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The KTN supports postgraduate research collaborations through CASE awards allocated by the Engineering and Physical Sciences Research Council (EPSRC). This page is a catalogue of the projects that have been supported in this way.
Full details of Industrial Mathematics CASE Awards and the application procedure are available here.
A significant issue with, and sometime criticism of, cloud computing relates to the security of data and computation which is “in the cloud”. Specifically, data owned by individuals and companies will be stored and operated on servers owned by a potentially untrusted (or at least partially trusted)
third party service provider; this provides significant privacy issues for individuals and possible extensive data security issues for corporations.
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The goal of this project is to understand the phenomenon of main landing gear shimmy. Oscillations always occur on the main gears at the point of touchdown, where this behaviour is dependant on the gear configuration, size of the aircraft, approach speed, attitude of the aircraft, and several other parameters. An
understanding of the most sensitive parameters that affect shimmy will enable companies such as Airbus to design more robust and safer landing gears.
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The objective of this project is to develop methods for reducing the degradation of numerical solutions for fluid flow problems during the refinement / derefinement process. The transition effects that arise when features (such as shocks) cross refinement interfaces will be investigated analytically and numerically using an existing adaptive mesh implementation. The issue of spurious oscillations at refinement interfaces need to be resolved for adaptive mesh refinement to be used more widely in industry.
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The objective of this project is to improve coordination between tower operation, airport operation and aircraft operators at London Heathrow. Integrated modelling of airport operations will combine interacting processes of arrival sequencing, runway allocation, land sequence compliance and stand allocation previously studied independently. This project aims to take advantage of the relationships between these processes to develop hybrid search methods for the integrated model that perform better than approaches based on independent consideration of the constituent problems.
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The objective of this project is to understand the stochastic and dynamical properties of the global foreign exchange market. High-frequency electronic broking data will enable the construction of a time-evolving correlation network and analysis of the dynamic evolution of community structure. This research will examine market inefficiencies that can only be probed using accurate high-frequency data and develop theoretical advances in dynamic network analysis of importance in numerous applications.
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The objective of this project is to understand the predictability of behaviour of the earth’s atmosphere to explain the success of operational weather forecasts based on space-time averaged models of the real system. An investigation will be made of the relationship between solutions of the full Navier-Stokes equations and their reduction to the semi-geostrophic equations, valid on large scales where the flow is dominated by the effects of the earth’s rotation. Understanding the high predictability of the real system through this research could then be exploited to improve operational systems.
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The objective of this project is to improve the understanding of fluid dynamics over sports equipment designed for drag reduction through the understanding and control of boundary layer flows. The optimisation of equipment can be used to reduce drag, increase lift, or induce some other
useful force.
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The aim of the project is to provide new tools for design-risk analysis of complex systems allowing early design decisions to be informed by their reliability impact (and in certain cases, by implication, their safety impact). Additionally, maintenance and fault diagnosis could be based on a deep understanding of the system components and their interactions.
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This project aims to extend and adapt signal processing and discrimination techniques for separating normal from disordered subjects by analysis of speech signals. This project will improve the reliability and applicability of existing techniques by managing and reporting uncertainty in realistic clinical settings with background noise. This work will contribute to the growth in automated, remote and objective assessment of symptoms for assisted living in an ageing population.
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This project explored a range of issues surrounding the development of powerful algorithms for collaborative decision making between multiple, independent robots operating in a dynamic environment. The effectiveness, robustness, scaleability and fault tolerance of algorithms were tested with the use of state-of-the-art robotic equipment. The combination of software advances developed in this project together with hardware developments by the industrial partner has provided insights into the use of systems of autonomous mobile robots in exploring hostile and unknown environments.
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This project will compare and improve approaches to resolving the multipath and tracking for sonar and radar applications. A range of approaches to handing multiple contact tracking will be compared and a way of including all known principal sources of error in the tracking models will be developed. This work will improve contact localisation and provide a better understanding of error sources than the traditional approach of extended Kalman filter.
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The objective of this projects is to understand the dynamic behaviour of silica and other constituent minerals as they melt to form a pool of molten glass. The project will involve mathematical modelling including fluid dynamics, heat transfer, asymptotic analysis and computational methods as well as close involvement with experimental work at Pilkington Technical Centre.
