CFD-based prediction of vessel manoeuvring performance in deep and shallow water
Abstract
The manoeuvring characteristics of a vessel can differ significantly between unrestricted and finite water depths. Therefore, the ability to predict and assess the manoeuvring performance of a vessel operating in various depths is crucial for ensuring safe operation at sea. Traditionally, vessel manoeuvrability in deep and shallow water has been investigated through model-scale experiments. While experiments provide reliable benchmark data, they are not without limitations. In particular, scale effects introduce uncertainty when extrapolating model scale results to full scale, while measurements can be affected by limited tank dimensions and the applied test procedures. To complement experiments and overcome some of their drawbacks, recent advances in Computational Fluid Dynamics (CFD) have made it possible to directly predict the full-scale manoeuvring capabilities of a vessel while accounting for viscous and environmental effects. In this work, the manoeuvrability of a full-scale research vessel in varying water depths was investigated using unsteady Reynolds-Averaged Navier–Stokes (RANS) simulations. Deep water simulations were compared with full-scale measurements and showed good agreement with experimental data. The vessel showed improved manoeuvrability in shallow water as the depth-to-draught ratio decreased to 1.5. However, further reduction in water depth led to a deterioration of manoeuvring performance, suggesting the presence of a critical depth below which vessel manoeuvrability worsens. Additionally, results highlighted the importance of induced velocity correction and the inclusion of propeller side forces in manoeuvring simulations.
Fields of Study & Subjects
Ship Hydrodynamics and Maneuverability
Maritime Navigation and Safety
Fluid Dynamics Simulations and Interactions
Publication details
- Journal / source
- International Journal of Naval Architecture and Ocean Engineering
- Publisher
- Elsevier BV
- Volume
- 18
- Pages
- 100774–100774
- Publication date
- 1 January 2026
- Language
- EN