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Computational fluid dynamics (CFD) is fundamental to modern engineering design, from aircraft and cars to household appliances. It allows the behaviour of fluids to be computationally simulated and new designs to be evaluated. Finding the best design is nonetheless very challenging because of the vast number of designs that might be explored. Computational optimisation is a crucial technique for modern science, commerce and industry. It allows the parameters of a computational model to be automatically adjusted to maximise some benefit and can reveal truly innovative solutions. For example, the shape of an aircraft might be optimised to maximise the computed lift/drag ratio. A very successful suite of methods to tackle optimisation problems are known as evolutionary algorithms, so-called because they are inspired by the way evolutionary mechanisms in nature optimise the fitness of organisms. These algorithms work by iteratively proposing new solutions (shapes of the aircraft) for evaluation based upon recombinations and/or variations of previously evaluated solutions and, by retaining good solutions and discarding poorly performing solutions, a population of optimised solutions is evolved. An obstacle to the use of evolutionary algorithms on very complex problems with many parameters arises if each evaluation of a new solution takes a long time, possibly hours or days as is often the case with complex CFD simulations. The great number of solutions (typically several thousands) that must be evaluated in the course of an evolutionary optimisation renders the whole optimisation infeasible. This research aims to accelerate the optimisation process by substituting computationally simpler, dynamically generated "surrogate" models in place of full CFD evaluation. The challenge is to automatically learn appropriate surrogates from a relatively few well-chosen full evaluations. Our work aims to bridge the gap between the surrogate models that work well when there are only a few design parameters to be optimised, but which fail for large industry-sized problems. Our approach has several inter-related aspects. An attractive, but challenging, avenue is to speed up the computational model. The key here is that many of these models are iterative, repeating the same process over and over again until an accurate result is obtained. We will investigate exploiting partial information in the early iterations to predict the accurate result and also the use of rough early results in place of the accurate one for the evolutionary search. The other main thrust of this research is to use advanced machine learning methods to learn from the full evaluations how the design parameters relate to the objectives being evaluated. Here we will tackle the computational difficulties associated with many design parameters by investigating new machine learning methods to discover which of the many parameters are the relevant at any stage of the optimisation. Related to this is the development of "active learning" methods in which the surrogate model itself chooses which are the most informative solutions for full evaluation. A synergistic approach to integrate the use of partial information, advanced machine learning and active learning will be created to tackle large-scale optimisations. An important component of the work is our close collaboration with partners engaged in real-world CFD. We will work with the UK Aerospace Technology Institute and QinetiQ on complex aerodynamic optimisation, with Hydro International on cyclone separation and with Ricardo on diesel particle tracking. This diverse range of collaborations will ensure research is driven by realistic industrial problems and builds on existing industrial experience. The successful outcome of this work will be new surrogate-assisted evolutionary algorithms which are proven to speed up the optimisation of full-scale industrial CFD problems.

