We present an innovative architecture of a Rayleigh-based optical fibre sensor for the monitoring of water level and temperature inside storage nuclear fuel pools. This sensor, able to withstand the harsh constraints encountered under accidental conditions such as those pointed-out during the Fukushima-Daiichi event (temperature up to 100 degrees C and radiation dose level up to similar to 20 kGy), exploits the Optical Frequency Domain Reflectometry technique to remotely monitor a radiation resistant silica-based optical fibre i.e. its sensing probe. We validate the efficiency and the robustness of water level measurements, which are extrapolated from the temperature profile along the fibre length, in a dedicated test bench allowing the simulation of the environmental operating and accidental conditions. The conceived prototype ensures an easy, practical and no invasive integration into existing nuclear facilities. The obtained results represent a significant breakthrough and comfort the ability of the developed system to overcome both operating and accidental constraints providing the distributed profiles of the water level (0-to-5 m) and temperature (20-to-100 degrees C) with a resolution that in accidental condition is better than 3 cm and of similar to 0.5 degrees C respectively. These new sensors will be able, as safeguards, to contribute and reinforce the safety in existing and future nuclear power plants.

Rizzolo, S., Périsse, J., Boukenter, A., Ouerdane, Y., Marin, E., Macé, J., et al. (2017). Real time monitoring of water level and temperature in storage fuel pools through optical fibre sensors. SCIENTIFIC REPORTS, 7(1) [10.1038/s41598-017-08853-7].

Real time monitoring of water level and temperature in storage fuel pools through optical fibre sensors

RIZZOLO, Serena;CANNAS, Marco;
2017-01-01

Abstract

We present an innovative architecture of a Rayleigh-based optical fibre sensor for the monitoring of water level and temperature inside storage nuclear fuel pools. This sensor, able to withstand the harsh constraints encountered under accidental conditions such as those pointed-out during the Fukushima-Daiichi event (temperature up to 100 degrees C and radiation dose level up to similar to 20 kGy), exploits the Optical Frequency Domain Reflectometry technique to remotely monitor a radiation resistant silica-based optical fibre i.e. its sensing probe. We validate the efficiency and the robustness of water level measurements, which are extrapolated from the temperature profile along the fibre length, in a dedicated test bench allowing the simulation of the environmental operating and accidental conditions. The conceived prototype ensures an easy, practical and no invasive integration into existing nuclear facilities. The obtained results represent a significant breakthrough and comfort the ability of the developed system to overcome both operating and accidental constraints providing the distributed profiles of the water level (0-to-5 m) and temperature (20-to-100 degrees C) with a resolution that in accidental condition is better than 3 cm and of similar to 0.5 degrees C respectively. These new sensors will be able, as safeguards, to contribute and reinforce the safety in existing and future nuclear power plants.
2017
Settore FIS/01 - Fisica Sperimentale
Rizzolo, S., Périsse, J., Boukenter, A., Ouerdane, Y., Marin, E., Macé, J., et al. (2017). Real time monitoring of water level and temperature in storage fuel pools through optical fibre sensors. SCIENTIFIC REPORTS, 7(1) [10.1038/s41598-017-08853-7].
File in questo prodotto:
File Dimensione Formato  
SR17.pdf

accesso aperto

Descrizione: articolo principale
Tipologia: Versione Editoriale
Dimensione 3.78 MB
Formato Adobe PDF
3.78 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/240704
Citazioni
  • ???jsp.display-item.citation.pmc??? 6
  • Scopus 39
  • ???jsp.display-item.citation.isi??? 33
social impact