| 1. |
- al-Dbissi, Moad, 1994, et al.
(författare)
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Conceptual design and initial evaluation of a neutron flux gradient detector
- 2022
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Ingår i: Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. - : Elsevier BV. - 0168-9002. ; 1026
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Tidskriftsartikel (refereegranskat)abstract
- Identification of the position of a localized neutron source, or that of local inhomogeneities in a multiplying or scattering medium (such as the presence of small, strong absorbers) is possible by measurement of the neutron flux in several spatial points, and applying an unfolding procedure. It was suggested earlier, and it was confirmed by both simulations and pilot measurements, that if, in addition to the usually measured scalar (angularly integrated) flux, the neutron current vector or its diffusion approximation (the flux gradient vector) is also considered, the efficiency and accuracy of the unfolding procedure is significantly enhanced. Therefore, in support of a recently started project, whose goal is to detect missing (replaced) fuel pins in a spent fuel assembly by non-intrusive methods, this idea is followed up. The development and use of a dedicated neutron detector for within-assembly measurements of the neutron scalar flux and its gradient are planned. The detector design is based on four small, fiber-mounted scintillation detector tips, arranged in a rectangular pattern. Such a detector is capable of measuring the two Cartesian components of the flux gradient vector in the horizontal plane. This paper presents an initial evaluation of the detector design, through Monte Carlo simulations in a hypothetical scenario.
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| 2. |
- al-Dbissi, Moad, 1994, et al.
(författare)
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Identification of diversions in spent PWR fuel assemblies by PDET signatures using Artificial Neural Networks (ANNs)
- 2023
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Ingår i: Annals of Nuclear Energy. - 0306-4549 .- 1873-2100. ; 193
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Tidskriftsartikel (refereegranskat)abstract
- Spent nuclear fuel represents the majority of materials placed under nuclear safeguards today and it requires to be inspected and verified regularly to promptly detect any illegal diversion. Research is ongoing both on the development of non-destructive assay instruments and methods for data analysis in order to enhance the verification accuracy and reduce the inspection time. In this paper, two models based on Artificial Neural Networks (ANNs) are studied to process measurements from the Partial Defect Tester (PDET) in spent fuel assemblies of Pressurized Water Reactors (PWRs), and thus to identify at different levels of detail whether nuclear fuel has been replaced with dummy pins or not. The first model provides an estimation of the percentage of replaced fuel pins within the inspected fuel assembly, while the second model determines the exact configuration of the replaced fuel pins. The two models are trained and tested using a dataset of Monte-Carlo simulated PDET responses for intact spent PWR fuel assemblies and a variety of hypothetical diversion scenarios. The first model classifies fuel assemblies according to the percentage of diverted fuel with a high accuracy (96.5%). The second model reconstructs the correct configuration for 57.5% of the fuel assemblies available in the dataset and still retrieves meaningful information of the diversion pattern in many of the misclassified cases.
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| 3. |
- al-Dbissi, Moad, 1994, et al.
(författare)
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On the use of neutron flux gradient with ANNs for the detection of diverted spent nuclear fuel
- 2024
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Ingår i: Annals of Nuclear Energy. - 0306-4549 .- 1873-2100. ; 204
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Tidskriftsartikel (refereegranskat)abstract
- One of the main tasks in nuclear safeguards is regular inspections of Spent Nuclear Fuel (SNF) assemblies to detect possible diversions of special nuclear material such as 235U and 239Pu. In these inspections, characteristic signatures of SNF such as emissions of neutrons and gamma rays from the radioactive decay, are measured and their consistency with the declared assemblies is verified to ensure that no fuel pins have been removed. Research in this field is focused on both the development of detection equipment and methods for the analysis of the acquired measurement data. In this paper, the use of the neutron flux gradient, which is not considered in regular SNF verification, is investigated in combination with the scalar neutron flux as input to artificial neural network models for the quantification of fuel pins in SNF assemblies. The training and testing of these ANN models rely on a synthetic dataset that is generated from Monte Carlo simulations of a typical intact pressurized water reactor assembly and with different patterns of fuel pins replaced by dummy pins. The dataset consists of unique scenarios so that the ANN can be assessed over “unknown” cases that are not part of the learning phase. Results show that the neutron flux gradient is advantageous for a more accurate reconstruction of diversions within SNF assemblies.
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| 4. |
- Demaziere, Christophe, 1973, et al.
