Abstract
<title>Abstract</title> <p>Rubber-metal bushings (RMB) are critical components in multi-body systems, such as vehicles and industrial machinery, due to their abilityto enable relative motion, dampen vibrations, and transmit forces. However,their nonlinear behavior challenges accurate modeling. Traditional physics-based models often fail to balance simplicity, accuracy, and computationalefficiency. The growing availability of experimental data offers opportunitiesto improve RMB modeling through hybrid and data-driven approaches. Thisstudy evaluates physics-based, hybrid, and data-driven methods based on predictive accuracy, modeling effort, and computational cost. Hybrid approaches,combining machine learning techniques with physics-based models, are investigated to leverage their complementary strengths. Results show that hybridmethods enhance accuracy for simpler models with a modest increase in computational time. This highlights their potential to simplify RMB modelingwhile balancing accuracy and efficiency, offering insights for advancing multi-body system simulations. Building on these insights, data-driven methods areexplored for their ability to provide surrogate models for dynamical systemswithout requiring expert knowledge. Experiments reveal that while simpledata-driven methods approximate system behavior when data has low variance, they fail with trajectories of widely varying frequency and amplitude.</p>
Publishing Year
LibreCat-ID

Cite this

Wohlleben MC, Schütte J, Berkemeier MB, Peitz S, Sextro W. Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings. Published online 2025.
Wohlleben, M. C., Schütte, J., Berkemeier, M. B., Peitz, S., & Sextro, W. (2025). Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings. Springer Science and Business Media LLC.
@article{Wohlleben_Schütte_Berkemeier_Peitz_Sextro_2025, title={Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings}, publisher={Springer Science and Business Media LLC}, author={Wohlleben, Meike Claudia and Schütte, Jan and Berkemeier, Manuel Bastian and Peitz, Sebastian and Sextro, Walter}, year={2025} }
Wohlleben, Meike Claudia, Jan Schütte, Manuel Bastian Berkemeier, Sebastian Peitz, and Walter Sextro. “Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings.” Springer Science and Business Media LLC, 2025.
M. C. Wohlleben, J. Schütte, M. B. Berkemeier, S. Peitz, and W. Sextro, “Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings.” Springer Science and Business Media LLC, 2025.
Wohlleben, Meike Claudia, et al. Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings. Springer Science and Business Media LLC, 2025.

Export

Marked Publications

Open Data LibreCat

Search this title in

Google Scholar