Although photolithography or scanning beam lithography are techniques widely used for the fabrication of devices with nanoscale features, a drive still exists to explore alternative and complementary nanoscale manufacturing processes, particularly for supporting the development of proof-of-concept devices that integrate 3D nano-structures. This is due to the fact that conventional nanofabrication technologies rely on capital-intensive equipment in addition to being restricted in the fabrication of true 3D features and in the range of processable materials. Besides, there are also increased concerns over their environmental friendliness as they are energy and resource intensive and generate significant waste. One candidate nano-manufacturing process that may help address these limitations, particularly during the development stages of nanotechnology-enabled devices, relies on mechanical machining with the tip of an Atomic Force Microscope (AFM) probe. In particular, material removal operations on the nanoscale can be achieved as a result of using the AFM probe tip as a "nano-cutting tool". However, it is currently not possible for AFM practitioners to determine the required input process parameters, in terms of load to be applied by the tip and the cutting direction to be followed, for achieving specific groove dimensions without completing experimental trial-and-error campaigns first. For this reason, this project aims to implement a novel modelling approach of AFM-based nano-machining such that, given a set of input parameters, it will be possible for a user to predict the expected geometry of a machined groove, and vice versa. To achieve this overall aim, the project will develop and validate a new coupled SPH-FE (i.e. Smooth Particle Hydrodynamics - Finite Elements) model of the AFM tip-based nano-machining process. In addition, to ensure that such process modelling is based on reliable data, the project proposes to adopt novel experimental characterisation techniques to extract the mechanical properties of a workpiece material, which are specifically relevant for nanoscale cutting. Finally, the project also aims to demonstrate the increased potential of this nano-manufacturing process, when applied with the proposed modelling approach, for the development and implementation of nanotechnology applications through two lab-based demonstrators.

This proposal is to develop a multi-sensor system for in-process metrology of parts made by the additive manufacturing (AM) process - laser powder bed fusion (L-PBF). AM, also known as '3D printing', is changing the way that engineers solve the problems of today. Unlike subtractive manufacturing methods, where materials must be cut away to produce a finished part, AM processes build parts up layer-by-layer. This provides almost limitless design freedom, allowing the design of more organic, more lightweight, more bespoke solutions. However, the technology is not without its challenges. The current state of AM technology cannot produce parts with the consistency or geometric tolerances that are required for many applications. The production of metal parts by AM is particularly challenging. The most prominent technology for producing AM metal parts is L-PBF, also called selective laser melting. To produce parts economically the process must be fast with high laser power making L-PBF a highly energetic process that is sensitive to a changes in process variables. Defects can occur at any stage of the process: incomplete melting, aggregation of unmelted powder, pitting, balling, spattering, as well as defects caused by thermal or residual stresses: cracking, spalling and layer separation. Effective control of the L-PBF process is an extremely challenging task, and the subject of significant research both in the UK and global research communities. One aspect of that challenge that has become clear in the last few years is the need for step change improvements in in-process condition monitoring and metrology. The key parameters for in-process control are the melt pool temperature, the powder bed temperature and the presence of physical defects in the powder laying and laser fusion stages. The laser fusion event that consolidates the powder takes place over a few hundreds of nanoseconds, making it very difficult to observe and control in real-time. Fortunately, a great deal of information about the melting conditions can be observed in the consolidated surface that fusion leaves behind; a so-called process signature or fingerprint. By capturing information on the form and the texture of the part surface it is possible to determine whether the laser and scan parameters have been chosen correctly, and critically it is also possible to monitor whether any major defects have occurred. AM processes, including L-PBF, are not yet mature enough that quality can be assured. Each machine will have slightly different performance characteristics, and the part quality can change from day to day, with small changes in the environment, the powder quality or the laser condition. For AM to be more widely adopted, industries need assurance, and that means highly robust in-process measurements. Current in-process measurement methods are inadequate; 2D imaging methods cannot identify all of the common defects or measure surface texture in the process fingerprint. The few pre commercial 3D measurement systems that have been demonstrated, have been unable to accommodate the extreme range in texture observed for L-PBF. In simple terms the surfaces are either too reflective for some methods, or too diffuse for others, often producing misleading imaging artefacts or missing significant defects. This lack of robust in-process metrology, stymies development and slows the wider adoption of L-PBF. What is required is a robust measurement of form, texture and thermal distribution of the metal powder bed. This proposal will achieve that aim by the intelligent combination of measurement data captured by multiple sensor systems. Each sensor individually cannot capture the whole surface, but when combined, will offer the most complete in process measurement achievable to date. This multi-sensor system will have profound benefits for process control of L PBF processes as well as providing a wealth of in process data to feed into future research.

