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The universal application of mathematics and computing across all sectors of the economy is indeed remarkable. New areas of application in sectors such as finance, retail and medicine are taking their places alongside traditional strengths in engineering design and the simulation of industrial processes. The emergence of cross-sectoral themes, for example complex systems or uncertainty and risk, highlight the value of looking outside one's immediate commercial environment for the next wave of innovation. The following paragraphs outline some specific sectoral challenges, followed by links to related projects in the KTN's portfolio.
The simulation of material properties in production and use helps to optimise industrial processes, predict failure and quantify risk. Where only limited data is available from measurements of material structure, sophisticated analysis is required to retrieve the maximum information content. Simulation and data analysis are also useful tools for the design of devices used in the measurement of material properties.
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Financial markets are complex systems. Quantifying uncertainties and risks in financial markets helps to identify business opportunities. A challenge in the simulations of financial market behaviour is the creation of models for the prediction of extreme and unusual events and their impact. Very many large financial datasets exist and are collected routinely, sophisticated analysis of which can yield business-critical information in the form of trends, relationships and patterns.
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Transport networks are complex systems that, through constant monitoring, generate large datasets regarding the state of the infrastructure, its capacity and safety. Models of scheduling can be exploited to manage a transport system more effectively. The sensitive deployment of modern scheduling methods can be exploited to manage a transport system more effectively. With the aid of such methods, schedulers and planners can explore options in both the planning and operational phases. Automotive design is a multidisciplinary activity. Simulations of airflow, EM radiation, noise and vibration, combustion, structure and materials are required to design complex systems with the desired capabilities. This presents significant challenges in the creation of multi-physics models and in combining data and analysis with quantified risks and uncertainties.
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Many food products have complex material properties.
Simulations of texture and consistency development and their dependence
on raw materials, processing and cooking are valuable aids to industrial
design and provide significant computational challenges.
Uncertainties in the markets for supplies need to be quantified and
accounted for in the costs of production. From raw materials to storage
and distribution the process must be traceable and safe.
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A better understanding of the human body as a complex system and simulation
of biological processes and organs enable better design of medical devices
and drugs. Design of a drug and its delivery is a multidisciplinary activity
that should be traceable and must be carried out robustly and safely.
Drug trials, clinical records and bioinformatics give rise to large datasets
that need to be managed properly to extract the most information from their
analysis.
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Communication networks are complex systems. Simulation models of network emergent
behaviour help to forecast capacity and optimise resource allocation to minimise
congestion. Improvements in the management of the radio spectrum can be achieved
through accurate simulation of the propagation of electromagnetic waves through
cluttered environments and various weather conditions.
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Simulation of flows in reservoirs is used extensively by industry in the
management of oil fields. The costs of exploration are reduced when more
information about the structure of the earth can be extracted by sophisticated
analysis of limited seismic data. Condition monitoring is critical and
improvements in the prediction of failures reduce the cost and inefficiency
of excessive backup measures. The energy market is becoming increasingly
complex through privatisation and the provision of renewable energy sources;
weather forecasting is an important factor in the prediction of both demand and
supply of energy and utilities. The use of
end-to-end forecasting methods aids business decision making by projecting
the impact of weather forecasting uncertainties into the end-use domain.
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Increasingly the aerospace and defence industries are required to manage
large projects from cradle to grave and this requires concurrent multidisciplinary
activity. Simulations of airflow, EM radiation, noise and vibration,
combustion, structure and materials are required to design complex systems
with the desired capabilities. This presents significant challenges in the
creation of multi-physics models and in combining data and analysis with
quantified risks and uncertainties.
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Loyalty cards enable retailers to collect data on consumer preferences.
The customer base is a complex system and identifying patterns in the emergent
behaviour, through simulation or data analysis, is valuable in the planning of
strategy. Demand in some markets, for example ice cream, is strongly affected
by weather conditions; understanding market behaviour reduces uncertainty and
costs through the efficient management of stocks.
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