Moore's Law and Dennard scaling have led to dramatic performance increases in microprocessors, the basis of modern supercomputers, which consist of clusters of nodes that include microprocessors and memory. This design is deeply embedded in parallel programming languages, the runtime systems that orchestrate parallel execution, and computational science applications. Some deviations from this simple, symmetric design have occurred over the years, but now we have pushed transistor scaling to the extent that simplicity is giving way to complex architectures. The absence of Dennard scaling, which has not held for about a decade, and the atomic dimensions of transistors have profound implications on the architecture of current and future supercomputers. Scalability limitations will arise from insufficient data access locality. Exascale systems will have up to 100x more cores and commensurately less memory space and bandwidth per core. However, in-situ data analysis, motivated by decreasing file system bandwidths will increase the memory footprints of scientific applications. Thus, we must improve per-core data access locality and reduce contention and interference for shared resources. Energy constraints will fundamentally limit the performance and reliability of future large-scale systems. These constraints lead many to predict a phenomenon of "dark silicon" in which half or more of the transistors on each chip must be powered down for safe operation. Low-power processor technologies based on sub-threshold or near-threshold voltage operation are a viable alternative. However, these techniques dramatically decrease the mean time to failure at scale and, thus, require new paradigms to sustain throughput and correctness. Non-deterministic performance variation will arise from design process variation that leads to asymmetric performance and power consumption in architecturally symmetric hardware components. The manifestations of the asymmetries are non-deterministic and can vary with small changes to system components or software. This performance variation produces non-deterministic, non-algorithmic load imbalance. Reliability limitations will stem from the massive number of system components, which proportionally reduces the mean-time-to-failure, but also from the component wear and from low-voltage operation, which introduces timing errors. Infrastructure-level power capping may also compromise application reliability or create severe load imbalances. The impact of these changes on technology will travel as a shockwave throughout the software stack. For decades, we have designed computational science applications based on very strict assumptions that performance is uniform and processors are reliable. In the future, hardware will behave unpredictably, at times erratically. Software must compensate for this behavior. Our research anticipates this future hardware landscape. Our ecosystem will combine binary adaptation, code refactoring, and approximate computation to prepare CSE applications. We will provide them with scale-freedom - the ability to run well at scale under dynamic execution conditions - with at most limited, platform-agnostic code refactoring. Our software will provide automatic load balancing and concurrency throttling to tame non-deterministic performance variations. Finally, our new form of user-controlled approximate computation will enable execution of CSE applications on hardware with low supply voltages, or any form of faulty hardware, by selectively dropping or tolerating erroneous computation that arises from unreliable execution, thus saving energy. Cumulatively, these tools will enable non-intrusive reengineering of major computational science libraries and applications (2DRMP, Code_Saturne, DL_POLY, LB3D) and prepare them for the next generation of UK supercomputers. The project partners with NAG a leading UK HPC software and service provider.

This proposal focuses on the impact performance of state-of-the-art composites in the form of fibre-reinforced plastics (FRPs) with through-thickness reinforcement introduced via Z-pinning. The application of composites in primary lightweight structures has been steadily growing during the last 20 years, increasing the requirement for new and advanced composites technologies. Recent examples include large civil aircraft, such as the Boeing 787 and the Airbus A350, high performance cars, such as the McLaren 650S, and civil infrastructure, such as the Mount Pleasant bridge on the M6 motorway. FRPs are made of thin layers (plies) of plastic material with embedded high stiffness and strength fibres. The plies are bonded together in a stack by applying heat and pressure in a process known as "curing". The resulting assembly is the FRP laminate. The main reasons for the increasing usage of FRPs in several engineering fields are the superior in-plane specific stiffness and strength with respect to traditional alloys and the long-term environmental durability due to the absence of corrosion. Another key advantage of FRPs is that they can be tailored to specific design loads via optimising the orientation of the reinforcing fibres across the laminate stack. FRPs are, however, prone to delamination, i.e. the progressive dis-bond of the plies through the thickness of the laminate. This is due to the fact that standard FRP laminates have no reinforcement in the through-thickness direction, so the out-of-plane mechanical properties are significantly lower than the in-plane ones. According to the US Air Force, delamination can be held responsible for 60% of structural failures in FRP components in service. Impacts are the main cause of delamination in FRP laminates with energies usually in the order of 20J, sufficient to produce multiple delaminations in FRP plates. A representative scenario for such energy level is that of a 2cm diameter stone impacting a laminate at a speed of 110 km/h. In aerospace impact scenarios can be much more severe. For example, the certification of turbofan engines requires the fan blades to be able to withstand an impact with a bird whose mass is in the order of a few kilograms at speed in excess of 300 km/h, with impact energies of thousands of Joules. Introducing through-thickness reinforcement in FRPs is a viable strategy for improving the through-thickness mechanical properties and inhibiting delamination. Z-pinning is a through-thickness reinforcement technique whereby short FRP rods are inserted in the laminate before curing. Z-pinning has been proven to be particularly effective in inhibiting delamination under quasi-static, fatigue loading and low velocity/low energy impact loading. Nonetheless, little is known regarding the performance of Z-pinned laminates withstanding high energy/high speed impacts, whose effects are governed by complex transient phenomena taking place within the bulk FRP laminates and multiple ply interfaces. Overall, these phenomena are commonly denoted as "high strain rate" effects. There is some evidence that Z-pinning is beneficial also for high-speed impacts, but this is not conclusive. The current lack of knowledge may be circumvented with overdesign and expensive large-scale structural testing, but this is not a sustainable solution in a medium to long-term scenario. This project aims to fill the knowledge gap outlined above, by combining novel experimental characterisation at high deformation rates with new modelling techniques that can be used for the design and certification of impact damage tolerant composite structures. The development of suitable modelling techniques is particularly important for industrial exploitation, since it will reduce the amount of testing required for certification of composite structures, with a significant reduction of costs and shorter lead times to mark