(författare)
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Development and test of a novel neutronic verification scheme for Molten Salt Reactors
- 2021
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Ingår i: Transactions of the American Nuclear Society. - 0003-018X. ; 124:1, s. 504-507
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Konferensbidrag (refereegranskat)abstract
- This paper presents the extension of a verification method of transient neutron transport solvers earlier developed to the case of Molten Salt Reactor (MSR). This method is based on the extraction of the point-kinetic response of a nuclear reactor excited by a mono-chromatic perturbation and on its subsequent comparison with a closed analytical form. Whereas a closed analytical form exists for systems with fixed fuel, no closed analytical form exists in the case of MSR, as highlighted by many authors. A workaround is nevertheless proposed in this work, thus giving the possibility to use a similar verification method to the case of MSR.
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| 5. |
- Demaziere, Christophe, 1973, et al.
(författare)
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Development and test of a novel verification scheme applied to the neutronic modelling of Molten Salt Reactors
- 2022
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Ingår i: Annals of Nuclear Energy. - : Elsevier BV. - 0306-4549 .- 1873-2100. ; 167
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents the extension of a method to verify transient neutron transport solvers earlier developed for reactors with non-moving fuel, to the case of Molten Salt Reactors (MSRs). This method is based on the extraction of the point-kinetic response of a nuclear reactor excited by a mono-chromatic perturbation and on its subsequent comparison with its expected functional dependence. Whereas a simple expression for this dependence exists for systems with fixed fuel, this is not the case for MSRs, as highlighted in many past studies. A workaround is nevertheless proposed in this work, thus giving the possibility to use a similar verification method to the case of MSRs. The method is applied to a simple dynamic MSR solver, demonstrating the capabilities of the technique. Contrary to other verification methods for which the system has to be simplified so that analytical solutions can be derived, the present method can be applied to any heterogeneous system.
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| 6. |
- Demaziere, Christophe, 1973, et al.
(författare)
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Monte Carlo-based dynamic calculations of stationary perturbations
- 2020
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Ingår i: International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future, PHYSOR 2020. - : EDP Sciences. ; 2020-March
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Konferensbidrag (refereegranskat)abstract
- Capitalizing on some earlier work, this paper presents a novel Monte Carlo-based approach that allows estimating the neutron noise induced by stationary perturbations of macroscopic cross-sections in the frequency domain. This method relies on the prior computation using Monte Carlo of modified Green’s functions associated to the real part of the dynamic macroscopic cross-sections, mimicking equivalent subcritical problems driven by external neutron sources. Once such modified Green’s functions are estimated, the neutron noise induced by any type of perturbations can be recovered, by solving a linear algebra problem accounting for the interdependence between the real and imaginary parts of the governing balance equations. The newly derived method was demonstrated on a large homogeneous test system and on a small heterogeneous test system to provide results comparable to a diffusion-based solver specifically developed for neutron noise applications. The new method requires the specification by the user of the real part of the Fourier transform of the macroscopic cross-sections. This is accomplished using ACE-formatted cross-section files defined by the user. Beyond this input data preparation, no change to the Monte Carlo source code is necessary. This represents the main advantage of the proposed method as compared to similar efforts requiring extensive modifications to the Monte Carlo source code.
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| 7. |
- Demaziere, Christophe, 1973, et al.
(författare)
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Neutron noise-based anomaly classification and localization using machine learning
- 2020
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Ingår i: International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future, PHYSOR 2020. - : EDP Sciences. ; 2020-March, s. 2913-2921
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Konferensbidrag (refereegranskat)abstract
- A methodology is proposed in this paper allowing the classification of anomalies and subsequently their possible localization in nuclear reactor cores during operation. The method relies on the monitoring of the neutron noise recorded by in-core neutron detectors located at very few discrete locations throughout the core. In order to unfold from the detectors readings the necessary information, a 3-dimensional Convolutional Neural Network is used, with the training and validation of the network based on simulated data. In the reported work, the approach was also tested on simulated data. The simulations were carried out in the frequency domain using the CORE SIM+ diffusion-based two-group core simulator. The different scenarios correspond to the following cases: a generic “absorber of variable strength”, axially travelling perturbations at the velocity of the coolant flow (due to e.g. fluctuations of the coolant temperature at the inlet of the core), fuel assembly vibrations, control rod vibrations, and core barrel vibrations. In all those cases, various frequencies were considered and, when relevant, different locations of the perturbations and different vibration modes were taken into account. The machine learning approach was able to correctly identify the different scenarios with a maximum error of 0.11%. Moreover, the error in localizing anomalies had a mean squared error of 0.3072 in mesh size, corresponding to less than 4 cm. The proposed methodology was also demonstrated to be insensitive to parasitic noise and will be tested on actual plant data in the near future.
