Our proposed research aims to develop an ocean wave imaging analyser to predict wave- vessel-payload-crew interaction. This is a currently missing prerequisite for optimal seakeeping of fast vessels. Seakeeping, concerning the control of vessel motion when subjected to waves and the resulting effects on humans, systems, and mission capacity, remains one of the biggest challenges in maritime safety. Vessel operational practices (48%) and human factors (17%), both key to seakeeping, have been the main safety recommendations amongst 1212 investigations, conducted by the European Maritime Safety Agency in the past decade.
Before making any control decisions, mitigating detrimental effects on seakeeping requires accurate and real-time modelling of the approaching waves in the perimeter of the vessel. The predicted wave loading is essential for any precise estimation of vessel motion, but it is absent. To derive such a model, 3D wave geometry evolving in real time - a dynamic 4D scene - is required. However, the computational time required for existing sensing and modelling approaches are too long for the decision windows of any vessel operations. This process presently takes more than tens of seconds in order to anticipate and react at close proximity. This leads to three specific challenges we propose to tackle.
1) Develop a real-time stereo wave imaging system for fast vessels to create an imaging database in order to reconstruct accurate 4D wave scenes.
2) Reduce inference time of extracting wave dynamic features, e.g. wave propagation speed, direction, magnitude by comparing and adapting different deep learning methods.
3) Predict dynamic loading on the vessel, payload and crew from reconstructed 4D wave.
Storms are expected to become more common and severe due to climate change. The maritime industries, including fishing, marine science, defence, offshore energy, and search and rescue services, will need to adapt. A shock mitigation strategy is essential for all crafts that undertake rough water transits manned or unmanned. In heavy seas, 'wave slams' induce high-acceleration events exposing occupants to mechanical shocks and whole-body vibration of extreme magnitudes with severe chronic and acute consequences on human health. The UK regulation based on the Control of Vibration Work Regulations 2005 and the Merchant Shipping and Fishing Vessel Regulations 2007, with daily limits for shock and vibration exposure. Similar legislation applies throughout Europe and other countries. It is not always practicable for fast vessel operators to carry out necessary activities and duties while complying with these limits. In many situations, crew shock and vibration exposures are the limiting factor of the operational capability.
It is practical to provide crew with shock mitigating seating. Seats or cabs, however, protect the crew, but not the hull, hull-mounted equipment or payload. If the coxswain continues to drive to the same discomfort level, the loading on the vessel will be increased with the potential of immediate and long-term damages. This is a current area of concern in the whole industry. An experienced coxswain can maintain a high speed while mitigating the impact severity via constant adjustment of the helm and throttle. This skillset requires understanding of many factors: the characteristics of the oncoming wave and the likely response of the vessel and crew.
The development of an 'intelligent' imaging system capable of reading the dynamic oncoming sea, sensing craft motion, and its effects on crew and cargo will be essential to the seakeeping and maritime safety.
Our industrial-driven research will address this challenge through extensive onboard stereo imaging experimentation, state-of-the-art numerical modelling and development of new artificial intelligence framework. The outcomes will transform critical operational safety of merchant shipping, fishing, defence, offshore energy assets, rescue services.
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