In highly engineered materials, microscale defects can determine failure modes at the compo-nent/system scale. While X-ray CT is unique in being able to image, find, and follow defects non-destructively at the microscale, currently it can only do so for mm sized samples. This currently presents a significant limitation for manufacturing design and safe life prediction where the nature and location of the defects are a direct consequence of the manufacturing process. For example, in additive manufacturing, the defects made when manufacturing a test-piece may be quite different from those in a three dimensionally complex additively manufactured engineering component. Similarly, for composite materials, small-scale samples are commonly not large enough to properly represent all the hierarchical scales that control structural behaviour. This collaboration between the European Research Radiation Facility (ESRF) and the National Research Facility for laboratory CT (NRF) will lead to a million-fold increase in the volume of material that can be X-ray imaged at micrometre resolution through the development and exploitation of a new beamline (BM18). Further, this unparalleled resolution for X-rays at energies up to 400keV enables high Z materials to be probed as well as complex environmental stages. This represents a paradigm shift allowing us to move from defects in sub-scale test-pieces, to those in manufactured components and devices. This will be complemented by a better understanding of how such defects are introduced during manufacture and assembly. It will also allow us to scout and zoom manufactured structures to identify the broader defect distribution and then to follow the evolution of specific defects in a time-lapse manner as a function of mechanical or environmental loads, to learn how they lead to rapid failure in service. This will help to steer the design of smarter manufacturing processes tailored to the individual part geometry/architecture and help to establish a digital twin of additive and composite manufacturing processes. Secondly, we will exploit high frame rate imaging on ID19 exploiting the increased flux available due to the new ESRF-extremely bright source upgrade to study the mechanisms by which defects are introduced during additive manufacture and how defects can lead to very rapid failures, such as thermal runaway in batteries In this project, we will specifically focus on additive manufacturing, composite materials manufacturing and battery manufacturing and the in situ and operando performance and degradation of such manufactured articles, with the capabilities being disseminated and made more widely available to UK academics and industry through the NRF. The collaboration will also lead to the development of new data handling and analysis processes able to handle the very significant uplift in data that will be obtained and will lead to multiple site collaboration on experiments in real-time. This will enable us to work together as a multisite team on projects thereby involving less travelling and off-setting some of the constraints on demanding experiments posed by COVID-19.

In 2008, the European Space Agency (ESA) will launch the first-ever satellite to measure ocean salinity from space: the Soil Moisture and Ocean Salinity (SMOS) mission. SMOS aims to deliver global maps of the hitherto poorly known sea surface salinity (SSS), especially its temporal and large scale spatial variability. Such measurements are critical for ocean circulation and climate research and to improve operational forecasts. This project seeks to contribute to the assessment of the quality of the SMOS products in the period preceeding and immediatly following the launch of the SMOS satellite in 2008. This work is the key element of the UK involvement in the international effort of SMOS salinity data validation coordinated by ESA. Financial support for satellite validation activities is not available from ESA and is expected to originate from national agencies. However, it has so far not been possible to secure funding for this Cal/Val work, which is notoriously difficult to get funded in the UK.

