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Methods of emulation, model calibration and uncertainty analysis developed by Professor Tony O'Hagan and his team at The University of Nottingham (UoN) have formed the basis of Pratt & Whitney's Design for Variation (DFV) initiative which was established in 2008. The global aerospace manufacturers describe the initiative as a `paradigm shift' that aims to account for all sources of uncertainty and variation across their entire design process.
Pratt & Whitney considers their implementation of the methods to provide competitive advantage, and published savings from Pratt & Whitney adopting the DFV approach for a fleet of military aircraft are estimated to be approximately US$1billion.
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.
Techniques developed at The University of Nottingham (UoN) have enabled organisations to deal with uncertainty in complex industrial and policy problems that rely on the elicitation of expert opinion and knowledge. The statistical toolkit produced for use in complex decision-making processes has been deployed in a wide range of applications. It has been particularly useful in asset management planning in organisations such as the London Underground, government approaches to evidence-based policy, and the Met Office UK Climate Projection tool (UKCP09), which is used by hundreds of organisations across the UK such as environment agencies, city and county councils, water companies and tourist boards.
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.
Ocean circulation accounts for much of the energy that drives weather and climate systems; errors in the representation of the ocean circulation in computational models affect the validity of forecasts of the dynamics of the ocean and atmosphere on daily, seasonal and decadal time scales. Research undertaken by the University of Reading investigated systematic model errors that resulted from data assimilation schemes embedded in the key processes used to predict ocean circulation. The researchers developed a new bias correction technique for use in ocean data assimilation that alleviates these errors. This has led to significant improvements in the accuracy of the forecasts of ocean dynamics. The technique has been implemented by the Met Office and by the European Centre for Medium Range Weather Forecasting (ECMWF) in their forecasting systems, resulting in major improvements to the prediction of the weather and climate from oceanic and atmospheric models. The assimilation technique is also leading to better use of expensively acquired satellite and in-situ data and improving ocean and atmosphere forecasts used by shipping and civil aviation, energy providers, insurance companies, the agriculture and fishing communities, food suppliers and the general public. The impact of the correction procedure is also important for anticipating and mitigating hazardous weather conditions and the effects of long-term climate change.
The School of Mathematics at Cardiff University has developed important statistical and mathematical models for forecasting consumer buying behaviour. Enhancements to classical models, inspired by extensively studying their statistical properties, have allowed us to exploit their vast potential to benefit the sales and marketing strategies of manufacturing and retail organisations. The research has been endorsed and applied by Nielsen, the #1 global market research organisation that provides services to clients in 100 countries. Nielsen has utilised the models to augment profits and retain their globally leading corporate position. This has led to a US$30 million investment and been used to benefit major consumer goods manufacturers such as Pepsi, Kraft, Unilever, Nestlé and Procter & Gamble. Therefore the impact claimed is financial. Moreover, impact is also measurable in terms of public engagement since the work has been disseminated at a wide range of national and international corporate events and conferences. Beneficiaries include Tesco, Sainsbury's, GlaxoSmithKline and Mindshare WW.
The Climate Change Act, 2008, constructed a legally-binding long-term framework for the UK to cut greenhouse gas emissions and a framework for building the UK's ability to adapt to a changing climate. The Act requires a UK-wide climate change risk assessment (CCRA) that must take place every five years and a national adaptation programme (NAP), setting out the Government's objectives, proposals and policies for responding to the risks identified in the CCRA. The CCRA, and thus the NAP, drew heavily on the uncertainty analysis for future climate outcomes, published in 2009 by the Met Office as the UK Climate Projections UKCP09, which in turn drew heavily on research into the Bayesian analysis of uncertainty for physical systems modelled by computer simulators carried out at Durham University. A wide range of industries and public sector organisations likely to be affected by climate change have consulted with the Met Office on UKCP09 to inform decisions on policy and investment, involving billions of pounds, in sectors as diverse as flood defence, transport, energy supply and tourism.
This impact case study is based on a Knowledge Transfer Partnership (KTP) between the School of Mathematics, Statistics and Actuarial Science, University of Kent and KROHNE Ltd, a world leading manufacturer of industrial measuring instruments. These precision instruments (typically flow meters and density meters) need to be calibrated accurately before being used and this is an expensive and time-consuming process.
The purpose of the KTP was to use Bayesian methodology developed by Kent statisticians to establish a novel calibration procedure that improves on the existing procedure by incorporating historical records from calibration of previous instruments of the same type. This reduces substantially the number of test runs needed to calibrate a new instrument and will increase capacity by up to 50%.
The impact of the KTP, which was graded as `Outstanding', has been to change the knowledge and capability of the Company, so that they can improve the performance of their manufacturing process by implementing this novel calibration method. This has been achieved by adapting the underpinning Kent research to the specific context of the calibration problem, by running many calibrations to demonstrate the effectiveness of the method in practice, and by supporting the implementation of the new calibration method within the Company's core software.
Moreover, the project has changed the Company's thinking on fundamental science, particularly industrial mathematics. The value of historical data, and the usefulness of Bayesian methods, is now widely appreciated and training for staff in Bayesian Statistics is being introduced. Thus the project has not only changed the protocols of the Company, it has also changed their practice.
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.
The safe operation of ships is a high priority task in order to protect the ship, the personnel, the cargo and the wider environment. Research undertaken by Professor Alexander Korobkin in the School of Mathematics at UEA has led to a methodology for the rational and reliable assessment of the structural integrity and thus safety of ships and their cargos in severe sea conditions. Central to this impact is a set of mathematical models, the conditions of their use, and the links between them, which were designed to improve the quality of shipping and enhance the safety of ships. The models, together with the methodology of their use, are utilised by the ship certification industry bringing benefits through recognised quality assurance systems and certification.