Ever since the jet age began in the 1950s, governments, scientists, and engineers have been acutely aware of the health effects created by aircraft noise--the prolonged exposure of which is highly damaging to human health. Increased noise pollution, for example, has been linked to cognitive impairment and behavioural issues in children, sleep disturbance (and consequent health issues therefrom) as well as the obvious hearing damage caused by the repeated intrusion of high levels of noise. The World Health Organization estimates that 1-million healthy life years are lost in Europe due to noise; this is mainly by cardiovascular disease via the persistent increase in stress level-with aviation noise being the largest contributor here. Moreover, the Aviation Environment Federation found that these issues place a £540M/year burden on UK government expenditure. While there has been tremendous progress in understanding aircraft noise, the doubling of flights in the past 20 years to a staggering 40 million (in the pre-Covid year 2019) has heightened the need for research into the physics of jet noise to uncover new reduced-order turbulence models. This proposal develops a novel mathematical model for jet flow turbulence using asymptotic analysis. The re-constructed turbulence structure will be used within a numerical code for fast noise prediction of a high-speed axisymmetric jet flow. Fundamentally, a jet flow breaking down into turbulence creates pressure fluctuations that propagate away as sound. In 1952, Lighthill showed that the Navier-Stokes equations can be exactly re-arranged into a form where a wave operator acting on the pressure fluctuation, is equal to the double-divergence of the jet's Reynolds stress. When the auto-covariance of the Reynolds stress was assumed to be known for a fluid at rest, scaling properties of the acoustic spectrum were obtained such as the celebrated 8th power law. The generalized acoustic analogy formulated by Goldstein in 2003 advanced this idea by dividing the fluid mechanical variables into a steady base flow and its perturbation. The acoustic spectrum per unit volume is a tensor product of a propagator and the auto-covariance of the purely fluctuating Reynolds stress tensor. The propagator can be calculated by determining the Green's function of the Linearized Euler operator for an appropriate jet base flow however, as in Lighthill's theory, the auto-covariance tensor is assumed to be known, which invariably requires the use of Large-Eddy Simulation (LES) and experiments to obtain an approximate functional form for it. But LES data still uses immense computational resources and computing time when different nozzle operating points are needed for design optimization or when complex jets are considered. What makes any alternative to modelling so complex is that the turbulence closure problem precludes a closed-form theory for the auto-covariance tensor. However, our recent work revealed that the peak noise can be accurately predicted when the propagator is determined at low frequencies that are of the same order as the jet spread rate (that is lesser than unity). This proposal, therefore, sets out an alternative, first-of-its-kind, analytical approach to determine the fluctuating Reynolds stress for a given mean flow solution. By solving the governing equations at this asymptotic scaling where the jet evolves temporally at the same rate it spreads in space, we determine the Large-Scale Turbulence (LST) structure in the jet. This approach is defined by a 2-dimensional system of equations for an axisymmetric jet and the computational time is expected to be an order-of-magnitude faster than LES. The LST-based solution of the Reynolds stress auto-covariance for peak jet noise will be compared to LES data provided by our project partners at several jet operating conditions. We aim to show that the LST model of turbulence provides accurate noise predictions and is a viable alternative to LES.

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.

Development of materials has underpinned human and societal development for millennia, and such development has accelerated as time has passed. From the discovery of bronze through to wrought iron and then steel and polymers the visible world around has been shaped and built, relying on the intrinsic properties of these materials. In the 20th century a new materials revolution took place leading to the development of materials that are designed for their electronic (e.g. silicon), optical (e.g. glass fibres) or magnetic (e.g. recording media) properties. These materials changed the way we interact with the world and each other through the development of microelectronics (computers), the world wide web (optical fibre communications) and associated technologies. Now, two decades into the 21st century, we need to add more functionality into materials at ever smaller length-scales in order to develop ever more capable technologies with increased energy efficiency and at an acceptable manufacturing cost. In pursuing this ambition, we now find ourselves at the limit of current materials-processing technologies with an often complex interdependence of materials properties (e.g. thermal and electronic). As we approach length scales below 100s of nanometres, we have to harness quantum effects to address the need for devices with a step-change in performance and energy-efficiency, and ultimately for some cases the fundamental limitations of quantum mechanics. In this programme grant we will develop a new approach to delivering material functionalisation based on Nanoscale Advanced Materials Engineering (NAME). This approach will enable the modification of materials through the addition (doping) of single atoms through to many trillions with extreme accuracy (~20 nanometres, less than 1000th the thickness of a human hair). This will allow us to functionalise specifically a material in a highly localised location leaving the remaining material available for modification. For the first time this will offer a new approach to addressing the limitations faced by existing approaches in technology development at these small length scales. We will be able to change independently a material's electronic and thermal properties on the nanoscale, and use the precise doping to deliver enhanced optical functionality in engineered materials. Ambitiously, we aim to use NAME to control material properties which have to date proven difficult to exploit fully (e.g. quantum mechanical spin), and to control states of systems predicted but not yet directly experimentally observed or controlled (e.g. topological surface states). Ultimately, we may provide a viable route to the development of quantum bits (qubits) in materials which are a pre-requisite for the realisation of a quantum computer. Such a technology, albeit long term, is predicted to be the next great technological revolution NAME is a collaborative programme between internationally leading UK researchers from the Universities of Manchester, Leeds and Imperial College London, who together lead the Henry Royce Institute research theme identified as 'Atoms to Devices'. Together they have already established the required substantial infrastructure and state-of-the-art facilities through investment from Royce, the EPSRC and each University partner. The programme grant will provide the resource to assemble the wider team required to deliver the NAME vision, including UK academics, research fellows, and postdoctoral researchers, supported by PhD students funded by the Universities. The programme grant also has significant support from wider academia and industry based both within the UK and internationally.

