Ship resistance estimation is one of the most important problems to be solved by naval architects at the early stages of the ship design project. This paper presents a comparison of methods that are used to estimate the resistance value of a vessel, studying the two terms that are the most relevant, the viscous resistance (depending on the form factor) and the resistance to waves, that appears in any floating device. This work focuses on the estimation of the form factor since it is a parameter difficult to estimate in the design early phases, and it is not always available in the measurements provided by real experiments with ship prototypes in towing tanks. Different estimation methods are applied and they are compared with the direct estimation and with the prediction obtained with a feedforward neural network. The results support the suitability of the neural networks to identify these vessel shape and wave related variables.
CITATION STYLE
Marón, D., & Santos, M. (2019). Wave and Viscous Resistance Estimation by NN. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11872 LNCS, pp. 161–168). Springer. https://doi.org/10.1007/978-3-030-33617-2_18
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