Development of Optical Sensors Based on Neutral Red Absorbance for Real-Time pH Measurements.

Measuring pH with an optical sensor requires the immobilization of a chemical recognition phase on a solid surface. Neutral red (NR), an acid base indicator was used to develop two different optical probe configurations. The chemistry of aryl diazonium salts was chosen for the elaboration of this chemical phase, as it enables strong covalent bonds to be established on the surface of metallized glass or metallic surfaces. It also allows the formation of a thick film required to obtain an exploitable spectral response. The surfaces of interest (metallized optical fiber and 316 L stainless-steel mirror) are modelized by flat surfaces (metallized glass plates and 316 L stainless-steel plates). The analytical characterizations carried out (IR, XPS, UV-Visible, and profilometry) show that NR was covalently grafted onto the model surfaces as well as on the surfaces of interest. The supports grafted with NR to develop optical pH probes exhibit spectral changes, particularly the values of pKa, the pH range, and the isosbestic point wavelength. The experimental results show that the optical probe can be used for pH measurements between 4 and 8.

Hybrid Twins Modeling of a High-Level Radioactive Waste Cell Demonstrator for Long-Term Temperature Monitoring and Forecasting.

Monitoring a deep geological repository for radioactive waste during the operational phases relies on a combination of fit-for-purpose numerical simulations and online sensor measurements, both producing complementary massive data, which can then be compared to predict reliable and integrated information (e.g., in a digital twin) reflecting the actual physical evolution of the installation over the long term (i.e., a century), the ultimate objective being to assess that the repository components/processes are effectively following the expected trajectory towards the closure phase. Data prediction involves using historical data and statistical methods to forecast future outcomes, but it faces challenges such as data quality issues, the complexity of real-world data, and the difficulty in balancing model complexity. Feature selection, overfitting, and the interpretability of complex models further contribute to the complexity. Data reconciliation involves aligning model with in situ data, but a major challenge is to create models capturing all the complexity of the real world, encompassing dynamic variables, as well as the residual and complex near-field effects on measurements (e.g., sensors coupling). This difficulty can result in residual discrepancies between simulated and real data, highlighting the challenge of accurately estimating real-world intricacies within predictive models during the reconciliation process. The paper delves into these challenges for complex and instrumented systems (multi-scale, multi-physics, and multi-media), discussing practical applications of machine and deep learning methods in the case study of thermal loading monitoring of a high-level waste (HLW) cell demonstrator (called ALC1605) implemented at Andra's underground research laboratory.

Measurement of the birefringence variation induced by dihydrogen diffusion into a polarization-maintaining fiber.

We report continuous measurements of the transmission spectrum of a fiber loop mirror interferometer composed of a Panda-type polarization-maintaining (PM) optical fiber during the diffusion of dihydrogen (H2) gas into the fiber. Birefringence variation is measured through the wavelength shift of the interferometer spectrum when the PM fiber is inserted into a gas chamber with H2 concentration from 1.5 to 3.5 vol.% at 75 bar and 70°C. The measurements correlated with simulation results of H2 diffusion into the fiber lead to a birefringence variation of -4.25 × 10-8 per mol m-3 of H2 concentration in the fiber, with a birefringence variation as low as -9.9×10-8 induced by 0.031 µmol m-1 of H2 dissolved in the single-mode silica fiber (for 1.5 vol.%). These results highlight a modification of the strain distribution in the PM fiber, induced by H2 diffusion, leading to a variation of the birefringence that could deteriorate the performances of fiber devices or improve H2 gas sensors.

Performance Assessment of Distributed Strain Sensing Techniques for Convergence Monitoring of Radioactive Waste Repository.

This paper presents the measurement methodology of diameter reduction monitoring of micro-tunnel structures used for radioactive waste storage based on distributed strain measurements along fiber optic sensors installed on the circumference. The whole measurement procedure is described: the calibration of the sensors for use in harsh environment (temperature and radioactivity), the measurement analysis technique, the performance assessment of different measurement systems on a surface mock-up and the in-situ validation on an underground structure. The performances of Brillouin and Rayleigh backscattering measurements are compared, as well as different fixation technologies. Distributed measurements are compared to alternative measurements: displacement sensors, Bragg grating extensometers and MEMS accelerometers. The distributed Rayleigh backscattering measurement performed on optical cables bonded to the surface of the structure appears to be the best solution for monitoring the convergence of micro-tunnels and offers comparable performance to alternative technologies tested on the surface demonstrator.