The Made in China 2025 report, highlights ocean renewable energy technologies as one of the 10 areas of opportunity for UK and Chinese companies. The "Outline of the National Marine Economic Development Plan" specifically targets the development of novel ocean farming methods, more productive but also more socially and environmentally compatible. In the EU, the "Blue Growth" program aims at sustainable growth in the marine and maritime sectors, already representing 5.4 million jobs and generating a gross added value of 500 billion euros a year. Offshore structures are very costly. The main idea of a Multi-Purpose Platform (MPP), integrating (for example) renewable energy devices and aquaculture facilities, is to find the synergies to share manufacturing, installation, operation and maintenance, and decommissioning costs. This has the potential to, save money, reduce the overall impact, and maximize the socio-economic benefits. MPP development poses cross-disciplinary challenges, since they simultaneously aim to achieve several potentially conflicting objectives: to be techno-economically feasible, environmentally considered, socially beneficial, and compatible with maritime legislations. In the EU, previous research focused on farms of multi-megawatt MPP (ocean renewable devices + aquaculture systems), with very few/no attempts to investigate lower rated power systems suitable for island/coastal communities. In China, previous projects aimed at island communities focused on renewable energy, but they did not integrate any aquaculture elements. Therefore, for island communities, novel fundamental questions arise, especially in terms of techno-economic feasibility and assessment and maximization of socio-environmental benefits at a completely different scale, but still requiring a whole-system, cross-disciplinary approach. The proposed solution is to investigate which are the specific challenges arising from the integration of these different offshore technologies, and with a multi-disciplinary approach to tackle them, making sure that all the dimensions (technological, economic, social, environmental, legal) are taken into account. The renewable energy technologies (Which wind turbine? Which wave device? What kind of solar panel?) and aquaculture systems most suitable for the needs of an island community will be identified, and the "cross-disciplinary" questions will be defined, e.g. "What is the impact of the noise generated by the renewable energy devices on the (closely co-located) aquaculture species growth rate?". Answering these questions, the novel contribution will consist in developing approaches to assess the feasibility of an MPP system, focusing on: global MPP dynamic response to metocean conditions, overall integrated control and power management strategies, environmental impact, socio-economic risks and benefits. The potential of these methodologies will be then show-cased through two case-studies, one focusing on an island community in China, and one in the UK. This consortium brings together internationally recognised experts from three Chinese and three British universities and institutes, for a total of 20 investigators, in the fields of solar and offshore wind and wave energy, control systems for renewable energy devices, environmental and socio-economic impact of renewables and aquaculture systems, aquaculture and integrated multi-trophic aquaculture development, and ecosystem modelling. These investigators are also leading members of the research community, directly involved in: Renewable Energy Key Lab of Chinese Academy of Sciences, IEC and Chinese National Standardization Committee for Marine Energy Devices, Supergen Wind Hub, EU Energy Research Alliance JP Wind, ITTC Ocean Engineering Committee, the Royal Institution of Naval Architects Maritime Innovation Committee, ICES WG-Marine Mammal Ecology, International Platform for Biodiversity and Ecosystem, Ecopath Consortium Advisory Board.

In real world water distribution systems (WDS) uncertainty can arise in a number of different ways. Variations in the performance of parts (for example pipe roughness) can affect the performance of the system. Uncertainty in the requirements the system must satisfy (such as demand at a node) will affect the ability of the system to meet those requirements. An algorithm which can reduce the number of fitness evaluations required to find performance probabilities for systems operating under uncertainty has the potential to significantly reduce computation times required for optimisation. Furthermore when system uncertainties include mechanical failures such as pipe bursts, blockages and leaks, costs can be associated with underperformance allowing such an algorithm to offer risk-based optimisations of systems by assigning an expected consequence of failure to each design. Such optimisations will find a family of solutions offering a trade-off between the cost of the system and the expected future costs or consequences due to failures and other uncertainties.The need for an optimisation technique which is not only capable of optimising systems under uncertainty, but is also scalable to large WDS is at the heart of the proposed research.This research project brings mathematical techniques for statistical sampling and evolutionary optimisation together with an engineering knowledge of the design of water distribution systems under uncertainty.

This project addresses the need for intercultural learning in Chinese higher education (HE) in view of an enhanced intercultural awareness in interacting with people from diverse backgrounds. Despite the increased attention for interculturality, a recent nation-wide survey revealed that teaching staff still largely treats culture as a static body of knowledge (Gu, 2016). By building on the IEREST-project (527373-LLP-1-2012-1-IT-ERASMUS-ESMO), RICH-Ed aims at supporting the Chinese partner HEIs in creating a learning environment that empowers students and staff for global engagement. To this end, the partnership will define a pedagogical approach for intercultural learning in Chinese HE; develop, test and adapt instructional materials; and organize trainings for teaching and support staff.The project will produce the following results with respect to intercultural learning in Chinese HE:- a description of the current situation and stakeholder analysis;- a tested pedagogical approach & methodology;- tested and adapted learning materials and teacher support tools for intercultural learning in English courses, and for administrative and management staff;- a minimum of 15 trained trainers, 50 teachers, 50 support staff, and 1000 students at the Chinese partner HEIs; and an additional 100 teachers and 1000 students at other HEIs in the Yangtze River Delta and North-East China.The developed approach will be sustained in various courses at the partner HEIs and elsewhere in these target regions. Through a continuing engagement with stakeholders at various levels, the project aims to raise a deeper understanding in the country of a non-essentialist approach to interculturality. By making the developed materials freely available on an e-repository, new end-users will be able to benefit after project completion. The partnership will also investigate opportunities for sustainability in the form of for-a-fee products and services, and reaching additional target groups.