Journal of Nuclear Science, Engineering and Technology (JONSAT)
In cooperation with the Iranian Nuclear Society

Burn up effect on optimal placement of fixed in-core detectors for Tehran research reactor using information theory

Document Type : Research Paper

Authors

M.S. Terman
N. Mataji Kojouri
H. Khalafi

Reactor and Nuclear Safety Research School, Nuclear Science and Technology Research Institute, P.O.Box: 14155-1339, Tehran - Iran

https://doi.org/10.24200/nst.2020.1125
Abstract
Monitoring the power distribution of reactor core is one of the most challenging issues in the safe operation of nuclear reactors. The Number and arrangement of detectors in a core monitoring system should be determined in a way that maximum amount of information about core states is extracted, while avoiding duplication of similar and correlated measurements. Information theory is the best method to deal with the problem of optimal number and placement of instruments. In this paper, the effects of reactor fuel burn-up on the optimal number and arragement of in-core fixed detectors of Tehran Research Reactor has been investigated using information theory. Comparison the results for the two modes, with and without consideration of the fuel burn-up, shows that by considering fuel burn-up in the placement problem, more information can be extracted from measurements of the detectors. Also, for an equal number of detectors, determined arrangement by considering fuel burn-up, mostly provide larger share of total available information in the data set. Using the optimal arrangement, maximum information can be obtained from minimum number of the detectors, which leads to considerable decrease in the cost of construction, implementation, operation, and maintenance of the in-core detectors for monitoring of neutron flux.
 

Highlights

1. X. Peng, K. Wang, Q. Li, A new power mapping method based on ordinary kriging and determination of optimal detector location strategy. Annals of Nuclear Energy, 68, 118-123 (2014).

 

2.             W.A. Boyd, R.W. Miller, The BEACON on-line core monitoring system: functional upgrades and applications. in Proc. Specialists' Meeting “In-core instrumentation and core assessment”, Mito-shi, Japan. (1996).

 

3.             M. Tojo, et al., Application of the New Core Monitoring System,'GNF-ARGOS', to the Start-up Tracking Calculation of ABWR. in PHYSOR'08: International Conference on the Physics of Reactors 'Nuclear Power: A Sustainable Resource'. Interlaken (Switzerland) (2008).

 

4.             S. Mishra, R. Modak, S. Ganesan, Computational Schemes for Online Flux Mapping System in a Large-Sized Pressurized Heavy Water Reactor. Nuclear Science and Engineering, 170(3), 280-289 (2012).

 

5.             K. Lee, C.H. Kim, The Least-Squares Method for Three-Dimensional Core Power Distribution Monitoring in Pressurized Water Reactors. Nuclear Science and Engineering, 143(3), 268-280 (2003).

 

6.             M.E. Pomerantz, C.R. Calabrese, C. Grant, Nuclear reactor power and flux distribution fitting from a diffusion theory model and experimental data. Annals of Nuclear Energy, 29(9), 1073-1083 (2002).

 

7.             A.M. El-Badry, A.S. Hassan, Sensitivity of developed self-powered neutron detector, in Fourth Conference on Nuclear and Particle Physics. Fayoum, Egypt., 294 (2003).

 

8.             L. Wanno, et al., A study on the sensitivity of self-powered neutron detector (SPND). in 1999 IEEE Nuclear Science Symposium. Conference Record. 1999 Nuclear Science Symposium and Medical Imaging Conference (Cat. No.99CH37019) (1999).

 

9.             A. Krause, et al., Near-optimal sensor placements: Maximizing information while minimizing communication cost. in Proceedings of the 5th international conference on Information processing in sensor networks. ACM (2006).

 

10. M. Basseville, et al., Optimal sensor location for detecting changes in dynamical behavior. in 1986 25th IEEE Conference on Decision and Control. (1986).

 

11.          J. Park, Y. Lim, Survey of Sensor Placement Methods for Structural Health Monitoring. International Journal of Energy, Information and Communications, 6(4), 35-44 (2015).

 

12. S.      Mishra, R.S. Modak, S. Ganesan, Selection of fuel channels for Thermal Power Measurement in 700 MWe Indian PHWR by evolutionary algorithm. Nuclear Engineering and Design, 247, 116-122 (2012).

 

13. B.R. Upadhyaya, F. Li, Optimal sensor placement strategy for anomaly detection and isolation. in 2011 Future of Instrumentation International Workshop (FIIW) Proceedings. (2011).

 

14. D.Y. Oh, H.C. No, Determination of the minimal number and optimal sensor location in a nuclear system with fixed incore detectors. Nuclear Engineering and Design, 152(1), 197-212 (1994).

 

15. L.M. Nunes, et al., Optimal estuarine sediment monitoring network design with simulated annealing. Journal of Environmental Management, 78(3), 294-304 (2006).

 

16. M. Al-Zahrani, T. Husain, An algorithm for designing a precipitation network in the south-western region of Saudi Arabia. Journal of Hydrology, 205(3), 205-216 (1998).

 

17. P.F. Krstanovic, V.P. Singh, Evaluation of rainfall networks using entropy: I. Theoretical development. Water Resources Management, 6(4), 279-293 (1992).

 

18. P.F.   Krstanovic, V.P. Singh, Evaluation of rainfall networks using entropy: II. Application. Water Resources Management, 6(4), 295-314 (1992).

 

19. A.K. Mishra, P. Coulibaly, Developments in hydrometric network design: A review. Reviews of Geophysics, 47(2), (2009).

 

20. C.E. Shannon, A mathematical theory of communication. The Bell System Technical Journal, 27, 379–423, 623–656 (1948).

 

21. L. Alfonso, A. Lobbrecht, R. Price, Locating Monitoring Water Level Gauges: An Information Theory Approach, in 7th ISE & 8th HIC. China (2009).

