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.

Fibre-reinforced composites are finding increased usage in load-bearing structures in a variety of applications in marine, automotive and rail transport industries owing to their specific strength and stiffness properties. A serious problem with these composite materials, particularly glass-reinforced polymeric composites, which are the most prevalent in marine and other surface transport applications, is that they support combustion and in fire conditions burn, most often with heavy soot and smoke. Insulation can reduce the fire hazard, but does not eliminate it. Moreover the insulation adds weight and cost to apply.The combustible part of the composite is organic resin matrix. Most common method of fire retarding the resin and hence, the overall composite is the physical and chemical modification of the resin by either adding fire retardant element in the polymer backbone or using fire retardant additives in the resin. For polyester or vinyl ester resins, usually halogenated chemicals are used. While the presence of halogen significantly reduces the flammability of the resin, due to increasing environmental awareness and strict environmental legislations thereof, halogen - containing fire retardants are being strictly scrutinised. When non-halogen flame retardants are used, invariably they are required in large quantities (>30% w/w) to achieve required level of fire retardancy. The high concentrations of additives however, can reduce the mechanical properties of the composite. Moreover, they also affect resin's processability for resin transfer moulding technique, commonly used for these types of composites. We propose here a step change in the resin matrix by reducing the combustibility of vinyl ester and/or polyester resin by co-blending with inherently fire retardant resins, such as phenolic or melamine-formaldehyde resin.This proposal is a joint attempt by 'Fire Materials' group at the University of Bolton and 'Fluid Structure Interactions Research Group (FSIRG) at the University of Southampton to develop, construct, test and model novel, fire-retardant composites, initially for marine applications. The principal focus is to develop a modified polymeric matrix to reduce the combustibility of the vinyl ester or polyester resins by blending with appropriately modified phenolic and melamine resins, which will increase the thermal stability and char-forming capacity of the matrix. The physical and chemical properties of the modified resin will be optimised to enable: (a) the resin to be infusible for moulding leading to good processing ability: (b) low temperature cure capability to maximize compatibility and bonding with glass fibres; and (c) up-scaling to produce large laminates and structures. It is proposed that two different approaches will be taken: the first one 'Material' based, mainly by Bolton, and the other 'Structure' based, to which both Bolton and Southampton will contribute. The specific tasks include resin blending, chemical / physical modification of the resin, process modelling and resin infusion, composite laminate preparation and flammability evaluation. The composite laminates and structures thus produced are expected to comply with the fire performance requirements contained in the International Convention for the Safety of Life at Sea (SOLAS) as `IMO/HSC Code (Code of Safety for High Speed craft of the International Maritime Organisation). Additionally, the structural performance of the composite would be expected to be comparable with current glass/vinyl ester. We also propose to conduct fire performance modelling, mechanical characterisation and progressive damage analysis from a structural design viewpoint.We expect these composites to find applications also in other engineering arenas for which low-weight, thermally resistant and fire-retardant structures are increasingly being sought.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Artificial Intelligence (AI) can have dramatic effects on industrial sectors and societies (e.g., Generative AI, facial recognition, autonomous vehicles). AI UK will pioneer a reflective, inclusive approach to responsible AI development that does not ignore AI's potential harms but acknowledges, understands and mitigates them for diverse societies. AI UK adopts a strong human-centred approach to ensure societies deploy and use AI in a responsible way by providing the AI community with a toolkit of technological innovations, case studies, guidelines, policies and frameworks for all key sectors of the economy. To achieve this, AI UK will deliver and drive a collaborative ecosystem of researchers, industry, policymakers and stakeholders that will be responsive to the needs of society, led by a team of experienced, well-connected leaders from all four nations of the UK, committed to an inclusive approach to the management of the programme. AI UK grows an interdisciplinary ecosystem that adopts Equality, Diversity and Inclusivity (EDI), Trusted Research, and Responsible Research and Innovation (RRI) as fundamental principles. AI UK will champion a research culture where everyone is respected, valued and able to contribute and benefit and coordinate the UK's AI research networks and programmes, working with key Research Council (and other funding) programmes, The Alan Turing Institute, The Ada Lovelace Institute, AI Standards hub, Centres for Doctoral Training, UKRI AI Research Hubs, Public Sector Research Establishments (PSREs) as well as the wider landscape of university-based Responsible/Ethical AI research institutes. AI UK will connect UK research to internationally leading research centres and institutions around the world. Ultimately, through this ecosystem, AI UK will deliver world-leading best practices for the design, evaluation, regulation and operation of AI-systems that benefit the nation and society. AI UK will invest in the following strands: Ecosystem Creation and Management: to define the portfolio of thematic areas, translational activities, and strategic partnerships with academia, business and government and associated impact metrics. This will broaden and consolidate the network nationally and internationally and identify course corrections to national policy (e.g., industrial strategy). Research & Innovation Programmes: to deliver consortia-led research that address fundamental challenges with multi-disciplinary and industrial perspectives, integrative research projects that link connected and established research teams across the community, and early stage and industry-led research and innovation projects to expand the UK's ecosystem and develop the next generation of leaders. Skills Programme: to translate research into skills frameworks and training for users, customers, and developers of AI, and to contribute to the call for the UK AI Strategy's Online Academy. Public and Policy Engagement: working with the network of policy makers, regulators, and key stakeholders to respond to arising concerns, need for new standards, build capacity for public accountability and provide evidence-based advice to the public and policymakers.

Autonomous Systems (AS) are cyberphysical complex systems that combine artificial intelligence with multi-layer operations. Security for dynamic and networked ASs has to develop new methods to address an uncertain and shifting operational environment and usage space. As such, we have developed an ambitious program to develop fundamental secure AS research covering both the technical and social aspects of security. Our research program is coupled with internationally leading test facilities for AS and security, providing a research platform for not only this TAS node, but the whole TAS ecosystem. To enhance impact, we have built a partnership with leading AS operators in the UK and across the world, ranging from industrial designers to frontline end-users. Our long-term goal is to translate the internationally leading research into real-world AS impact via a number of impact pathways. The research will accelerate UK's position as a leader in secure AS research and promote a safer society.