This work presents a Neural Network-based performance analysis and optimization of sailing configurations of an America’s Cup yacht. The analysis is based on experimental data only, gathered from the sailing records provided by the onboard telemetry to train the neural networks. The focus of the work is on the performance analysis, with the objective of maximizing boat speed (objective function) by varying the sailing setups (design variables). The neural network based on the experimental data is coupled with a genetic algorithm to determine the maximum boat speed and corresponding yacht settings at various wind speeds. More importantly, however, the paper demonstrates that multiple yacht sailing configurations can be analyzed instantaneously on a regular PC, thus providing a valuable analysis and prediction tool for the design and sailing teams.

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