Aerodynamic Performance and Layout Optimisation of Symmetrically Cambered Wing Sails for Wind-Assisted Ship Propulsion
Licentiate thesis, 2026

A growing need for sustainable maritime transport has driven the development of rigid wing sails. Symmetrically cambered profiles offer high thrust potential across many apparent wind angles, but their aerodynamic design and installation layout can still be further optimised. This licentiate thesis addresses these challenges through two complementary studies: the development of an aerofoil optimisation framework and an exploratory analysis of multi-sail layouts.

The first study develops a surrogate-based Bayesian optimisation method to reduce reliance on costly CFD simulations. A Gaussian Process surrogate model uses prediction uncertainty to guide the search for maximum average thrust over apparent wind angles from 10o to 150o. A hybrid parametrisation enables flexible aerofoil geometry variation. The optimised configuration has a more uniform thickness distribution and achieves an 8% thrust increase over the D2R10 benchmark, validated by high-fidelity IDDES.

The second study investigates the aerodynamic interference in multi-sail layouts using a two-dimensional inviscid method. Two configurations are considered: a triple in-line and a quad-sail parallel layout. Under a fixed total spacing, optimisation yields only limited performance improvements. The in-line layout experiences thrust losses of up to 6% compared to isolated sails. The parallel layout exhibits larger reductions ranging from 10% to 28%. These findings indicate that aerodynamic interference significantly affects multi-sail performance.

This thesis develops a Bayesian optimisation framework for multi-fidelity wing sail design. It shows how using a fast lower-fidelity solver can deliver measurable 3D aerofoil performance gains. The new parametrisation enables broad shape variation, revealing how geometric characteristics affect thrust. The framework also identifies trends and limitations in different layout configurations. These results provide insights to guide future wing sail design strategies.

wing-assisted ship propulsion

rigid wing sail

Aerodynamics

machine learning

multi-point optimisation

installation layout

Delta & Gamma
Opponent: Jan Östh, RISE (Research Institutes of Sweden), Sweden

Author

Stephan van Reen

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

GEneric Multidiscaplinary optimization for sail INstallation on wInd-assisted ships (GEMINI)

Swedish Transport Administration (2023/32107), 2023-09-01 -- 2026-08-31.

Subject Categories (SSIF 2025)

Fluid Mechanics

Marine Engineering

Vehicle and Aerospace Engineering

Publisher

Chalmers

Delta & Gamma

Online

Opponent: Jan Östh, RISE (Research Institutes of Sweden), Sweden

More information

Latest update

1/7/2026 2