How Hull Shape Reduction Can Produce Energy Savings

This paper presents a hydrodynamic optimisation of hull shapes achievable through the implementation and integration of cascading computational tools, targeting reduction of energy consumption. Parametric modelling was applied to a hull by non-uniform rational spline (NURBS) using the Rhinoceros plug-in Grasshopper. Hull shape optimisation was performed by using IMPROVEit® software, which constitutes the interface between Grasshopper and OpenFOAM. The optimiser can use various methods such as radial basis functions, krigging, gradient methods, neural networks, genetic algorithms, evolutionary and stochastic algorithms. The main software idea is to identify an analytical function that acceptably reproduces the unknown real objective function. This principle, used to calculate the hydrodynamic forces, was appropriately validated using Wigley’s hull with experimental data from the literature. Validation was carried out on four Froude numbers, respectively, 0.250, 0.316, 0.350, and 0.408. Drag coefficient has shown a maximum relative error of –15.71% at the lowest Froude number. Then, the validated numerical framework was applied to model a ship hull with an overall length (LOA) of 30 m, and the results were discussed appropriately to highlight the differences reported by the optimisation. In conclusion, for Froude numbers between 0.291 and 0.350 there is good optimisation with a 1% improvement in resistance. For Froude number of 0.233, there is excellent optimisation with up to a 3.49% improvement in resistance, and thus with a maximum energy saving of 4%.