scholarly journals Neutron Flux Monitoring Based on Blind Source Separation Algorithms in Moroccan TRIGA MARK II Reactor

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Hanane Arahmane ◽  
El-Mehdi Hamzaoui ◽  
Rajaa Cherkaoui El Moursli

We present an overview of fission chamber’s functioning modes, theoretical aspects of the nonnegative matrix factorization methods, and the opportunities that offer neutron data processing in order to achieve neutron flux monitoring tasks. Indeed, it is a part of research project that aimed at applying Blind Source Separation methods for in-core and ex-core neutron flux monitoring while analyzing the outputs of fission chamber. The latter could be used as a key issue for control, fuel management, safety concerns, and material irradiation experiments. The Blind Source Separation methods had been used in many scientific fields such as biomedical engineering and telecommunications. Recently, they were used for gamma spectrometry data processing. The originality of this research work is to apply these powerful methods to process the fission chamber output signals. We illustrated the effectiveness of this tool using simulated fission chamber signals.

2018 ◽  
Vol 170 ◽  
pp. 03002
Author(s):  
G. Galli ◽  
H. Hamrita ◽  
C. Jammes ◽  
M.J. Kirkpatrick ◽  
E. Odic ◽  
...  

During the operation of the Superphenix and Phenix reactors, an aberrant electrical signal was detected from the fission chambers used for neutron flux monitoring. This signal, thought to be due to partial electrical discharge (PD) is similar to the signal resulting from neutron interactions, and is generated in fission chambers at temperatures above 400 °C. This paper reports work on the characterization and localization of the source of this electrical signal in a High Temperature Fission Chamber (HTFC). The relation between the shape of the PD signal and various parameters (nature and pressure of the chamber filling gas, electrode gap distance, and fission chamber geometry) are first described. Next, experiments designed to identify the location within the chambers where the PD are being generated are presented. After verification and refinement of the results of these localization studies, it should be possible to propose changes to the fission chamber in order to reduce or eliminate the PD signal.


2004 ◽  
Vol 47 (1) ◽  
pp. 36-38
Author(s):  
S. S. Parzhitskii ◽  
A. P. Kobzev ◽  
Yu. P. Popov ◽  
N. A. Gundorin ◽  
I. A. Oprya ◽  
...  

Author(s):  
Luigi Lepore ◽  
Romolo Remetti ◽  
Mauro Cappelli

Although Sodium Fast Reactors (SFRs) are the most investigated solutions for the future fast-flux facilities so far, Lead Fast Reactors (LFRs) promise to be a very competitive alternative thanks to their peculiarity concerning coolant-safety, fuel cycle and waste management. Nevertheless, the development of LFRs presents today some drawbacks still to be solved. Due to the harder neutron flux, the current instrumentation developed for SFRs is likely to be extended to LFRs as a first attempt. Otherwise, new monitoring instrumentation could be developed in order to assure more tailored results. Different measurement technologies can be considered for fast flux monitoring and flux absolute measurements in order to provide a reliable and quick calibration of the overall reactor neutron instrumentation. The goal of this paper is to study the validity of typical fast reactor fission chamber designs (e.g. SuperPhénix fission chambers), indicating which are the limitations when used in a LFR environment. Afterwards, alternative detector solutions with enhanced sensitivity and response will be proposed.


2008 ◽  
Vol 2008 ◽  
pp. 1-10 ◽  
Author(s):  
Junying Zhang ◽  
Le Wei ◽  
Xuerong Feng ◽  
Zhen Ma ◽  
Yue Wang

Independent component analysis (ICA) is a widely applicable and effective approach in blind source separation (BSS), with limitations that sources are statistically independent. However, more common situation is blind source separation for nonnegative linear model (NNLM) where the observations are nonnegative linear combinations of nonnegative sources, and the sources may be statistically dependent. We propose a pattern expression nonnegative matrix factorization (PE-NMF) approach from the view point of using basis vectors most effectively to express patterns. Two regularization or penalty terms are introduced to be added to the original loss function of a standard nonnegative matrix factorization (NMF) for effective expression of patterns with basis vectors in the PE-NMF. Learning algorithm is presented, and the convergence of the algorithm is proved theoretically. Three illustrative examples on blind source separation including heterogeneity correction for gene microarray data indicate that the sources can be successfully recovered with the proposed PE-NMF when the two parameters can be suitably chosen from prior knowledge of the problem.


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