Undesirable ice formation causes a lot of disruption - from impairing energy efficiency of household refrigerators to causing destructive accidents due to ice accumulation on infrastructure components and airplanes. The proposed research aims to address this ubiquitous problem using precise, but potentially scalable techniques to nanoengineer icephobic surfaces that can suppress ice formation, resist impact of cold drops and have minimal adhesion to ice. The proposal is motivated to provide a viable, passive and energy efficient alternative to the currently employed anti-icing techniques, which rely either on electro-thermal systems that affect the system efficiency and running costs, or make use of environmentally adverse chemicals. The surface nanoengineering to be employed will involve a precise control of both the surface texture at nanoscale and the surface hydrophobicity. The appropriate combination of these two aspects is expected to not only suppress ice formation in severely supercooled conditions (at sub-zero temperatures), but to resist impact of high speed supercooled droplets and minimize adhesion of ice on the surface - all these aspects are relevant to icing in practical applications and will be tested in the current work. The ambition of the proposal is to make nanotextured surfaces with nanohole arrays with better than 10 nm precision (i.e. resolution). Such precise and rounded morphologies are expected to suppress ice formation according to the thermodynamic heterogeneous ice nucleation framework previously introduced by the PI and supported by atomistic modelling results in the literature. In addition, self-assembly of hydrophobic molecules on the surfaces will allow a control over the surface energy, which, in combination with the texture control, will help produce superhydrophobic surfaces that can resist impalement by high speed, cold drops, and have low ice adhesion. The drop impalement resistance can help avoid icing on aircrafts and outdoor infrastructure elements in freezing rain conditions. As a proof-of-concept for a potentially scalable, precise nanotexturing, current project will exploit electrochemical anodisation of metals through polymeric nanohole films, prepared using block-copolymers (BCP), serving as templates. The surface texturing will be limited to top ~100 nm or lower thickness of the substrate and only mild anodisation conditions will be used. The templated anodisation is well suited to aluminium and titanium - substrates prevalent in aerospace, refrigeration and automotive industry; however, similar templated etching approaches can be developed for substrates in other applications (see the PATHWAYS TO IMPACT section). PI's prior work has shown that thermally conductive substrates are better for arresting frost formation from cold drops lying on the surface, thus the metallic substrates are a very good choice. In addition, the current work, for the first time, introduces a novel means to use simple anodic surface projections to improve the resolution of BCP nanohole templates themselves to ~10 nm precision - surfaces anodised through these precise templates are expected to be ideally suited for icephobicity. The resulting anodised substrates will be rendered hydrophobic by functionalizing with hydrophobic molecules. These precisely nanotextured hydrophobic surface are expected to suppress icing not only due to their rounded nanoscale morphology, but will also feature minimal solid-liquid contact area, thereby further suppressing the icing probability. The synthesized surfaces will be subjected to three set of tests: their ability to resist impalement by high speed, supercooled drops (target: 25 m/s); ability to delay ice formation in supercooled conditions at different humidity levels (target: 2 hours at -25 degrees Centigrade); and minimize their adhesion to frozen (ice) drops.