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This project will develop predictive models for ion diffusion processes in float glass by a combination of mathematical modelling and SIMS depth profiling experiments. Physical properties resulting from ion diffusion will be predicted as functions of production and processing conditions. A predictive model for ion diffusion is important in the prevention of bubble formation, the major cause of loss in glass manufacture, and glass corrosion during storage and use.
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This project aims to explain some statistical properties of natural images via a fundamental hypothesis that images are made up of objects. Object-based modelling and mutual information will be used to develop a novel approach for explaining non-Gaussianity of images. Internal features of natural images will be investigated mathematically and statistically with the aim of creating new mathematical tools to be incorporated into real digital devices.
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This project aims to predict the best optimisation approach for large scale, typically hierarchical, optimisation problems where the objective function is expensive to evaluate. The project will compare a range of approaches to optimisation with an emphasis on methods using sequential approximation to the objective function. The ultimate aim is to produce a library of optimisation subroutines using emulators that could be incorporated into other engineering software.
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This project will develop algorithms for improved noise estimation in active sonar by incorporating environmental models. Background noise is highly variable in both the spatial and temporal domain and often can be linked to features in the environment. Improving adaptive estimation of background noise is fundamental to the detection and tracking of targets in different environments.
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This project aims to improve the understanding of the behaviour of random composites and/or pre-stressed
composites capable of large deformation. Specifically the issue of low frequency excitation will be addressed.
Numerical methods are costly in terms of computational time and resources, and do not give a great deal of
insight into the physical processes involved. Therefore, mathematical homogenization schemes will be developed
and extended in order to tackle the various model problems.
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This project will develop and evaluate graphical models for collaborative filtering. Probabilistic recommender systems capable of hidden variables underpinning preference, choice and purchase behaviour will be developed within the Bayesian belief networks framework.
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This project will construct mathematical models of the pathomechanisms of work-related musculoskeletal disorders (WRMSDs). Integrative biology and multi-scale modelling will be used to combine existing research on wound healing and soft tissue growth under stress to construct novel generic soft tissue models. These will be of predictive value in determining the important pathomechanisms associated with WRMSDs and in identifying what helps / hinders the recovery process.
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This project is investigating the use of autonomous operation to achieve faster air-to-gate-to-air transit at airports. Uncertainty will be included in an iterative mixed integer linear programming approach and scalable solutions will be determined through the development of distributed solution methods. The requirements for the communication network infrastructure and computation and sensing on board each aircraft will be identified.
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This project will examine the use of natural and mixed-mode ventilation for low energy building design. Experimental fluid dynamics will be combined with well-established reduced numerical models to investigate time-dependent ventilation flows. Different mechanical systems and ventilation strategies will be assessed to quantify the potential energy savings associated with mixed-mode ventilation.
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This project will identify new mathematical approaches to best match and proximity searching with particular application to very large, compressed and encrypted textual data stores. Encryption presents particular challenges in that with a good approach there should be no relationship between an encrypted document and an encrypted very similar document. Cluster based multiresolution methods will be developed to exploit the anticipated exact match in summary data for similar documents.
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This project will establish interactive algorithms for the generation of photo-quality facial composites for criminal investigations. Robust, accurate and fast evolutionary search strategies will be developed that incorporate fuzziness in the fitness evaluation in response to cognitively simple user decisions. The aim is to replace current systems that rely on recall and verbal description with a system that makes direct use of the highly developed human capacity for facial recognition.
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Suppose a number of acoustic sensors distributed over a city detect a gunshot. Where did it originate? The plan in this project is to study this inverse problem for sound in a complex and partly unknown environment.
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The aim of this Faraday research project is to model, evaluate and build a decision support system that works alongside advanced intrusion detection systems. Intrusion Detection Systems are software systems designed to identify and prevent the misuse of computer networks and systems. The project is to
explore mathematical methods for intrusion detection data mining in order to create knowledge bases that represent high-level threat models, situational models and attacker profiles. Such knowledge bases may then be used to process data from distributed intrusion detection sensors in real time (this process is known as data fusion). This should allow an intrusion detection system to present a richer, more accurate, picture of current threats by being able to piece together information from diverse sources.
