CFD verification and validation of added resistance and motions of KVLCC2 with fixed and free surge in short and long head waves

The paper aims at providing a comprehensive and up-to-date review on the latest achievements made in the context of particle methods, in particular the projection-based ones, with applications in ocean engineering. The latest achievements corresponding to stability, accuracy, energy conservation and boundary condition enhancements as well as advancements related to improved simulations of multiphase flows, surface tension and fluid–structure interactions are reviewed. The future perspectives for enhancement of applicability and reliability of these methods for ocean engineering applications are also highlighted.

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Current achievements and future perspectives for projection-based particle methods with applications in ocean engineering

Particle methods in ocean and coastal engineering

COLREGs-compliant multiship collision avoidance based on deep reinforcement learning

Deep reinforcement learning (DRL) has excellent performance in continuous control problems and it is widely used in path planning and other fields. An autonomous path planning model based on DRL is proposed to realize the intelligent path planning of unmanned ships in the unknown environment. The model utilizes the deep deterministic policy gradient (DDPG) algorithm, through the continuous interaction with the environment and the use of historical experience data; the agent learns the optimal action strategy in a simulation environment. The navigation rules and the ship's encounter situation are transformed into a navigation restricted area, so as to achieve the purpose of planned path safety in order to ensure the validity and accuracy of the model. Ship data provided by ship automatic identification system (AIS) are used to train this path planning model. Subsequently, the improved DRL is obtained by combining DDPG with the artificial potential field. Finally, the path planning model is integrated into the electronic chart platform for experiments. Through the establishment of comparative experiments, the results show that the improved model can achieve autonomous path planning, and it has good convergence speed and stability.

An Autonomous Path Planning Model for Unmanned Ships Based on Deep Reinforcement Learning

Automatic collision avoidance of multiple ships based on deep Q-learning

This paper describes latest collaborative researches between Japan and the UK on parametric roll resonance of a container ship in following and head seas with realistic modelling of restoring moment as a nonlinear function of wave steepness in experimental, geometrical and analytical approaches. Firstly, captive model experiments were conducted, and demonstrated that the Froude-Krylov prediction could overestimate the amplitude of its variation. Secondly, Poincare mapping technique applied to the numerical model with measured time-varying restoring moment was used for tracing stable steady states, and revealed symmetry-breaking, period-doubling, chaos and capsizing associated with parametric roll resonance. Thirdly, an averaging method was applied to the same numerical model, and confirmed good agreement with the Poincare mapping as well as subcritical bifurcation. Finally, by utilising the present numerical model and methodology, it is shown that a requirement of higher metacentric height does not always improve safety for capsizing associated with parametric roll resonance.

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Nonlinear dynamics on parametric roll resonance with realistic numerical modelling

By utilizing a four-degrees-of-freedom numerical model with dense grids of control parameters and the sudden-change concept, the qualitative aspects of the nonlinear motions of a fishing vessel complying with the International Maritime Organization's intact stability criteria in following and quartering seas were intensively explored. As a result, capsizing due to broaching, capsizing without broaching, broaching without capsizing, stable surf-riding, and steady periodic motion were identified. The natures of the boundaries of these motions in the control parameter plane were investigated, and the effects of the initial conditions and the nonlinearity of calm-water maneuvering forces are also discussed. Furthermore, comparisons with a model experiment showed that the numerical model used here qualitatively explains capsizing phenomena, but quantitatively overestimates the danger of capsizing.

Hirotada Hashimoto

Papers

Automatic collision avoidance of multiple ships based on deep Q-learning

Nonlinear dynamics on parametric roll resonance with realistic numerical modelling

Qualitative aspects of nonlinear ship motions in following and quartering seas with high forward velocity

CFD, system-based and EFD study of ship dynamic instability events: Surf-riding, periodic motion, and broaching

Head-wave parametric rolling of a surface combatant