Our research draws together mathematical expertise from across the University to address a wide range of problems in mathematics and its applications.
Our research themes include, but are not limited to:
- efficient multiscale numerical simulation
- detecting structure and correlation in ‘big data’
- optimal management of limited resources, with uncertainty
- assessing risk (specific, systemic, systematic)
- model construction, data assimilation, and uncertainty quantification
- emergent properties, from the discrete to the continuous
Bath IMI also hosts MI-NET (Mathematics for Industry Network). Through Horizon 2020 COST (European Cooperation in Science and Technology) funding, MI-NET will support a pan-European programme of activites to stimulate greater interaction between mathematicians and industrialists.
The Met Office plays a vital role in the UK economy by providing accurate weather forecasts, but a major limitation of forecast accuracy is the ability to blend computational modelling with observational data. In collaboration with the Met Office, University of Bath mathematicians have developed adaptive numerical methods that allow computational models to make better use of data. As a result of implementing these methods into operational models, the Met Office forecasting accuracy of temperatures near the ground has demonstrably improved, helping local councils, airports and the travelling public.
Clinical trials are a crucial step in translating fundamental medical research into improved healthcare. But they are expensive to conduct, and making changes to a trial while preserving statistical validity is difficult. Research carried out at Bath has developed methods to help make decisions on when to stop a study, and to allow a broader range of adaptations to be made during the course of a trial. The results of this research have made clinical trials faster and more efficient while maintaining safety.
Air pollution poses significant threats to both the environment and to human health. The World Health Organisation reports that in 2012 around 7 million premature deaths were due to air pollution exposure, making it the world’s largest single environmental health risk. Our researchers developed a large-scale computer simulation model that provides a flexible platform for developing a wide variety of models for predicted exposures. This has impacted on public policy and has resulted in the US Environmental Protection Agency making changes to legislation and regulations governing acceptable air quality.
Forests are economically, recreationally and environmentally important, but it is difficult to monitor their health. Statisticians at Bath have worked with the Forest Research Institute Freiburg (Baden-Württemberg, Germany) to develop a new statistical model to estimate trends in forest health from monitoring data. As a result, forests are being better managed, mitigating the effects of pollution and climate change.
AMEC Foster Wheeler is a global leader in the field of nuclear safety advice. The company has a range of software used to assess the safety and operation of nuclear facilities. The company has built up a powerful suite of software for modelling and simulation of such facilities. Our research team identified conditions under which AMEC Foster Wheeler’s Monte Carlo perturbation module was not guaranteed to converge and suggested an improvement that prompted the company to recode parts of this module to extend the range of scenarios to which it can be applied.
Cleft lip is one of the most common birth defects, affecting 1 in 700 children. Surgery to correct the condition has to be balanced between improving a child’s looks, while avoiding nerve damage that inhibits the development of normal expression and eating functions. Our researchers have worked with physicians in the USA to develop ways to understand data taken from motion capture of patients with cleft lip. The result is a new tool that surgeons can use to decide whether surgery is advisable, gives guidance on what form the surgery should take, and provides a way to evaluate the outcome of surgery objectively.
Modern oil extraction is highly simulation-driven. Decisions on where to search for oil and where to place wells depend on accurate and efficient simulations of the physical processes of oil flow underground. The partner for this project, the Institut Français du Petrole Energies Nouvells (IFPEN), was faced with a changing environment in which its competitors were investing in large efficiency improvements in their simulators. By improving the simulation algorithms used by IFPEN’s software packages, our researchers created a ten-fold increase in simulation speed, creating more efficient and robust algorithms.