Seakeeping optimization of cruise ship based on artificial neural networks

Resumen

Seakeeping of ships is a key parameter for their operation, and is traditionally assessed based on either experimentation in model basins or through numerical models. And nowadays Artificial Intelligence (AI) is having a great development boosted by the increased of computational capabilities. But no many works can be found applying AI for seakeeping prediction. In this work a pre-trained Artificial Neural Network (ANN) will be used to assess the seakeeping performance for specific scenarios. The main advantage of using this algorithm is that it allows to compute a large number cases in almost no time if compared with traditional approaches. In this work the seakeeping performance for a cruise ship under millions of parametric variations of the principal dimensions will be computed for different Sea States. The main objective is to determine the principal form coefficients and dimensions with a predefined criterion in order to obtain the best seakeeping performance. Most relevant conclusions will be shown.