How can we trust autonomous computer-based systems? Autonomous means "independent and having the power to make your own decisions". This proposal tackles the issue of trusting autonomous systems (AS) by building: experience of regulatory structure and practice, notions of cause, responsibility and liability, and tools to create evidence of trustworthiness into modern development practice. Modern development practice includes continuous integration and continuous delivery. These practices allow continuous gathering of operational experience, its amplification through the use of simulators, and the folding of that experience into development decisions. This, combined with notions of anticipatory regulation and incremental trust building form the basis for new practice in the development of autonomous systems where regulation, systems, and evidence of dependable behaviour co-evolve incrementally to support our trust in systems. This proposal is in consortium with a multi-disciplinary team from Edinburgh, Heriot-Watt, Glasgow, KCL, Nottingham and Sussex, bringing together computer science and AI specialists, legal scholars, AI ethicists, as well as experts in science and technology studies and design ethnography. Together, we present a novel software engineering and governance methodology that includes: 1) New frameworks that help bridge gaps between legal and ethical principles (including emerging questions around privacy, fairness, accountability and transparency) and an autonomous systems design process that entails rapid iterations driven by emerging technologies (including, e.g. machine learning in-the-loop decision making systems) 2) New tools for an ecosystem of regulators, developers and trusted third parties to address not only functionality or correctness (the focus of many other Nodes) but also questions of how systems fail, and how one can manage evidence associated with this to facilitate better governance. 3) Evidence base from full-cycle case studies of taking AS through regulatory processes, as experienced by our partners, to facilitate policy discussion regarding reflexive regulation practices.

Metamaterials are artificial materials with characteristics beyond those found in nature that unlock routes to material and device functionalities not available using conventional approaches. Their electromagnetic, acoustic or mechanical behaviour is not simply dictated by averaging out the properties of their constituent elements, but emerge from the precise control of geometry, arrangement, alignment, material composition, shape, size and density of their constituent elements. In terms of applications, metamaterials have phenomenal potential, in important areas, from energy to ICT, defence & security, aerospace, and healthcare. Numerous market research studies predict very significant growth over the next decade, for example, by 2030 the metamaterial device market is expected to reach a value of over $10bn (Lux Research 2019). The 'Metamaterials' topic is inherently interdisciplinary, spanning advanced materials (plasmonics, active materials, RF, high index contrast, 2D materials, phase change materials, transparent conductive oxides, soft materials), theoretical physics, quantum physics, chemistry, biology, engineering (mechanical and electrical), acoustics, computer sciences (e.g. artificial intelligence, high performance computing), and robotics. Historically, the UK has been a global leader in the field, with its roots in the work of radar engineers in the 2nd World War, and being reinvigorated by the research of some of our most eminent academics, including Professor Sir John Pendry. However today, it risks falling behind the curve. As a specific example, the Chinese government has funded the development of the world's first large-scale metamaterial fabrication facility, which has capacity to produce 100,000 m2 of metamaterial plates annually, with projects relating to aerospace, communication, satellite and military applications. The breadth of metamaterial research challenges is huge, from theory, fabrication, experiment, and requiring expertise in large-scale manufacturing and field testing for successful exploitation. We believe that the isolation of research groups and lack of platforms to exchange and develop ideas currently inhibits the UK's access to the interdisciplinary potential existing within our universities, industries, and governmental agencies. It is of the utmost importance to develop interactions and mobility between these communities, to enable knowledge transfer, innovation, and a greater understanding of the barriers and opportunities. The intervention that this Network will provide will ensure that the UK does not lag our international competitors. Via the Network's Special Interest Groups, Forums, National Symposia and other community-strengthening strategies, the enhanced collaboration will help resolve key interdisciplinary challenges and foster the required talent pipeline across academia and industry. As a result we will see an increase in research power for the metamaterials theme, and therefore reaping the impact opportunities of this area for UK economy and society. The Network's extensive promotion of the benefits of metamaterials technology (e.g., case studies, white papers etc), facilitation of access to metamaterial experts and facilities (through the online database) and closer interactions with end-users at appropriate events (e.g. industry-academia workshops) will help grow external investment in metamaterials research. Ultimately the Network will provide the stimulation of a discovery-innovation-enterprise cycle to meet desired outcomes for prosperity and consequentially, society, defence, and security.