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The aim of this Faraday Partnership project is improve existing models of composite materials, comprising microspheres in a rubber substrate, to predict changes in effective bulk properties with applied quasistatic pressure and in response to dynamic acoustic and vibration fields. In particular the model development will assess potential explanations of the experimentally observed hysteresis in compression. Composite materials of this kind are used as coatings for submarines and this research will enhance understanding of their behaviour for that application.
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The aim of this Faraday Partnership project is to study the effects of flow/director interactions on the switching characteristics of a post-aligned bistable nematic liquid crystal device. A novel flow boundary condition will be applied to the Ericksen-Leslie equations to investigate the back-flow and kick-back effects of flow/director interactions at the device substrate. This research will lead to more detailed understanding of director dynamics and avoidance of reverse switching in bistable nematic liquid crystal devices.
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The aim of this Faraday Partnership project is to develop powerful and robust algorithms for the sequencing and scheduling of airport runways. A range of meta-heuristic approaches will be investigated, and methods developed for handling the complexities of the physical manoeuvring and the uncertainty inherent in the problem. Runways are a critical bottleneck in the air transport system and using them with maximum efficiency is a key objective for air traffic control.
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The aim of this project is to create new models for scheduling of a large, mobile workforce in a dynamic environment. Existing approaches lack the flexibility to make the most efficient use of available human and other resources for such complex problems. More efficient work team schedules offer the potential for considerable financial return for the large problem considered.
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The aim of this Faraday Partnership project is to develop a quantitative theory of the mechanism of adsorption in strongly interacting polymer-surfactant mixtures. A mathematical model linking the surface tension and adsorption behaviour with the bulk phase behaviour will provide a sound quantitative basis for interpretation of experimental data. The resulting understanding will have direct relevance to the formulation, processing and use of fabric conditioners, detergents and shampoo.
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The aim of this Faraday Partnership project is to develop theoretical models to describe multiphase flows in flexible microchannels found in biological and engineered networks. Asymptotic and numerical techniques appropriate to free surface flows and flow-structure interactions will be exploited to understand the complex dynamics of instabilities in these systems. This work will help to improve the design of high-throughput microfluidic devices and improve understanding of drug delivery and the release of nutrition or flavour from foods in the small intestine.
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This Faraday Partnership project has developed a new model of droplet drying that overcomes the numerical and conceptual limitations of established models. The model couples droplet properties such as moisture content, particle shape and particle density to a population balance of droplets and a model of turbulent flow. The process of spray drying is used for the production of foods, detergents and many other products and this work will provide a better understanding of the influence of process design on product properties.
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The aim of this Faraday Partnership project is to discover and analyse numerical methods that are as insensitive as possible to grid quality. Novel discretisations of elliptic, hyperbolic and parabolic partial differential equations will be studied to find methods that are stable and convergent for grids that satisfy only the volume bounding property. This work will enable more sophisticated interpretation of a wide range of physical measurements for oil exploration and better design and operation of oil recovery systems that require simulation of flow through complex geological formations.
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The aim of this Faraday Partnership project is to develop mathematical models of predictive value in determining risks associated with chronic exposure to particular classes of chemicals, or to chemical mixtures. Asymptotic and numerical methods will be used to study the complex dynamics of in vitro response of human tissue exposed to toxic chemicals; multi-scale modelling and integrative biology will enable experimental results to be scaled up to make predictions of behaviour in vivo. The models developed in this work will play a crucial complementary role in the use of human tissue culture in place of animal testing, in particular in low dose chronic exposure to solvents and pesticides.
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This Faraday Partnership research project aims to model the movement and orientation of a monolayer of grain flowing down an inclined chute. The effects of chute shape and surface roughness will be explored by developing models on a range of scales from discrete grain dynamics to a continuum model for the grain monolayer and its interaction with the adjacent thin layer of air. Chute re-design resulting in significant increases in grain throughput would bring immediate gains in food sorting machine capacity.
