The Smart Detection of Ship Severe Roll Motions and Decision-Making for Evasive Actions

This paper presents a numerical model for the smart detection of synchronous and parametric roll resonance of a ship. The model implements manoeuvring equations superimposed onto ship dynamics in waves. It also features suited autopilot and rudder actuator models, aiming at a fair depiction of the control delay. The developed method is able to identify and distinguish between synchronous and parametric roll resonance, based on the estimation of encounter wave period from ship motions. Therefore, it could be useful as a smart tool for manned vessels and, also, in the perspective of unmanned and autonomous vessels (in the paper it is assumed a hypothetical remote crew). Once the resonance threat is identified, different evasive actions are simulated and compared, based on course and speed change. Calculations are carried out on a ro-ro pax vessel vulnerable to parametric roll. We conclude that, in roll resonance situations, and in the absence of roll stabilisation systems on-board, course change could be the most effective countermeasure.

SVR-Based Parametric Identification for Parametric Roll Resonance of Ships in Longitudinal Regular Waves

Parametric roll resonance, as a nonlinear phenomenon related to ship stability, is particularly apt to happen when a ship is sailing in longitudinal waves. It can generate sudden oscillation with large amplitude up to 30–40 degrees of roll and put the ship and crew in danger. To predict the parametric roll resonance of ships, a suitable model for describing this phenomenon is needed. In this paper, a nonlinear mathematical model considering the strong nonlinear coupling among the heave, roll, and pitch motions of ships is established, and support vector regression (SVR) is applied to identify the unknown damping and restoring coefficients in the mathematical model. To verify the accuracy and validity of SVR in parametric identification, a container ship is considered, and the coupled heave, roll, and pitch motions of the ship in longitudinal regular waves are simulated. Based on the simulated responses, the unknown coefficients in the mathematical model are identified by SVR. Then the coupled heave-roll-pitch motion of the container ship in regular waves is predicted by using the identified coefficients in comparison with the simulated data, and satisfactory agreement is achieved. From this study, it is concluded that SVR can be applied to identify the unknown coefficients in the nonlinear mathematical model for predicting the parametric roll resonance of ships in longitudinal regular waves.

Investigation of Parametric Resonance in Roll for Container Carrier Ships

Parametric roll resonance is of concern for container and fishing vessels, especially in head-sea waves. Here this phenomenon is investigated with a numerical method based on potential-flow theory with viscous corrections for the roll damping. The seakeeping problem is handled by considering a strip theory and assuming a 5-DOF system. Nonlinearities are accounted for in the Froude-Krylov and hydrostatic loads. The solver has been validated against experiments on a C11 class container carrier ship in terms of parametric resonance occurrence and features for different ship forward speeds and headings, wavelengths, wave amplitudes and wave headings. The overall agreement is good but there are some discrepancies. For instance, the simulations show capsizing in some cases while it does not happen in the experiments. The results from present method can be used to generate 2D and 3D polar diagrams identifying the zones with parametric roll occurrence, and are very handy for masters aboard ships. This type of information is valuable at design stage and can be used aboard vessels for a safer voyage.