Cullis, IG and Kelmanson, MA (2016) Cost-effective simulation and prediction of explosions for military and public safety, and for improved oil extraction. In: Aston, PJ, Mulholland, AJ and Tant, KMM, (eds.) UK Success Stories in Industrial Mathematics. Springer , pp. 155-161. ISBN 978-3-319-25452-4
Abstract
An MoD-funded research programme based in Applied Mathematics at Leeds University has resulted in demonstrable long-term and ongoing benefits on diverse fronts for beneficiaries in a range of public and private sectors. First, by guaranteeing robustness and reliability of bespoke numerical methods for the MoD, the joint research led to substantial financial savings in ballistic-development programmes, thereby enabling the delivery of advanced research output cost-effectively under severe budgetary pressures. As a result, QinetiQ was placed as a world leader in the simulation of explosions, which supported the MoD to rapidly assess and develop countermeasures to the ever-changing threats faced by British Forces in Afghanistan and Iraq, and to reduce casualties. It also enabled government agencies to assess threats to transport and public-building infrastructure. Second, the joint research underpinned substantial recurrent income for QinetiQ, who has additionally developed the codes with the oil industry to develop a new explosive perforator for oil extraction that has not only led to demonstrable improvements in both extraction efficiency and research-and-development costs, but has also yielded recurrent licensing royalties.
Metadata
Item Type: | Book Section |
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Authors/Creators: |
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Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Sep 2015 11:30 |
Last Modified: | 07 Apr 2017 09:03 |
Published Version: | http://dx.doi.org/10.1007/978-3-319-25454-8_20 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-319-25454-8_20 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:90234 |