Picture of a black hole

Strathclyde Open Access research that creates ripples...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of research papers by University of Strathclyde researchers, including by Strathclyde physicists involved in observing gravitational waves and black hole mergers as part of the Laser Interferometer Gravitational-Wave Observatory (LIGO) - but also other internationally significant research from the Department of Physics. Discover why Strathclyde's physics research is making ripples...

Strathprints also exposes world leading research from the Faculties of Science, Engineering, Humanities & Social Sciences, and from the Strathclyde Business School.

Discover more...

An intelligent system for monitoring the nuclear refuelling process

Steele, J.A. and Martin, L.A. and McArthur, S.D.J. and Moyes, A.J. and McDonald, J.R. and Howie, D. and Elrick, R. (2001) An intelligent system for monitoring the nuclear refuelling process. In: Large Engineering Systems Conference on Power Engineering, 2001-07-11 - 2001-07-13.

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

Certain types of nuclear reactors contain over 300 fuel assemblies that over time will become depleted and require replacement with new fuel assemblies - this process is known as refuelling. When refuelling a nuclear reactor, the data produced must be evaluated to ensure that the fuel assembly has landed properly in its position, thereby allowing the continued and safe operation of the station. The process of evaluation is time consuming because of the manual interpretation required and the large amount of data produced. This manual interpretation also requires considerable domain experience due to the nature of the domain. This paper will present an intelligent system to automate the process of the data analysis, thereby shortening the evaluation time and providing an explanation of the reasoning behind its conclusions. The intelligent system utilises a knowledge based system, neural network based classification, K-means clustering techniques and rule induction methods to evaluate the data and inform the operator of any errors encountered.