Towards an Online Prognostic System for Predicting the Axial Shrinkage of AGR Cores

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Oct 14, 2013
Graeme M. West Christopher J. Wallace Stephen D. J. McArthur

Abstract

In the UK, there is the desire to extend the operation of the Advanced Gas-cooled Reactor (AGR) power plants beyond their initial design lifetimes of 35 years. As part of the justification of extended operation, an increased understanding of the current and future health of the graphite reactor cores is required. One measure of the health of the AGR power plants is the axial height of the graphite core, which can be determined through measurements undertaken during statutory outages. These measurements are currently used to manually make predictions about the future height of the core, through identifying the relevant data sources, extracting the relevant parameters and generating the predictions is time- consuming and onerous. This paper explores an online prognostic approach to support these manual predictions, which provides benefits in terms of rapid, updated predictions as soon as new data becomes available. Though the approach is described with reference to a case study of the UK’s AGR design of power plant, similar challenges of predicting passive structure health also exist in other designs of power plant with planned license extensions.

How to Cite

M. West, G. ., J. Wallace, C., & D. J. McArthur, S. . (2013). Towards an Online Prognostic System for Predicting the Axial Shrinkage of AGR Cores. Annual Conference of the PHM Society, 5(1). https://doi.org/10.36001/phmconf.2013.v5i1.2298
Abstract 146 | PDF Downloads 87

##plugins.themes.bootstrap3.article.details##

Keywords

applications: nuclear

References
Brocklehurst, J. E. & Kelly, B. T. (1993), Analysis of the dimensional changes and structural changes in polycrystalline graphite under fast neutron irradiation, Carbon, Vol 31 Issue 1, pp. 155-178.

Coble J. B., and Hines, J. W. (2008), Prognostic algorithm categorization with PHM Challenge application, International Prognostic and Health Management Conference 2008, p1-11

Coble, J. B., Humberstone, M and Hines, J. W, (2010) Adaptive monitoring, fault detection and diagnostics, and prognostics system for the IRIS nuclear plant, International Prognostic and Health Management Conference 2010

Goebel, K., Saha B., Saxena, A., Celaya, J. and Christophersen, J. (2008) “Prognostics in battery health management,” IEEE Instrumentation & Measurement Magazine, vol. 11, no. 4, pp. 33–40
Goh, K.M. (2006), A review of Research in Manufacturing Prognostics, IEEE Conference on Industrial Informatics, 16-18 August 2006, Singapore, pp417-422.

Hashemian, H. M., Kiger, C. J., Morton, G. W. & Shumaker, B. D. (2011), Wireless Sensor Applications in Nuclear Power Plants, Nuclear Technology, Vol. 173, No. 1, pp 8-16.

Heng, A., Zhang, S., Tan, A. C. C and Mathew, J (2009) Rotating machinery prognostics: State of the art, challenges and opportunities, Mechanical Systems and Signal Processing, Volume 23, Issue 3, p. 724–739

IAEA (2008), Heavy Component Replacement in Nuclear Power Plants: Experience and Guidelines, IAEA Nuclear Energy Series No.NP-T-3.2, Vienna (2008).

Kothamasu, R., S.H. Huang, and W.H. VerDuin (2006), “System Health Monitoring and Prognostics – A Review of Current Paradigms and Practices,” International Journal of Advanced Manufacturing Technology 28: 1012 – 1024.

Li, H., Marsden, B. J. & Fok, S. L. (2004), Relationship between nuclear graphite moderator brick bore profile measurement and irradiation-induced dimensional change, Nuclear Engineering and Design, No. 232 pp.237-247

Pecht, M. (2008), Prognostics and Health Management of Electronics, Wiley, Interscience, New York, NY, 2008.

Pecht, M. and Jaai, R. (2010), A prognostics and health management roadmap for information and electronics- rich systems, Microelectronics Reliability, Volume 50, Issue 3, p. 317–323
Shennan, J.V. (1983), Graphite R&D reveals long life for AGRS. ATOM, No. 323, pp.188-191.

Bond, L.J., Ramuhalli, P., Tawfik, M.S. & Lybeck, N.J. (2011), Prognostics and life beyond 60 years for nuclear power plants. IEEE Conference on Prognostics and Health Management (PHM), 2011, pp.1,7, June 20- 23, doi: 10.1109/ICPHM.2011.6024316

U.S. Department of Energy (2013) Light Water Reactor Sustainability Program: Integrated Program Plan, INL/EXT-11-23452, Revision 1

Varde, P. V. and Pecht, M. G., (2012) Role of Prognostics in Support of Integrated Risk-based Engineering in Nuclear Power Plant Safety, International Journal of Prognostics and Health Management, ISSN 2153-2648, 2012 008

West, G.M., Wallace, C.J., Jahn, G. J., McArthur, S. D.J., & Towle, D. (2010), Predicting the ageing of advanced gas-cooled reactor (AGR) graphite bricks. Seventh American Nuclear Society International Topical Meeting on Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, Las Vegas Nov. 2010.
Section
Technical Research Papers