TUESDAY, 5th DECEMBER 2017 GABE__5_DEC_17.doc
“TOWARDS HIGH SPEED MACHINE LEARNING ROLL DAMPING PREDICTIONS"
DR. GABRIEL D. WEYMOUTH, PhD
Associate Professor, Southampton Marine
and Maritime Institute
University of Southampton
Meeting to be held at
Lloyds Register (LR), 71 Fenchurch Street, London EC3M, 4BS
at 17:30 for 18:15 hours (duration approximately 1 hour)
New materials, manufacturing methods, and autonomous systems are enabling vessel designs which push the limits of conventional high-speed Naval Architecture design tools. This has driven many efforts to speed up computational fluid dynamic predictions to replace our linearized and potential flow models. In this work we study the utility of open source "black-box" machine learning methods to learn the highly nonlinear problem of roll damping. Specifically, we use computational fluid dynamic simulations of a family of bilge keels and operating conditions to train Neural Networks to predict roll damping coefficients. We find that while the networks are capable of predicting the nonlinear flow to an accuracy of 12-15%, this requires many hundreds of examples. Therefore, while these open source tools may be of great use in simplifying predictions of well documented systems, a more data insensitive method is required for exploration of new vessel designs.
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