Developing a radiation field-based monitoring system for the transport and storage cask inventory during extended interim storage

High-level radioactive waste must be stored safely for a very long time but a suitable site for long-term storage is yet to be found. Additionally, in Germany the licence for transport and storage of casks is limited to 40 years, beginning at the time of emplacement and begins to expire for the first containers in the 2030s. To resolve the conflict between not having a final repository in time and the licence expiring, the licence must be extended while ensuring uninterrupted safe storage and safe transport. The DCS-Monitor II research project supports this process by investigating approaches to noninvasive, radiation field-based diagnostics that enable the observation of potential geometric changes of the cask inventory. Previous feasibility studies in the predecessor project DCS-Monitor I showed that cask monitoring using gamma radiation, neutron fields and cosmic muons is promising. In the ongoing research project presented here, the investigations on the qualification of radiation field-based diagnostics are extended via simulations. For muon imaging, a suitable procedure which solves the inverse problem to monitor the cask inventory is implemented. In addition, a partially automated gamma and neutron measurement system is being constructed and a muon detector is being developed and built. Both systems will be tested in field studies on large scale geometries and real containers.

Time-resolved secondary triton burnup 14 MeV neutron measurement by a new scintillating fiber detector in middle total neutron emission ranges in deuterium large helical device plasma experiments

A middle-sensitivity scintillating fiber detector (hereafter middle Sci-Fi detector) that works at a deuterium-tritium neutron flux of ~105-107 cm−2s−1 was utilized to measure secondary deuterium-tritium neutron emission rates with high temporal resolution at a total neutron emission rate of 1013 to 1015 n/s, where strong magnetohydrodynamic (MHD) instabilities were observed in the large helical device deuterium plasma experiments. The gain and angular characteristics of the middle Sci-Fi detector were evaluated in an accelerator-based deuterium-tritium neutron source in the intense 14 MeV neutron source facility at Osaka University. Observation of 1 MeV triton transport due to MHD instability was performed by a middle Sci-Fi detector whose deuterium-tritium neutron counting rate was approximately 20 times higher than that of the conventional Sci-Fi detector. Fusion-born triton transport due to energetic-particle-driven MHD instability was observed using the middle Sci-Fi detector due to its high detection efficiency and high discrimination ability of deuterium-tritium neutrons from the sea of deuterium-deuterium neutrons.

Application of artificial neural network in neutron/gamma pulse shape discrimination for EJ301 scintillation detector

The scintilator detectors are sensitive to both neutron and gamma radiation. Therefore, right identification of the pulses which generated by neutrons or gamma ray from these detectors plays an important role in neutron measurement by using scintilator detector. In order to improve the ability to pulse shape discrimination (PSD), many PSD techniques have been studied, developed and applied. In this work, we use a basic configuration of a Fully connected Neural network (Fc- Net) where the number of elements of the network is minimum, and each element corresponds to identified specification of neutron or gamma pulses measured by using EJ-301 scintilator detector. The minimum of error principle has been applied for neuron network design; therefore, the accuracy of recognitions did not affect by this reduced network. The obtained results show that the identify accuracy of FcNet is higher than those of digital charge integration (DCI) method. Being tested using 60Co radioactive source, it is shown that, with the application of the FcNet, the accuracy of the gamma pulses discrimination acquires 98.60% in the energy region from 50 to 2000 keV electron equivalent energy (keVee), and 95.59% in the energy region from 50 to 150 keVee. In general, the obtained results indicate that the artificial neural network method can be applied to build neutron/gamma spectrometers with limited hardware.

Studies of the fast ion confinement in the Large Helical Device by using neutron measurement and integrated codes

The neutral beam (NB) fast ion confinement in the Large Helical Device (LHD) is studied for several full field ( $B_{t}\sim 2.75~\text{T}$ ) magnetic configurations by a combination of neutron measurement and simulations. To investigate the NB fast ion confinement, we have performed a series of short-pulse NB injection experiments. The experiment results are analysed by the integrated code TASK3D-a. From this investigation, the effective particle diffusion coefficients of the tangential and perpendicular NBs are approximately $D^{\text{eff}}\sim 0.1~\text{m}^{2}~\text{s}^{-1}$ and $D^{\text{eff}}\sim 1~\text{m}^{2}~\text{s}^{-1}$ in the standard configuration. It is clarified that the NB fast ion confinement improves when the plasmas are shifted inward. Moreover, it is also found that the simulation, which considers the deuteron dilution effect due to the presence of impurity ions, can describe a neutron emission rate consistent with the measurement.

Error estimation for soil moisture measurements with cosmic-ray neutron sensing and implications for rover surveys

<p>The cosmic ray neutron (CRN) probe is a non-invasive device to measure soil moisture at the field scale. This instrument relies on the inverse correlation between aboveground epithermal neutron intensity (1eV – 100 keV) and environmental water content. The measurement uncertainty of the neutron detector follows Poisson statistics and thus decreases with decreasing neutron intensity, which corresponds to increasing soil moisture. In order to reduce measurement uncertainty (e.g. < 0.03 m<sup>3</sup>/m<sup>3</sup>), the neutron count rate is often aggregated over large time windows (e.g. 12h or 24h). To enable shorter aggregation intervals, the measurement uncertainty can be reduced either by using more efficient detectors or by using arrays of detectors, as in the case of CRN rover applications. Depending on soil moisture and driving speed, aggregation of neutron counts may also be necessary to obtain sufficiently accurate soil moisture estimates in rover applications. To date, signal aggregation has not been investigated sufficiently with respect to the optimisation of temporal (stationary probes) and spatial (roving applications) resolution. In this work, we present an easy-to-use method for uncertainty quantification of soil moisture observations from CRN sensors based on Gaussian error propagation theory. We have estimated the uncertainty using a third order Taylor expansion and compared the result with a more computationally intensive Monte Carlo approach and found excellent agreement. Furthermore, we used our method to quantify the dependence of soil moisture uncertainty on CRN rover survey design and on selected aggregation time. We anticipate that the new approach helps to quantify cosmic ray neutron measurement uncertainty. In particular, it is anticipated that the strategic planning and evaluation of CRN rover surveys based on uncertainty requirements can be improved considerably.</p>