This work focuses on the hydrodynamic investigation of a RoRo cargo ship through full-scale RANS (Reynolds-Averaged Navier-Stokes) simulations in calm water conditions. Conducted as part of the EU-funded Retrofit55 project, the study aims to validate the bow optimization process based on a multi-fidelity surrogate model that integrates high-fidelity and low-fidelity potential flow solver solutions to reduce total drag. The open-source finite-volume CFD library OpenFOAM is used to perform the RANS simulations on both the original and optimized shape. This paper highlights the synergy of combining the computational efficiency of potential flow methods with the high-fidelity accuracy of full-scale RANS simulations. This approach provides both efficient optimization and reliable performance verification, paving the way for broader applications in ship design and energy efficiency improvements.

Full-Scale RANS Validation of Multi-Fidelity Bow Optimization for a RoRo Cargo Ship

A. DEL BUONO
;
R. BROGLIA;A. SERANI;M. DIEZ;
2025

Abstract

This work focuses on the hydrodynamic investigation of a RoRo cargo ship through full-scale RANS (Reynolds-Averaged Navier-Stokes) simulations in calm water conditions. Conducted as part of the EU-funded Retrofit55 project, the study aims to validate the bow optimization process based on a multi-fidelity surrogate model that integrates high-fidelity and low-fidelity potential flow solver solutions to reduce total drag. The open-source finite-volume CFD library OpenFOAM is used to perform the RANS simulations on both the original and optimized shape. This paper highlights the synergy of combining the computational efficiency of potential flow methods with the high-fidelity accuracy of full-scale RANS simulations. This approach provides both efficient optimization and reliable performance verification, paving the way for broader applications in ship design and energy efficiency improvements.
2025
Istituto di iNgegneria del Mare - INM (ex INSEAN)
978-1-64368-610-3
Multi-fidelity
Full-Scale
RANS
Shape optimization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/566083
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