This project aims to develop, and to provide a range of mechanisms to support interdisciplinary collaborations that use and develop new mathematics for understanding climate variability and impact on resilience. Focusing on three scientific themes the project will nurture connections between mathematicians, statisticians, environmental scientists, policy makers and end users working in impact areas to help to identify high-risk and high-return research that will develop collaborations in the areas of the themes. We will do this by a range of tools, including a series of managed events (workshops, sandpits, study groups and e-seminars) that will focus on specific problems to end users as well as promoting novel collaborations in the areas of scientific focus. We will provide a mechanism to solicit, evaluate and fund proposals for feasibility studies that work across this area. This will be informed by an expert panel of researchers as well as an advisory panel taken from national and international groups and end-users.

Liquid crystal (LC) technology has become a dominant force in the displays market. To date, a lot of research and development has been focussed in optimising the LC material properties for displays; however, there are an increasing number of other non-display applications that could benefit from LC technology if it were used to modulate the phase of the light rather than its intensity. Specifically, a dynamic optical element based upon LC technology that can modulate the phase rapidly and with analogue control will be of significant importance in the development of next-generation adaptive optics (AO) for a range of technologies whereby aberration correction and/or dynamic parallelisation are required. Notable advances have already been made using AO in areas such as microscopy, optical tweezing, holographic projection, and laser machining. For example, AO is expanding the capabilities of biomedical microscopy by enabling imaging of biological process in thick and even live tissue specimens, through compensation of aberrations. Such research is now being extended to super-resolution microscopy, which reveals cellular structures an order of magnitude lower than the diffraction limit. AO devices are also used for opto-genetics and photo-activation, where it is necessary to reconfigure 3D light fields at high speeds so that specific cells can be selectively activated. New and improved LC devices would therefore enable a range of research that underpins the life and medical sciences. Equally, adaptive control of ultra-fast lasers for optical nano-fabrication would benefit considerably from new LC technology, allowing pulse shaping and parallelisation at high speeds to be realised, supporting future advances in high-value manufacturing. The potential of using dynamic optical elements, such as LC devices, in all of these applications is well substantiated, but current performance is constrained by the switching speeds and/or phase modulation capabilities of the display-type devices. Increasing device speed will satisfy an as-yet unmet demand from these applications and could enable a greater impact in all of these application areas. Moreover, the development of a new fast-switching SLM with analogue phase control may potentially pave the way to new application spaces that are yet to be realised.

