[HTML][HTML] Ship maneuvering in shallow and narrow waters: predictive methods and model development review
M Maljković, I Pavić, T Meštrović… - Journal of marine science …, 2024 - mdpi.com
The maneuverability of ships is influenced by several factors, including ship design, size,
propulsion system, hull shape, and external conditions such as wind, waves, and currents …
propulsion system, hull shape, and external conditions such as wind, waves, and currents …
Data-Driven system identification of 6-DoF ship motion in waves with neural networks
Critical evaluation of ship responses in the ocean is important for not only the design and
engineering of future platforms but also the operation and safety of those that are currently …
engineering of future platforms but also the operation and safety of those that are currently …
Geometric moment-dependent global sensitivity analysis without simulation data: application to ship hull form optimisation
In this work, we propose and test a method to expedite Global Sensitivity Analysis (GSA) in
the context of shape optimisation of free-form shapes. To leverage the computational burden …
the context of shape optimisation of free-form shapes. To leverage the computational burden …
On the use of dynamic mode decomposition for time-series forecasting of ships operating in waves
In order to guarantee the safety of payload, crew, and structures, ships must exhibit good
seakee**, maneuverability, and structural-response performance, also when they operate …
seakee**, maneuverability, and structural-response performance, also when they operate …
Time-series forecasting of ships maneuvering in waves via dynamic mode decomposition
A data-driven and equation-free approach is proposed and discussed to forecast responses
of ships maneuvering in waves, based on the dynamic mode decomposition (DMD). DMD is …
of ships maneuvering in waves, based on the dynamic mode decomposition (DMD). DMD is …
A multi-fidelity active learning method for global design optimization problems with noisy evaluations
A multi-fidelity (MF) active learning method is presented for design optimization problems
characterized by noisy evaluations of the performance metrics. Namely, a generalized MF …
characterized by noisy evaluations of the performance metrics. Namely, a generalized MF …
A data driven method for multi-step prediction of ship roll motion in high sea states
Ship roll motion in high sea states has large amplitudes and nonlinear dynamics, and its
prediction is significant for operability, safety, and survivability. This paper presents a novel …
prediction is significant for operability, safety, and survivability. This paper presents a novel …
Time-series forecasting for ships maneuvering in waves via recurrent-type neural networks
The prediction capability of recurrent-type neural networks is investigated for real-time short-
term prediction (nowcasting) of ship motions in high sea state. Specifically, the performance …
term prediction (nowcasting) of ship motions in high sea state. Specifically, the performance …
Comparing multi-index stochastic collocation and multi-fidelity stochastic radial basis functions for forward uncertainty quantification of ship resistance
This paper presents a comparison of two multi-fidelity methods for the forward uncertainty
quantification of a naval engineering problem. Specifically, we consider the problem of …
quantification of a naval engineering problem. Specifically, we consider the problem of …
Recurrent-type neural networks for real-time short-term prediction of ship motions in high sea state
The prediction capability of recurrent-type neural networks is investigated for real-time short-
term prediction (nowcasting) of ship motions in high sea state. Specifically, the performance …
term prediction (nowcasting) of ship motions in high sea state. Specifically, the performance …