Options
Regularized machine learning for system identification of ship free-running manoeuvres from CFD-based synthetic data: a comparative study
Citation Link: https://doi.org/10.15480/882.17286
Publikationstyp
Preprint
Date Issued
2026
Sprache
English
TORE-DOI
Citation
R.F. Suárez, J.C. Berndt, and M. Abdel-Maksoud. Regularized machine learning for system identification of ship free-running manoeuvres from cfd-based synthetic data: A comparative study. Ocean Engineering, 2026. Manuscript submitted for publication.
Publisher
Elsevier
Peer Reviewed
false
This study investigates supervised machine learning techniques for identifying ship hydrodynamic coefficients from CFD-generated data from free-running simulations. Specifically, ordinary least squares and regularized regression methods are applied to Abkowitz-type manoeuvring models. Training and validation datasets are derived from URANS simulations of zig-zag and turning circle manoeuvres, which are validated against experimental benchmark data. The analysis evaluates the effects of coefficient set size, minimum training length required for predictive model training, and manoeuvre combinations on model performance. Results demonstrate the suitability of large-angle zig-zag manoeuvres for hydrodynamic system identification, provided that multicollinearity is addressed through appropriate coefficient selection, regression models, or input data variability. Larger coefficient sets offer greater model flexibility for variable conditions but are more prone to multicollinearity. Regularized regression techniques effectively mitigate multicollinearity and notably enhance prediction accuracy, as does incorporating more diverse manoeuvring data. Among tested models, Ridge regression provided the best compromise between computational efficiency and prediction accuracy.
Subjects
Ship Manoeuvring
System Identification
Abkowitz Model
Hydrodynamic Coefficients
Computational Fluid Dynamics
Machine Learning
DDC Class
623.8: Naval Architecture; Shipbuilding
Publisher‘s Creditline
R.F. Suárez: Conceptualization, Formal analysis, Investigation, Methodology, Resources, Visualization, Writing – original draft, review and editing.
J.C. Berndt: Conceptualization, Formal analysis, Investigation, Visualization, Methodology, Validation, Writing – original draft, review and editing.
M. Abdel-Maksoud: Investigation, Funding acquisition, Supervision, Writing - review and editing.
J.C. Berndt: Conceptualization, Formal analysis, Investigation, Visualization, Methodology, Validation, Writing – original draft, review and editing.
M. Abdel-Maksoud: Investigation, Funding acquisition, Supervision, Writing - review and editing.
Publication version
submittedVersion
Loading...
Name
Suarez_Berndt_Maksoud_2026-preprint.pdf
Type
Main Article
Size
52.96 MB
Format
Adobe PDF
Version History
You are currently viewing version 1 of the item.