Title: An ontological approach to knowledge management for sustainable nuclear decommissioning

Authors: Steve Wallbridge; Andrew John Lowe; John A. Keane; Goran Nenadic; Jasmin Cooper

Addresses: School of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester, M13 9PL, UK ' School of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester, M13 9PL, UK ' School of Computer Science, The University of Manchester, Manchester, M13 9PL, UK ' School of Computer Science, The University of Manchester, Manchester, M13 9PL, UK ' School of Chemical Engineering and Analytical Science, The University of Manchester, Manchester, M13 9PL, UK

Abstract: Nuclear decommissioning design and operational knowledge may remain relevant over many decades. Designing sustainable operations today requires meaningful simulation of future events, which in turn relies on the accurate representation of all relevant current knowledge. In decommissioning, human agents may be as important for maintaining operational safety as technical systems, so simulations must represent not just technical but tacit knowledge (embedded in practice) and the contextual and perceptual aspects of knowledge - i.e. how the meaning of data changes with the circumstances and viewpoint of stakeholders. We propose that this detail may be captured by ontological knowledge systems, which are augmenting traditional archives, databases or operational flowcharts in other highly interlinked, multi-disciplinary, dynamic and highly specialised fields. Using the example of waste transport modelling, this study discusses how a coherent ontology unifying knowledge, physics and simulations could facilitate the design, assessment and communication of sustainable decommissioning.

Keywords: nuclear decommissioning; ontology; dynamic systems modelling; sustainability; stakeholder communication; knowledge engineering; text mining; waste transport simulation; semantic data; nuclear knowledge management; sustainable decommissioning; nuclear waste; nuclear energy; nuclear power; tacit knowledge; ontological knowledge systems; modelling.

DOI: 10.1504/IJNKM.2014.058924

International Journal of Nuclear Knowledge Management, 2014 Vol.6 No.3, pp.199 - 216

Received: 11 May 2013
Accepted: 23 Jun 2013
Published online: 23 Oct 2014 *

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