Collaboration is described on assessment of computational fluid dynamics (CFD) predictions for surface combatant model 5415 at static drift β = 0 deg and 20 deg using recent tomographic particle image velocimetry (TPIV) experiments. Assessment includes N-version verification and validation to determine the confidence intervals for CFD solutions/codes, and vortex onset, progression, instability, and turbulent kinetic energy (TKE) budget analysis. The increase in β shows the following trends. Forces and moment increase quadratically/cubically, and become unsteady due to shear layer, Karman and flapping instabilities on the bow. Wave elevation becomes asymmetric; its amplitude increases, but the total wave elevation angle remains same. The vortex strength and TKE increase by about two orders of magnitude, and for large β, the primary vortices exhibit helical mode instability similar to those for delta wings. Forces and moment for both β and wave elevation for β = 0 deg are compared within 4% of the data, and are validated at 7% interval. Wave elevation for β = 20 deg, and vortex core location and velocities for both β are compared within 9% of the data, and are validated at 12% interval. The vortex strength and TKE predictions show large 70% errors and equally large scatter and are not validated. Thus, both errors and scatter need reduction. TKE budgets show transport of turbulence into the separation bubble similar to canonical cases, but pressure transport is dominant for ship flows. Improved CFD predictions require better grids and/or turbulence models. Investigations of solution-adaptive mesh refinement for better grid design and hybrid Reynolds-averaged Navier-Stokes/large eddy simulation models for improved turbulent flow predictions are highest priority.

The seakeeping ability of ships is one of the aspects that needs to be assessed during the design phase of ships. Traditionally, potential flow calculations and model tests are employed to investigate whether the ship performs according to specified

The present paper proposes a new mixed-fidelity method to optimize the shape of ships using genetic algorithms (GA) and potential flow codes to evaluate the hydrodynamics of variant hull forms, enhanced by a surrogate model based on an Artificial Neural Network (ANN) to account for viscous effects. The performance of the variant hull forms generated by the GA is evaluated for calm water resistance using potential flow methods which are quite fast when they run on modern computers. However, these methods do not take into account the viscous effects which are dominant in the stern region of the ship. Solvers of the Reynolds-Averaged Navier-Stokes Equations (RANS) should be used in this respect, which, however, are too time-consuming to be used for the evaluation of some hundreds of variants within the GA search. In this study, a RANS solver is used prior to the execution of the GA to train an ANN in modeling the effect of stern design geometrical parameters only. Potential flow results, accounting for the geometrical design parameters of the rest of the hull, are combined with the aforementioned trained meta-model for the final hull form evaluation. This work concentrates on the provision of a more reliable framework for the evaluation of hull form performance in calm water without a significant increase of the computing time.

A method for optimizing hull forms with respect to their hydrodynamic performance in calm and rough water is presented. The method is based on an initial optimization of a parent hull form for seakeeping and the improvement of the resulting optimum hull form for calm water resistance. In the first part of the method, variant hull forms differing from a parent in the main dimensions and/or in one or more hull form parameters, such as CWP, LCF, CB, LCB, KB, CP, are automatically generated and their seakeeping qualities evaluated. When appropriate ranges for the principal characteristics and parameters of the hull form under investigation are prescribed, a formal optimization procedure is used to obtain the variant with the best seakeeping behavior. The weighted sum of the resonant values of selected ship responses for a number of ship speeds and headings in regular waves forms the objective function. The Hooke and Jeeves algorithm is used to accomplish the optimization. The procedure results in a set of trends regarding the proposed variations of the selected hull form parameters, within the specified constraints. These trends are then applied on the parent hull to derive an optimized hull form with fair lines. Subsequently, this hull form can be locally modified to improve its calm water resistance or, as it should be done, its propulsion characteristics. The applicability of the method is demonstrated in two cases: a conventional reefer ship and a naval destroyer. Scaled models of the parent and the optimized hull forms have been tested for calm water resistance and seakeeping. In both cases the validity of the methodology is demonstrated.

The operational profiles of both commercial and naval ships encompass a range of speeds below the service speed. On the way to estimating their performance at these speeds, the varying effect of hull roughness should be quantified. Roughness constitutes a significant resistance component superimposed on skin frictional resistance, which deteriorates ship performance by increasing power requirements and CO₂ emissions to retain a specified speed or, equivalently, by reducing attained speed at a given power. This paper exploits the single available full-scale records of a naval combatant and the Computational Fluid Dynamics (CFD) calculations for a well-known containership to compose a methodology to derive the speed dependence of fouling on ship performance at reduced speed based on the respective effect at service speed. Sailing at reduced speed, either imposed by the charter contract for fuel economy (slow steaming) or due to adverse sea conditions, resulting in excessive ship dynamic responses and/or added resistance in waves, is a quite common situation, occurring for the whole period of charter contracts or a significant portion of it, respectively. This study concluded that the roughness effect reduces drastically with speed, supporting shipowners to compose a more reliable charter contract and shipping companies to derive a realistic dry-docking plan.