CFD prediction and validation of ship-bank interaction in a canal
Zou, L.; Larsson, L.; Delefortrie, G.; Lataire, E. (2011). CFD prediction and validation of ship-bank interaction in a canal, in: Pettersen, B. et al. (Ed.) 2nd International Conference on Ship Manoeuvring in Shallow and Confined Water: Ship to Ship Interaction, May 18 - 20, 2011, Trondheim, Norway. pp. 413-422
In: Pettersen, B. et al. (2011). 2nd International Conference on Ship Manoeuvring in Shallow and Confined Water: Ship to Ship Interaction, May 18 - 20, 2011, Trondheim, Norway. Flanders Hydraulics Research/Ghent University/Norwegian Marine Technology Research Institute/Norwegian University of Science and Technology (NTNU)/The Royal Institute of Naval Architects: London. ISBN 978-1-905040-83-4. X, 422 pp., more
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Document type: Conference paper
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| Keywords |
Harbours and waterways > Wave generation by ships > Influence on banks and bottom
Numerical calculations
Physical modelling
Water bodies > Inland waters > Canals
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| Author keywords |
Computational Fluid Dynamics (CFD); Numerieke stromingsleer; Ship-bank interactions; Schip-oeverinteracties |
| Authors | | Top |
- Zou, L.
- Larsson, L.
- Delefortrie, G., more
- Lataire, E., more
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| Abstract |
This paper utilizes CFD (Computational Fluid Dynamics) methods to investigate the bank effects on a tanker moving straight ahead at low speed in a canal characterized by surface piercing banks. For varying water depths and ship-tobank distances, the sinkage and trim as well as the viscous hydrodynamic forces on the hull are predicted mainly by a steady state RANS (Reynolds Averaged Navier-Stokes) solver, in which the double model approximation is adopted to simulate the flat free surface. A potential flow method is also applied to evaluate the effect of the free surface and viscosity on the solutions. In addition, focus is placed on V&V (Verification and Validation) based on a grid convergence study and comparison with EFD (Experimental Fluid Dynamics) data, as well as the exploration of the modelling error in RANS computations to enable more accurate and reliable predictions of the bank effects. |
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