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This impact case study describes the development and application of models of training and performance in elite cycling. These models have been used by elite medal winning teams in their search for competitive advantage in the UK (by British Cycling and British Triathlon, including the GB Olympic Cycling and British Triathlon Teams and the British Paralympic Team) and internationally (by the Australian Institute of Sport). These new cycling models have provided the basis for the development of new training processes that are influencing the way in which many nations prepare their elite riders. This work has contributed directly to enhance elite sports science practice in the field of cycling and the competitive advantage for British teams to which it contributes is envied around the world. The adoption of the underlying algorithms for the `Wattbike' software has given our work a wider impact on sports practice and training methods, and it has been adapted for the `Map My Tracks' website which is used by sports enthusiasts worldwide.
A dedicated specialist mathematical modelling unit in the H. Lee Moffitt Cancer Center, Tampa, FL, USA, was set up — the Integrated Mathematical Oncology Unit (IMO) — through the movement of three staff with expertise in cancer modelling from the UoA's Mathematical Biology (MB) research group. Clinical practice has been changed and patient treatment improved through the work of IMO.
Modelling by members of the MB research group and the move of a former PDRA led to Cyclacel Ltd. and AstraZeneca obtaining a better understanding of the link between drug-dose and drug-efficacy in a class of cell-cycle-specific anti-tumour drugs called Aurora kinase inhibitors and has led to enhanced business performance.
Research at the University of Strathclyde has increased the economic and policy modelling capacity of the Scottish Government. This has been affected through collaboration between researchers at Strathclyde and the Office of the Chief Economic Advisor (OCEA) and the Scottish Government-funded Centre of Expertise in Climate Change, ClimateXChange. The improvement in modelling capability and scope has enhanced the process of policy formation and evaluation, as well as the outcomes from it. This has allowed for improved decision making in the Scottish Government, allowed significant budget savings, improved advice to Scottish Ministers, improved interaction with the Westminster Government and resulted in a more informed public debate on policy decisions.
A two-dimensional flood inundation model called LISFLOOD-FP, which was created by a team led by Professor Paul Bates at the University of Bristol, has served as a blueprint for the flood risk management industry in the UK and many other countries. The documentation and published research for the original model, developed in 1999, and the subsequent improvements made in over a decade of research, have been integrated into clones of LISFLOOD-FP that have been produced by numerous risk management consultancies. This has not only saved commercial code developers' time but also improved the predictive capability of models used in a multimillion pound global industry that affects tens of millions of people annually. Between 2008 and 2013, clones of LISFLOOD-FP have been used to: i) develop national flood risk products for countries around the world; ii) facilitate the pricing of flood re-insurance contracts in a number of territories worldwide; and iii) undertake numerous individual flood inundation mapping studies in the UK and overseas. In the UK alone, risk assessments from LISFLOOD-FP clones are used in the Environment Agency's Flood Map (accessed on average 300,000 times a month by 50,000 unique browsers), in every property legal search, in every planning application assessment and in the pricing of the majority of flood re-insurance contracts. This has led to more informed and, hence, better flood risk management. A shareware version of the code has been available on the University of Bristol website since December 2010. As of September 2013, the shareware had received over 312 unique downloads from 54 different countries.
Waltham's software, developed at Royal Holloway, is impacting on the oil and gas industry. For Statoil, one of the beneficiaries, it "influenced multi-million pound decisions" (Doré, Statoil Chief Geologist 2012) in their exploitation of the Gudrun oilfield, which required a £5 billion exploration investment. The software predicts the location of oil and gas reservoirs by simulating their formation by turbidity currents. The Royal Holloway software was commercialized by Midland Valley Exploration Ltd (MVE), used in consultancy work and sold to major oil-companies. Sales have generated £120k (Q3-2008 to Q2-2011) and created high-quality employment for three staff members at MVE.
Loudness is the subjective magnitude of a sound as perceived by human listeners and it plays an important role in many human activities. It is determined jointly by the physical characteristics of a sound and by characteristics of the human auditory system. A model for predicting the loudness of sounds from their physical spectra was developed in the laboratory of Professor Brian Moore with support from an MRC programme grant.
The model formed the basis for an American National Standard and is currently being prepared for adoption as a standard by the International Organization for Standardisation (ISO). In addition, the model has been widely used in industry worldwide for prediction of the loudness of sounds, for example: noise from heating, ventilation and air-conditioning; inside and outside cars, and from aircraft; and from domestic appliances and machinery.
Data assimilation is playing an ever increasing role in weather forecasting. Implementing four- dimensional variational data assimilation (4DVAR) is part of the long term strategy of the UK Met Office.
In this case study, an idealised 4DVAR scheme, developed by a team from the Universities of Surrey and Reading working with the UK Met Office, based on the integration of Hamiltonian dynamics and nonlinearity into data assimilation, has now been taken up by the Met Office. It is being used to evaluate options for improving operational 4DVAR. The simplicity of the scheme developed by this team has facilitated careful analyses of some generic problems with the operational model. The outcome includes direct impact on the environment and indirect impact on the economy, both through improvements in weather forecasting.
Rail transport is the greenest form of transport in that it produces the least pollution of the environment. However, the noise from squealing trains has been a major factor preventing the wider use of rail transport in populated areas, especially in cities, where trains have to traverse tight curves in built-up areas. Research carried out at Keele University on curve squeal gave crucial input to developing an effective control method (KELTRACK friction modifier, developed by the company LB Foster Friction Management). This is a device by which a thin film is applied at the wheel-rail interface, which in turn destroys the generation mechanism of curve squeal. The KELTRACK friction modifier is now used in transport systems all over the world, especially in underground systems, such as the metros of Tokyo, Beijing and Madrid.
Research by Professor John Thuburn and his group at the University of Exeter has made several key contributions to the formulation and development of ENDGame, the new dynamical core of the Met Office weather and climate prediction model. ENDGame has been shown to deliver improved accuracy and better computational performance at high processor counts compared to the current operational dynamical core, directly impacting the technological tools available to the Met Office. These improvements will benefit users when ENDGame becomes operational in early 2014: the economic value to the UK of the weather forecasts produced by the Met Office has been estimated to be in excess of £600M pa, while climate change projections inform policy decisions on mitigation and adaptation with huge economic implications.
Research conducted at the School of Mathematics at Cardiff University has engineered lifesaving, improvements to UK healthcare systems. New mathematical models, accounting for the complexity and diversity of the health system, have been created and applied in a variety of contexts to markedly enhance the efficiency and effectiveness of a wide range of healthcare services — at policy, commissioning and operational levels. The extensive benefits include:
This work has been disseminated nationally and internationally, in the media and at a range of events designed to engage the public with Mathematics. Therefore the impacts claimed in this case study are health, economic benefits and public engagement.