Raman lidar for hydrogen gas concentration monitoring and future radioactive waste management.

A multi-channel Raman lidar has been developed, allowing for the first time simultaneous and high-resolution profiling of hydrogen gas and water vapor. The lidar measures vibrational Raman scattering in the UV (355 nm) domain. It works in a high-bandwidth photon counting regime using fast SiPM detectors and takes into account the spectral overlap between hydrogen and water vapor Raman spectra. Measurement of concentration profiles of H2 and H2O are demonstrated along a 5-meter-long open gas cell with 1-meter resolution at 85 meters. The instrument precision is investigated by numerical simulation to anticipate the potential performance at longer range. This lidar could find applications in the French project Cigéo for monitoring radioactive waste disposal cells.

A Multi-Parametric Device with Innovative Solid Electrodes for Long-Term Monitoring of pH, Redox-Potential and Conductivity in a Nuclear Waste Repository.

We present an innovative electrochemical probe for the monitoring of pH, redox potential and conductivity in near-field rocks of deep geological radioactive waste repositories. The probe is composed of a monocrystalline antimony electrode for pH sensing, four AgCl/Ag-based reference or Cl- selective electrodes, one Ag2S/Ag-based reference or S2- selective electrode, as well as four platinum electrodes, a gold electrode and a glassy-carbon electrode for redox potential measurements. Galvanostatic electrochemistry impedance spectroscopy using AgCl/Ag-based and platinum electrodes measure conductivity. The use of such a multi-parameter probe provides redundant information, based as it is on the simultaneous behaviour under identical conditions of different electrodes of the same material, as well as on that of electrodes made of different materials. This identifies the changes in physical and chemical parameters in a solution, as well as the redox reactions controlling the measured potential, both in the solution and/or at the electrode/solution interface. Understanding the electrochemical behaviour of selected materials thus is a key point of our research, as provides the basis for constructing the abacuses needed for developing robust and reliable field sensors.

France's State of the Art Distributed Optical Fibre Sensors Qualified for the Monitoring of the French Underground Repository for High Level and Intermediate Level Long Lived Radioactive Wastes.

This paper presents the state of the art distributed sensing systems, based on optical fibres, developed and qualified for the French Cigéo project, the underground repository for high level and intermediate level long-lived radioactive wastes. Four main parameters, namely strain, temperature, radiation and hydrogen concentration are currently investigated by optical fibre sensors, as well as the tolerances of selected technologies to the unique constraints of the Cigéo's severe environment. Using fluorine-doped silica optical fibre surrounded by a carbon layer and polyimide coating, it is possible to exploit its Raman, Brillouin and Rayleigh scattering signatures to achieve the distributed sensing of the temperature and the strain inside the repository cells of radioactive wastes. Regarding the dose measurement, promising solutions are proposed based on Radiation Induced Attenuation (RIA) responses of sensitive fibres such as the P-doped ones. While for hydrogen measurements, the potential of specialty optical fibres with Pd particles embedded in their silica matrix is currently studied for this gas monitoring through its impact on the fibre Brillouin signature evolution.

High γ-ray dose radiation effects on the performances of Brillouin scattering based optical fiber sensors.

The use of distributed strain and temperature in optical fiber sensors based on Brillouin scattering for the monitoring of nuclear waste repository requires investigation of their performance changes under irradiation. For this purpose, we irradiated various fiber types at high gamma doses which represented the harsh environment constraints associated with the considered application. Radiation leads to two phenomena impacting the Brillouin scattering: 1) decreasing in the fiber linear transmission through the radiation-induced attenuation (RIA) phenomenon which impacts distance range and 2) modifying the Brillouin scattering properties, both intrinsic frequency position of Brillouin loss and its dependence on strain and temperature. We then examined the dose dependence of these radiation-induced changes in the 1 to 10 MGy dose range, showing that the responses strongly depend on the fiber composition. We characterized the radiation effects on strain and temperature coefficients, dependencies of the Brillouin frequency, providing evidence for a strong robustness of these intrinsic properties against radiations. From our results, Fluorine-doped fibers appear to be very promising candidates for temperature and strain sensing through Brillouin-based sensors in high gamma-ray dose radiative environments.