Industrial Control Systems (ICS) are used in sectors such as energy, manufacturing, transport, etc., and consequently play a fundamental role in the operation of many critical national infrastructures. In the last few decades ICS have evolved to incorporate new capabilities and connectivity, provided by integrating modern information and communications technology (ICT). However, a significant problem that has emerged due to this new set of technologies and high degree of interconnectivity is that ICS have become exposed to the myriad security problems that beset traditional ICT systems. Of great concern is the trend towards advanced multi-stage attacks against ICS, which continue to emerge. These can involve remote exploitation and lateral movements (pivots) across multiple systems. Recent attacks suggest that traditional crimeware type malware is being adapted explicitly for ICS; e.g. BlackEnergy and Havex exhibit malware modules that appear to have been developed to target ICS features and vulnerabilities. New threats against ICS supporting national infrastructures continue to emerge, and criminal and state entities are known to be targeting such systems. Consequently it is of great importance that we analyse and understand how advanced attacks against ICS behave and can be better detected. Common initial attack vectors include highly targeted spear-phishing against executives or engineers with valuable credentials, or opportunistic watering hole attacks against websites of specific interest to ICS personnel. Following the initial infiltration of an ICS network, the malware will likely try to execute actions including escalating its privileges on the host system, attempting to connect to a command and control server, downloading further payload packages, enumerating the network, pivoting and propagate further, exfiltrating data, and so on. A highly targeted, or "weaponised", payload is likely to enumerate ICS devices on the network or attempt to sniff and identify particular ICS related network traffic. Detecting advanced multi-stage attacks is difficult in IT systems, but approaches towards detection and response for ICS are comparatively less mature. Moreover, attacks discovered in the wild continue to evolve in sophistication. Stopping such attacks demands continual monitoring of the infrastructure and it is difficult to provide operators with targeted security status information in the face of advanced multi-stage ICS threats. This research aims to develop and test an approach that enhances real-time cyber-security monitoring capabilities for networked ICS environments. The objective is to present information to an operator that is more closely correlated to advanced multi-stage threats, rather than individual alerts, thereby improving the ability of the operator to gauge the current security status of the system. A threat measurement based approach will be used to investigate how the real-time cyber-security status of an ICS network environment can be measured in terms of an observable threat presence. It is hypothesised that such a status can be appraised by using suitable metrics, which may be derived by analysing, decomposing and modelling known advanced multistage threats. The analysis will target the development of threat models based on a combination of reported ICS attacks and an investigation of future potential advanced threats based on emerging trends in crimeware. A proposed solution will be implemented and tested in a test-bed environment based on a realistic factory automation environment.

Flutter is a well-studied phenomenon in aircraft wings, and typically affects wings at high flight speeds. Traditionally, aircraft designers sought to avoid flutter altogether; if it was encountered at all during advanced design stages or flight testing, it was dealt with using design fixes and/or inefficient operational modifications. The importance of active flutter mitigation has increased as the wings have become lighter and consequently more flexible over the years. A recent example of active flutter mitigation, which is also commercially deployed, is the outboard aileron modal suppression (OAMS) system incorporated on the Boeing 747-8I. While the details of OAMS are unknown, the phrase "modal suppression" suggests that its design falls within the ambit of traditional wing control methods which use a finite dimensional approximation of the dynamics to design a stabilizing controller. Although this approach allows a designer to tap into the vast family of control techniques for systems described by ordinary differential equations (ODEs), it has three major drawbacks: the ODE approximations tend to have large orders, the states of the ODE are seldom physically meaningful, and the control design process is susceptible to spillover instabilities which can result from an improper modal approximation. Control techniques for systems described by partial differential equation (PDEs), and which avoid finite dimensional approximations, have been evolving steadily in the recent past and promise to do away with both aforementioned drawbacks. The prior work done by the PI led to two new adaptive control techniques that fall within this evolving family of techniques. One of the techniques developed by the PI uses finite dimensional input-output (FDIO) maps that arise naturally for specific input-output pairs for a given PDE. Using FDIO maps, it is possible to convert the control design problem exactly to one for ODEs. Although akin to the risky approach of designing a static output feedback controller in finite dimensional systems, the PI discovered that the structure of the PDE provides a means for expanding the stable envelope of the system even under static output feedback. The PI's work also provided a partial explanation for the underlying stabilization mechanism. The aim of the present project is to develop and demonstrate a low-order adaptive control design technique for flexible wings which exploits the underlying PDE structure of the dynamics effectively, together with a clever reformulation of the control problem. The controller would be based on the PI's prior work [1, 6]. We will provide a major extension of the technique to more realistic, 2-dof wing models and adaptive laws to help the controller deal with modeling and parametric uncertainties. This is key to ensuring practical applicability of the control technique, and requires non-trivial theoretical development as well. We will validate the control technique using wind tunnel testing. The outcome of this project would be a low-order adaptive controller accompanied by analytical performance and stability guarantees. Additionally, the control design would minimize the set of sensors required for the feedback laws, by avoiding ODE approximations as far as possible during the design process. Beneficiaries of this research include the academic community and the aircraft industry, notably those that are involved in developing and deploying aeroelastic solutions. The broader impact of the proposed research has been described elsewhere in the proposal.

