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Enhancing competitive advantage at Pratt & Whitney using Design for Variation

Summary of the impact

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.

Submitting Institution

University of Nottingham

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Artificial Intelligence and Image Processing
Economics: Econometrics

Incorporating expert knowledge in complex industrial and policy applications

Summary of the impact

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.

Submitting Institution

University of Nottingham

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Economics: Applied Economics, Econometrics

Policy implications of uncertainties related to climate change

Summary of the impact

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.

Submitting Institution

University of Durham

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Environmental

Research Subject Area(s)

Mathematical Sciences: Statistics

Enhanced reservoir management in the oil/gas sector via new algorithms for large-scale optimization

Summary of the impact

Research in the HWCS Intelligent Systems Lab since 2006 has developed approaches to accelerate and improve large-scale optimization. This has led to new algorithms that enable multiple high-quality solutions for complex problems, either more quickly, with better solution quality than previously obtainable, or both. These algorithms, combined with uncertainty quantification techniques from related research, have been adopted by both British Petroleum Plc (BP) and Epistemy Ltd (an SME serving the oil/gas sector). Impact for BP includes improved business decision-making (relating to ~$330M in turnover),and impact for Epistemy includes sales of £230k.

Submitting Institution

Heriot-Watt University

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Numerical and Computational Mathematics, Statistics
Information and Computing Sciences: Computation Theory and Mathematics

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