Our goal is to create a world-class Centre for Doctoral Training (CDT) in fluid dynamics. The CDT will be a partnership between the Departments of Aeronautics, Bioengineering, Chemical Engineering, Civil Engineering, Earth Science and Engineering, Mathematics, and Mechanical Engineering. The CDT's uniqueness stems from training students in a broad, cross-disciplinary range of areas, supporting three key pillars where Imperial is leading internationally and in the UK: aerodynamics, micro-flows, and fluid-surface interactions, with emphasis on multi-scale physics and on connections among them, allowing the students to understand the commonalities underlying disparate phenomena and to exploit them in their research on emerging and novel technologies. The CDT's training will integrate theoretical, experimental and computational approaches as well as mathematical and modelling skills and will engage with a wide range of industrial partners who will contribute to the training, the research and the outreach. A central aspect of the training will focus on the different phenomena and techniques across scales and their inter-relations. Aerodynamics and fluid dynamics are CDT priority areas classified as "Maintain" in the Shaping Capabilities landscape. They are of key importance to the UK economy (see 'Impact Summary in the Je-S form') and there currently is a high demand for, but a real dearth of, doctoral-level researchers with sufficient fundamental understanding of the multi-scale nature of fluid flows, and with numerical, experimental, and professional skills that can immediately be used within various industrial settings. Our CDT will address these urgent training needs through a broad exposure to the multi-faceted nature of the aerodynamics and fluid mechanics disciplines; formal training in research methodology; close interaction with industry; training in transferable skills; a tight management structure (with an external advisory board, and quality-assurance procedures based on a monitoring framework and performance indicators); and public engagement activities. The proposed CDT aligns perfectly with Imperial's research strategy and vision and has its full support. The CDT will leverage the research excellence of the 60 participating academics across Imperial, demonstrated by a high proportion of internationally-leading researchers (among whom are 15 FREng, and, 4 FRS), 5*-rated (RAE) departments, and a fluid dynamics research income of 93M pounds sinde 2008 (with about 32% from industry) including a number of EPSRC-funded Programme Grants in fluid dynamics (less than 4 or 5 in the UK) and a number of ERC Advanced Investigator Grants in fluid dynamics (less than about 7 across Europe). The CDT will also leverage our existing world-class training infra-structure, featuring numerous pre-doctoral training programmes, high-performance computing and laboratory facilities, fluid dynamic-specific seminar series, and our outstanding track-record in training doctoral students and in graduate employability. The Faculty of Engineering has also committed to the development of bespoke dedicated space which is important for cohort-building activities, and the establishment of a fluids network to strengthen inter-departmental collaborations for the benefit of the CDT.

This proposal is based on two premises: that (1) increased autonomy is essential for future space exploration; (2) that existing programming methods are tedious to apply to autonomous components that have to handle an environment with continuous state variables. For well defined discrete-event environments the above rational agent approach is well developed; for a continuous environment, however, perception processes need to be linked with abstractions forming the basis of behaviour. As the environment changes, the abstracted models may also change. Hence, agents are needed that can use these abstractions to aid their decision making processes, use these in the predictive modelling of a continuous world, and connect these abstractions to both planning and goal achievement within rational agents.This project also intends to replace the current complex programming techniques, used for autonomous spacecraft control, with simpler declarative programming. High-level, declarative agent programming languages have been investigated at Liverpool and such theories and languages will be developed further for agents that require predictive modelling capabilities. The Southampton team is experienced both in the formal handling of analytical and empirical models for control and prediction, and in developing control software for real satellites. The merging of these themes is very promising. Although the results will be transferable to ground vehicles and robots, this project will particularly illustrate the new methods in space applications, both in simulation and laboratory hardware demonstrations.

This proposal is based on two premises: that (1) increased autonomy is essential for future space exploration; (2) that existing programming methods are tedious to apply to autonomous components that have to handle an environment with continuous state variables. For well defined discrete-event environments the above rational agent approach is well developed; for a continuous environment, however, perception processes need to be linked with abstractions forming the basis of behaviour. As the environment changes, the abstracted models may also change. Hence, agents are needed that can use these abstractions to aid their decision making processes, use these in the predictive modelling of a continuous world, and connect these abstractions to both planning and goal achievement within rational agents.This project also intends to replace the current complex programming techniques, used for autonomous spacecraftcontrol, with simpler declarative programming. High-level, declarative agent programming languages have been investigated at Liverpool and such theories and languages will be developed further for agents that require predictive modelling capabilities. The Southampton team is experienced both in the formal handling of analytical and empirical models for control and prediction, and in developing control software for real satellites. The merging of these themes is very promising. Although the results will be transferable to ground vehicles and robots, this project will particularly illustrate the new methods in space applications, both in simulation and laboratory hardware demonstrations.