Composite industry exhibits a wide spectrum of efficient manufacturing methods spanning from cheap and robust liquid moulding processes to high quality expensive autoclaving. All the available methods have one feature in common: the continuously reinforced components, no matter how big or small, are produced in one curing/consolidation shot. Thus to achieve good dimensional tolerances and internal composite quality, a heavy tooling must be used: autoclaves, hot presses, double sided RTM moulds and other equipment that can provide high levels of applied pressure over large area. Considerable efforts are required to design and monitor these manufacturing processes. It is difficult to introduce any correction once the process has started or to detect and mitigate the defect occurrence when it runs. All possible scenarios of the material formation have to therefore be considered in advance and any possible quality issues must be addressed prior to the material consolidation. There is also a very limited instrument pallete available to adjust the process as the overall manufacturing parameters do not determine the formation of local geometrical features directly. This makes these processes expensive and risky particularly for new applications and reinforcement systems. This project introduces a new additive manufacturing concept which negates the need for heavy manufacturing equipment. The process is implemented through local deposition of liquid resin by means of a series of high precision injections through the thickness of a textile preform followed by local consolidation. In other words, the process is realised as 3D print of matrix into the reinforcement which maintains the liquid resin in the required position. The locality of the process guarantees its flexibility and sophisticated control over the geometry and properties. The current project looks at (a) optimisation of injection and consolidation process aimed at competitive rates of print, and (b) understanding effects of manufacturing parameters on the composite properties. In other words, this study offers new flexible high-quality composite manufacturing method tailored to the needs of property enhancement and the management of complex failure processes.

To design complex products, engineers need to consider and optimise many different attributes. In aerospace, optimisation mainly considers both structural (e.g. displacements, accelerations) and fluid (e.g. pressures acting on a body) attributes. One of the main factors which can impact performance is product shape, which affects a number of disciplines. When changing the shape of the design the options are to change the analysis model (i.e. a mesh) or the geometry model which represents the design. The preferred option is to optimise the geometry model as the result is integrated with the wider design enterprise (e.g. it can also be used for manufacturing considerations). This is particularly true if the geometry model is a feature based CAD model (e.g. Catia V5 or Siemens NX). In a feature based CAD system, the object shape is modified using the parameters which define the features that make up the model itself. One challenge is that the variables which define the shape of the design and control how it can change, may not actually be well suited for the disciplines driving the optimisation. This means that regardless of how much effort the optimiser puts in, it will not be possible to reach a truly optimum design. This three year project will ensure the parameterisation is suited to optimisation by investigating robust methodologies to automatically insert new features into the CAD model, for which the associated parameters will be new optimisation variables. This will rely on robust and efficient new methods for computing multi-disciplinary sensitivities. The project benefits from collaboration with a major UK industrial partner (Airbus) and developers of key analysis software (DLR). They will assist in researching a new capability with the overall aim of "delivering a step change in the configuration, time to market and performance of new designs." The following objectives have been set: 1. Implement strategies for improving CAD parameterisations for multi-disciplinary optimisation by automatically inserting features into the model based on sensitivity. 2. Investigate efficient and robust methodologies for computing aero-structural sensitivities. This will see a novel approach to the calculation of the sensitivities. 3. Develop strategies for coupling and coherently meshing solid and fluid models. This is a key piece of research required in any aero-structural analysis. 4. Combine aero-structural sensitivities with CAD parameterisation strategies, in an automated optimisation framework, for a range of test cases. This is where the benefits of the work will be demonstrated to industry. 5. Quantify the decrease in time to market and increase in performance due to this research. Application areas for this research include the design of products which require the optimisation of complex shapes. It will be particularly relevant in industries where feature based CAD systems underpin the design process, and where the physics of the problem may identify the need for shape features which may not be apparent when the CAD models are being setup. An example may be where the surface sensitivities suggest the need for a winglet, but where the parameterisation of a basic wing does not include the parameters to allow such a feature to form. Benefits include: 1. the ability to discover new, optimum, configurations. This is a route to innovative design solutions which will help to keep the UK as a world leader in the design and manufacture of complex products; 2. improved product performance due to the improved optimisation variables (CAD parameters) created based on the requirements of the physics of the problem. For air travel this will result in more environmentally friendly aircraft and lower travel prices; 3. reduced development times due to an automated and efficient optimisation processes, leading to new, better performing, products being available sooner;