A Study on the Minimum Requirements for the On-Line, Efficient and Robust Validation of Neutron Detector Operation and Monitoring of Neutron Noise Signals using Harmony Theory Networks

Abstract

On-line monitoring (OLM) of nuclear reactors (NRs) incorporatesamong other prioritiesthe concurrent verification of (i) valid operation of the NR neutron detectors (NDs) and (ii) soundness of the captured neutron noise (NN) signals (NSs) per se. In this piece of research, efficient, timely, directly reconfigurable and non-invasive OLM is implemented for providing swiftyet precisedecisions upon the (i) identities of malfunctioning NDs and(ii) locations of NR instability/unexpected operation. The use of Harmony Theory Networks (HTNs)is put forward to this end, with the results demonstrating the ability of these constraint-satisfaction artificial neural networks (ANNs) to identify(a) the smallest possible set of NDs which, configured into (b) the minimum number of 3-tuples of NDs operating on(c) the shortest NS time-window possible, instigate maximally efficient and accurate OLM. A proof-of-concept demonstration on the set of eight ex-core NDs and corresponding NSs of a simulated Pressurized Water nuclear Reactor (PWR) exhibits(i) significantly higher efficiency, at(ii) no detriment to localization accuracy, when employing only (iii) half of the original NDs and corresponding NSs, which are configured in (iv) a total of only two (out of the 56 combinatorially possible)3-tuples of NDs. Follow-up research shall investigate the scalability of the proposed methodology on the more extensive and homogeneous (i.e. "harder" in terms of ND/NS cardinality as well as of ranking/selection) dataset of the 36 in-core NSs of the same simulated NR.

Problem Decomposition and Information Minimization for the Global, Concurrent, On-line Validation of Neutron Noise Signals and Neutron Detector Operation

“…The aim of this piece of research is to identify the minimal set of in-core neutron detectors (in-NDs)and corresponding in-core neutron noise (NN) signals (in-NSs 2 )which, when configured into the minimum necessary number of in-ND/NS 3-tuples [1], constitutes a necessary as well as sufficient set of in-NDs/NSs for collectively, on-line monitoring (OLM) the nuclear reactor (NR) core, in terms of (I) valid operation of each in-ND and (II) "correctness" 3 of each corresponding in-NS.…”

“…A pilot investigation of the proposed methodology has been tested successfully [3] on the ex-core NS dataset of a pressurized water NR (PWR) [4] model [5] created for H2020 CORTEX [6]. The implementation employed the incremental/recursive application of the harmony theory artificial neural network architecture (HTN) [7] for the concurrent optimization of (I) and (II), as well as for the minimization of OLM time/space complexity, both of which have been accomplishedin the specific casevia the use of only (a) four (out of the total of eight, i.e.…”

“…This piece of research builds upon the general concept of [3], adapted toand demonstrated onthe corresponding in-core NN dataset of the same PWR model, thus further…”