contributor author | Bisinotto, Gustavo A. | |
contributor author | de Mello, Pedro C. | |
contributor author | Cozman, Fabio G. | |
contributor author | Tannuri, Eduardo A. | |
date accessioned | 2024-04-24T22:44:20Z | |
date available | 2024-04-24T22:44:20Z | |
date copyright | 2/13/2024 12:00:00 AM | |
date issued | 2024 | |
identifier issn | 0892-7219 | |
identifier other | omae_146_5_051204.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4295783 | |
description abstract | The directional wave spectrum, which describes the distribution of wave energy along frequencies and directions, can be estimated from the measured motions of a vessel subjected to a particular sea condition by resorting to the wave-buoy analogy. Several methods have been proposed to address the inverse estimation problem; recently, machine learning techniques have been assessed as further alternatives. However, it may be difficult to gather large datasets of in-service motion responses and the associated sea states to train effective data-driven models. In this work, an encoder–decoder neural network is trained with the synthetic responses of a station-keeping platform supply vessel (PSV) to estimate the directional wave spectrum. This estimation model is directly applied to perform wave inference from motion data of wave basin tests with a small-scale model of the same vessel. Furthermore, fine-tuning is also used to incorporate experimental data into the neural network model. Results show a satisfactory match between estimated and measured values, both with respect to the energy distribution and the integral spectrum parameters, indicating that the proposed approach can be employed to obtain data-driven wave inference models when there is little or no availability of measured motion records and the corresponding sea conditions. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Motion-Based Wave Inference With Neural Networks: Transfer Learning From Numerical Simulation to Experimental Data | |
type | Journal Paper | |
journal volume | 146 | |
journal issue | 5 | |
journal title | Journal of Offshore Mechanics and Arctic Engineering | |
identifier doi | 10.1115/1.4064618 | |
journal fristpage | 51204-1 | |
journal lastpage | 51204-9 | |
page | 9 | |
tree | Journal of Offshore Mechanics and Arctic Engineering:;2024:;volume( 146 ):;issue: 005 | |
contenttype | Fulltext | |