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The aim of the Faraday research project is to develop a better understanding of the underlying mechanisms determining the performance and limitations of curtain coating of paper. Models will be developed to study the stability of a curtain comprising one or more pigment-loaded films and the behaviour in the region of the impact of the curtain with the moving paper web. Curtain coating is well established in the photographic industry and it has many potential advantages over more traditional paper coating methods; this research will support the transfer of this technology into papermaking.
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The aim of this Faraday Partnership research project was to understand the scope for enhanced management of the radio spectrum through informed implementations of spectrum trading and better techniques for channel assignment.
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This Faraday Partnership research modelled interference characteristics in flow from a parallel
array of ducts using slender-flow modelling and flexible marching schemes with
analysis. The target application is the enhanced design of food-sorting machines.
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Consistency of flavour, colour and texture in Chewits is determined by the continuous cooking and mixing of two components. This Faraday Partnership project aimed to develop predictive mathematical models relating the effect of process parameters on the rheological properties of the non-Newtonian confectionery mass.
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The aim of this project is to develop Boolean information networks with decision-making nodes that can be optimised to locally reduce data traffic.
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Naturalistic and qualitative research methods offer the potential to provide rich insight for systems
design. However it is as yet unclear how to apply these insights in a systematic fashion,
and in particular to novel and collaborative technologies.
Using interaction analysis of video materials,
recorded in both real workplaces and experimental situations,
this Faraday Partnership research project seeks a framework for the evaluation of technology.
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Foods such as crumpets and pikelets exhibit a structure consisting of columnar bubbles in a set batter, which develop during cooking. However, blind bubbles (those which are not open at the top surface) are sometimes formed and it may be difficult to achieve the desired columnar structure consistently.
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The aim of this Faraday Partnership project was to develop and include a model of price dynamics into calculations of uncertainty and risk. A realistic price dynamics model was formulated using agent-based simulations and generalised stochastic models. The outcome is a better ability to account for extreme market events, such as crashes, when calculating uncertainty and risk.
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The aim of this Faraday Partnership project is to better understand the meaning of
physical parameters in an imperfect model class, with particular application to the modelling of grid frequency.
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The response of food to microwave radiation depends very sensitively on a number of parameters, which change during the cooking process, especially the saline content and the moisture content of the food. This Faraday Partnership project will model the cooking process in through a series of models of increasing complexity in a variety of controlled geometries. The effects of moisture, salinity, rotation speed of the food and the food/cavity geometry will each be investigated.
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The aim of this Faraday research project was to understand and improve the clinical decision-making process with respect to prosthetic surgery. Historical data on decisions and outcomes were distilled and patterns identified, enabling the information to be formulated for clinical use. Ultimately the aim is to develop generic and applicable decision-support methodologies for clinicians.
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The aim of this Faraday Partnership project is to develop a model of securities prices
without assuming the efficient markets hypothesis. The
principles of behavioural finance will be combined with
rigorous mathematical techniques to account for an inefficient
market setting. Of particular interest is the application of
the new model to the pricing of credit derivatives.
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The aim of this Faraday Partnership project is to quantify, through experiment and modelling, the consequences to ice formation of the impact of super-cooled water droplets. The theoretical work will combine full numerical simulations and asymptotic approximations for impinging droplets including heat transfer between the super-cooled water droplets and the most sensitive surfaces of the aircraft. The aim is to better understand the ice formation on aircraft passing through clouds in order to improve aviation flight safety.
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The aim of this Faraday Partnership project is to determine how remote sensing of accumulation solids in vessels can be improved by applying Industrial Process Tomography.
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The aim of this Faraday Partnership project is to determine and solve suitable models for the pricing of energy derivatives. Asymptotic models for spot and forward curves will be based on daily and weekly periodicities; structured derivatives will be analysed and numerical solutions will be sought. The main application is in the pricing of swing options.
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The aim of this Faraday Partnership project is to construct and analyze models for the dynamics of a pipeline bundle, suspended under two tug boats by chains attached at each end. The result will be a better understanding of the standard procedure for transporting prefabricated pipeline bundles to oil and gas fields in the North Sea.
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The aim of this Faraday Partnership project is to develop 2d and 3d finite element simulations of incompressible, slow, viscous multiple-extrusion flows, for shear-thinning power-law fluids such as toothpaste. The results will help to identify novel multiple extrusion opportunities.
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