The wastewater treatment process (WWTP) plays a critical role in providing clean water. However, emerging and predominately unregulated, bioactive chemicals such as steroids and pharmaceutical drugs are being increasingly detected in surface waters that receive wastewater effluent. Although present at low concentrations, their inherent bioactive nature has been linked to abnormalities in aquatic organisms and there are also water reuse and human health implications. As part of the urban water cycle, the WWTP is the gatekeeper to the surface waters e.g. rivers. Pharmaceuticals enter wastewater treatment from inappropriate disposal of unused drugs to the sink/toilet or via landfill. Prescribed or illicit drug use also has the inevitable consequence of being metabolised in the human body (to parent, Phase I / II metabolites) and excreted in urine, which subsequently enters the WWTP. Coupled with naturally produced and excreted bioactive steroids, the challenge for wastewater treatment is that it was never designed to remove these bioactive chemicals and is inefficient. Evaluating the prevalence and fate of a steroid or pharmaceutical in the WWTP is challenging as human enzymatic metabolism causes the bioactive chemical to exist in multiple forms - parent, Phase I and Phase II metabolites. Phase II metabolites predominate urine excretion and are the starting products entering the wastewater environment. They therefore act as the precursors to the biotransformations that take place during treatment and produce the Phase I and/or parent forms of the bioactive chemical. Before treatment technologies can be developed and evaluated for pharmaceutical and steroid removal in the WWTP, our understanding needs to improve on how the different bioactive chemical forms behave, and their relationships to each other. This means identifying the biotransformations between metabolites and parent forms. To achieve this requires a move from targeted analysis - we analyse for what we expect to see - to develop methods that are non-targeted and search for Phase II metabolites and their associated Phase I / parent forms. Drawing on inspiration from metabolomics approaches used in the biosciences, the aim of this proposal is to develop a novel non-target method to identify bioactive chemical Phase II metabolites and their biotransformation products in wastewater. Knowledge of Phase II metabolite occurrence and fate in the wastewater environment is important in assessing the impact of user behaviour, process and environmental factors or bioactive chemical parent removal. This will inform on WWTP efficiency, provide data for optimising models that predict pharmaceuticals and steroids, and evaluate environmental risk.

While the theory of minimal and constant mean curvature (CMC) surfaces is a purely mathematical one, such surfaces overtly present themselves in nature and are studied in many material sciences. This makes the theory more exciting. If we take a closed wire and dip it in and out of soapy water, the soap film that forms across the loop is in fact a minimal surface and the physical properties of soap films were already studied by Plateau in the 1850s. The air pressure on the sides of soap films is equal and constant. However, if we change the pressure on one side, for instance by blowing air on it, the new surface that we obtain is what we call a soap bubble. A soap bubble is a CMC surface. More precisely, minimal and CMC surfaces are, respectively, mathematical idealisation of soap films and soap bubbles. The mean curvature of a soap film and bubble is a quantity that is proportional to the pressure difference on the sides of the film. The value of the pressure difference, and therefore of the mean curvature, is zero for a soap film/minimal surface and it is non-zero constant for a soap bubble/CMC surface. Since the pressure inside a small bubble is greater than the pressure inside a big one, the constant mean curvature of a small bubble is greater than the constant mean curvature of a big one. Minimal and CMC surfaces also enjoy crucial minimising properties relative to area. Among all surfaces spanning a given boundary, a soap film/minimal surface is one with locally least area; soap bubbles/CMC surfaces locally minimise area under a volume constraint. This project aims to investigate several key geometric properties of minimal and CMC surfaces. Roughly speaking, I intend to prove several results about CMC surfaces embedded in a flat three-dimensional manifold, including area estimates when the surfaces are compact with bounded genus and the ambient manifold is compact. I also plan to study the limits of a sequence of minimal or CMC surfaces embedded in a general three-dimensional manifold.