 

22. B.     Ainslie, et al., Application of an entropy-based Bayesian optimization technique to the redesign of an existing monitoring network for single air pollutants. Journal of Environmental Management, 90(8), 2715-2729 (2009).

 

23. A.     Krause, A. Singh, C. Guestrin, Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies. J. Mach. Learn. Res., 9, 235-284 (2008).

 

24.R.W. Yeung, Information theory and network coding. Springer Science & Business Media (2008).

 

25.R.E. Uhrig, L.H. Tsoukalas, Soft computing technologies in nuclear engineering applications. Progress in Nuclear Energy, 34(1), 13-75 (1999).

Keywords

Research reactor
Fixed in-core detector
Optimal placement
Information theory
Fuel burn-up
1. X. Peng, K. Wang, Q. Li, A new power mapping method based on ordinary kriging and determination of optimal detector location strategy. Annals of Nuclear Energy, 68, 118-123 (2014).
 
2.             W.A. Boyd, R.W. Miller, The BEACON on-line core monitoring system: functional upgrades and applications. in Proc. Specialists' Meeting “In-core instrumentation and core assessment”, Mito-shi, Japan. (1996).
 
3.             M. Tojo, et al., Application of the New Core Monitoring System,'GNF-ARGOS', to the Start-up Tracking Calculation of ABWR. in PHYSOR'08: International Conference on the Physics of Reactors 'Nuclear Power: A Sustainable Resource'. Interlaken (Switzerland) (2008).
 
4.             S. Mishra, R. Modak, S. Ganesan, Computational Schemes for Online Flux Mapping System in a Large-Sized Pressurized Heavy Water Reactor. Nuclear Science and Engineering, 170(3), 280-289 (2012).
 
5.             K. Lee, C.H. Kim, The Least-Squares Method for Three-Dimensional Core Power Distribution Monitoring in Pressurized Water Reactors. Nuclear Science and Engineering, 143(3), 268-280 (2003).
 
6.             M.E. Pomerantz, C.R. Calabrese, C. Grant, Nuclear reactor power and flux distribution fitting from a diffusion theory model and experimental data. Annals of Nuclear Energy, 29(9), 1073-1083 (2002).
 
7.             A.M. El-Badry, A.S. Hassan, Sensitivity of developed self-powered neutron detector, in Fourth Conference on Nuclear and Particle Physics. Fayoum, Egypt., 294 (2003).
 
8.             L. Wanno, et al., A study on the sensitivity of self-powered neutron detector (SPND). in 1999 IEEE Nuclear Science Symposium. Conference Record. 1999 Nuclear Science Symposium and Medical Imaging Conference (Cat. No.99CH37019) (1999).
 
9.             A. Krause, et al., Near-optimal sensor placements: Maximizing information while minimizing communication cost. in Proceedings of the 5th international conference on Information processing in sensor networks. ACM (2006).
 
10. M. Basseville, et al., Optimal sensor location for detecting changes in dynamical behavior. in 1986 25th IEEE Conference on Decision and Control. (1986).
 
11.          J. Park, Y. Lim, Survey of Sensor Placement Methods for Structural Health Monitoring. International Journal of Energy, Information and Communications, 6(4), 35-44 (2015).
 
12. S.      Mishra, R.S. Modak, S. Ganesan, Selection of fuel channels for Thermal Power Measurement in 700 MWe Indian PHWR by evolutionary algorithm. Nuclear Engineering and Design, 247, 116-122 (2012).
 
13. B.R. Upadhyaya, F. Li, Optimal sensor placement strategy for anomaly detection and isolation. in 2011 Future of Instrumentation International Workshop (FIIW) Proceedings. (2011).
 
14. D.Y. Oh, H.C. No, Determination of the minimal number and optimal sensor location in a nuclear system with fixed incore detectors. Nuclear Engineering and Design, 152(1), 197-212 (1994).
 
15. L.M. Nunes, et al., Optimal estuarine sediment monitoring network design with simulated annealing. Journal of Environmental Management, 78(3), 294-304 (2006).
 
16. M. Al-Zahrani, T. Husain, An algorithm for designing a precipitation network in the south-western region of Saudi Arabia. Journal of Hydrology, 205(3), 205-216 (1998).
 
17. P.F. Krstanovic, V.P. Singh, Evaluation of rainfall networks using entropy: I. Theoretical development. Water Resources Management, 6(4), 279-293 (1992).
 
18. P.F.   Krstanovic, V.P. Singh, Evaluation of rainfall networks using entropy: II. Application. Water Resources Management, 6(4), 295-314 (1992).
 
19. A.K. Mishra, P. Coulibaly, Developments in hydrometric network design: A review. Reviews of Geophysics, 47(2), (2009).
 
20. C.E. Shannon, A mathematical theory of communication. The Bell System Technical Journal, 27, 379–423, 623–656 (1948).
 
21. L. Alfonso, A. Lobbrecht, R. Price, Locating Monitoring Water Level Gauges: An Information Theory Approach, in 7th ISE & 8th HIC. China (2009).
 
22. B.     Ainslie, et al., Application of an entropy-based Bayesian optimization technique to the redesign of an existing monitoring network for single air pollutants. Journal of Environmental Management, 90(8), 2715-2729 (2009).
 
23. A.     Krause, A. Singh, C. Guestrin, Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies. J. Mach. Learn. Res., 9, 235-284 (2008).
 
24.R.W. Yeung, Information theory and network coding. Springer Science & Business Media (2008).
 
25.R.E. Uhrig, L.H. Tsoukalas, Soft computing technologies in nuclear engineering applications. Progress in Nuclear Energy, 34(1), 13-75 (1999).

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