Structural application of fibre-reinforced polymer (FRP) composite materials is one of the key factors leading to technological innovations in aviation, chemical, offshore oil and gas, rail and marine sectors. Motivated by such successes, FRP shapes and systems are increasingly used in the construction sector, such as for bridges and small residential buildings. An obstacle to a wider use of FRP materials in structural engineering is the current lack of comprehensive design rules and design standards. While the preparation of design guidance for static actions is at an advanced stage in the USA and EU, the design against dynamic loading is underdeveloped, resulting in cautious and conservative structural design solutions. Knowledge on the dynamic properties (natural frequencies, modal damping ratios, modal masses and mode shapes of relevant vibration modes) of FRP structures and their performance under dynamic actions (such as pedestrian excitation, vehicle loading, wind and train buffeting) needs to be advanced if to achieve the full economic, architectural and engineering merits in having FRP components/structures in civil engineering works. This project will provide a step change to design practice by developing new procedures and recommendations for design against dynamic actions. This will be achieved by: 1) Developing an instrumented bridge structure at the University of Warwick campus that will provide unique insight into both static and dynamic performance over the course of the project, and beyond; 2) Providing novel experimental data on dynamic properties and in-service vibration response of ten full-scale FRP structures; and 3) Critical evaluation of the numerical modelling and current vibration serviceability design approaches. The data collected will be delivered in a systematic form and made available, via an open-access on-line database for rapid and easy dissemination, to academic and industrial beneficiaries, as well as to agencies supporting the preparation of institutional, national and international consensus design guidance. Outcomes from this project will provide the crucial missing information required for the reliable design of light-weight FRP structures, and pave the way towards this structural material becoming a 'material of choice' for future large-scale bridges and other dynamically loaded structures. This medium to longer-term impact is aligned with national plans for the UK having a sustainable and resilient built environment.

The development of technologies that exploit quantum physics to improve measurement, information processing, and communication is an area of rapid growth. Quantum devices such as memories and processors operate at different optical frequencies, typically outside the telecom range where losses in fibre are minimal. The goal of this studentship is to develop frequency-conversion techniques using nonlinear optics in optical fibre that will allow individual photons to be shifted between different wavelength bands. This will enable communication between the nodes of quantum devices operating at different optical frequencies; it will also allow low-loss, (and hence long-distance) exchange over fibre as well as photon conversion to frequencies where optimal detectors operate. To be of value, use of quantum frequency translation must allow any small or large photon frequency shift within the visible and near infrared. The frequency conversion must also not alter properties of the photon other than its wavelength, including any entanglement with other systems. Furthermore, it should be highly efficient while not introducing additional 'noise' photons. To meet the above requirements, frequency conversion of single photons will be investigated in photonic crystal fibre (PCF), optical fibres with a matrix of air holes running along their length, as well as subclasses of PCF such as bandgap fibre and hybrids thereof. In order to achieve this, new fibres will need to be designed and then fabricated in the university's state-of-the-art fibre fabrication facility. The project will involve theoretical and numerical analysis, fabrication, laboratory work using cutting-edge equipment, and participation in project meetings and reporting. Hence the full range of skills required for high-impact scientific research will be developed as well as communication and transferrable skills. There will be opportunities to present work at leading international conferences and to publish in high-quality peer-reviewed journals. The project will be carried out in close collaboration with other members of the Networked Quantum Information Technologies hub being led by the University of Oxford, providing the opportunity to work on this individual experiment and simultaneously contribute to a larger joint research effort.

We propose to prepare and study a new class of synthetic ion channels based on dynamic metal-organic complexes that possess a pore-like central channel that will allow for substrate transport across a lipid bilayer. These complexes are obtained through the condensation of simple organic building blocks around octahedral metal ion templates. The modular nature of these complexes and the dynamic nature of their imine bonds will allow us to tune the assemblies to confer different physical properties upon them, while retaining their overall structures. Through tuning we will identify the key characteristics of complexes that can be inserted into lipid bilayers. This project builds upon preliminary investigations that have shown that heptyl-chain-bearing derivatives allowed chloride ions to pass across a membrane, providing a point of departure for our investigations. In other key precedent work we established that it is possible to induce reconstitution of the complexes into entirely different structures in the presence of different templating anions. We will investigate ways to exploit this phenomenon as an approach to controlling flux across a membrane by reversibly triggering reconstitution to form complexes that do not possess central channels, thus inhibiting ion transport. Development of these tuneable, gating ion channels will pave the way to new industrial processes that are driven by the effective separation of high value compounds from impure mixtures, and new chemical transformations involving the selective gating of intermediate species between vesicular reaction chambers. In future, our technologies may also facilitate new treatments for those who suffer from forms of channelopathy.