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| 8. |
- Durrant, A., et al.
(författare)
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Detection and localisation of multiple in-core perturbations with neutron noise-based self-supervised domain adaptation
- 2021
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Ingår i: Proc. Int. Conf. Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C2021). - 9781713886310
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Konferensbidrag (refereegranskat)abstract
- The use of non-intrusive techniques for monitoring nuclear reactors is becoming more vital as western fleets age. As a consequence, the necessity to detect more frequently occurring operational anomalies is of upmost interest. Here, noise diagnostics — the analysis of small stationary deviations of local neutron flux around its time-averaged value — is employed aiming to unfold from detector readings the nature and location of driving perturbations. Given that in-core instrumentation of western-type light-water reactors are scarce in number of detectors, rendering formal inversion of the reactor transfer function impossible, we propose to utilise advancements in Machine Learning and Deep Learning for the task of unfolding. This work presents an approach to such a task doing so in the presence of multiple and simultaneously occurring perturbations or anomalies. A voxel-wise semantic segmentation network is proposed to determine the nature and source location of multiple and simultaneously occurring perturbations in the frequency domain. A diffusion-based core simulation tool has been employed to provide simulated training data for two reactors. Additionally, we work towards the application of the aforementioned approach to real measurements, introducing a self-supervised domain adaptation procedure to align the representation distributions of simulated and real plant measurements.
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| 9. |
- Herb, Joachim, et al.
(författare)
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Sensitivity analysis in core diagnostics
- 2022
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Ingår i: Annals of Nuclear Energy. - : Elsevier BV. - 0306-4549 .- 1873-2100. ; 178
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Tidskriftsartikel (refereegranskat)abstract
- In the CORTEX project, methods to simulate neutron flux oscillations were enhanced and machine-learning based tools to determine the causes of measured neutron flux oscillations were developed, using the results of simulations as training and validation data. For a selected combination of those methods and tools, several sensitivity analyses were performed to assess their robustness and trustworthiness. The neutron flux oscillations were simulated using the tool CORE SIM+. It calculates the three-dimensional field of the neutron flux oscillations, which can be used to determine the response of neutron detectors at given locations. For the sensitivity analysis, the neutron flux oscillations were assumed to be caused by the vibration of one fuel element. It was investigated how selected input parameters like the core loading pattern, the burn up of the fuel elements, the neutronic core data, the geometry details of the vibrating fuel element, the chosen detectors, and other noise source parameters like the amplitude of the fuel element vibrations, affect the simulated neutron flux oscillations. A three dimensional fully convolutional neural network had been developed and trained during the CORTEX project to determine the cause and location of perturbations causing given measurements of in-core detectors in pressurized water reactors. The robustness of this network was tested by applying it to the simulated detector readings created during the sensitivity analysis.
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| 10. |
- Hursin, Mathieu, et al.
(författare)
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Modeling noise experiments performed at AKR-2 and CROCUS zero-power reactors
- 2023
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Ingår i: Annals of Nuclear Energy. - 0306-4549 .- 1873-2100. ; 194
-
Tidskriftsartikel (refereegranskat)abstract
- CORTEX is a EU H2020 project (2017-2021) devoted to the analysis of ’reactor neutron noise’ in nuclear reactors, i.e. the small fluctuations occurring around the stationary state due to external or internal disturbances in the core. One important aspect of CORTEX is the development of neutron noise simulation codes capable of modeling the spatial variations of the noise distribution in a reactor. In this paper we illustrate the validation activities concerning the comparison of the simulation results obtained by several noise simulation codes with respect to experimental data produced at the zero-power reactors AKR-2 (operated at TUD, Germany) and CROCUS (operated at EPFL, Switzerland). Both research reactors are modeled in the time and frequency domains, using transport or diffusion theory. Overall, the noise simulators managed to capture the main features of the neutron noise behavior observed in the experimental campaigns carried out in CROCUS and AKR-2, even though computational biases exist close to the region where the noise-inducing mechanical vibration was located (the so-called ”noise source”). In some of the experiments, it was possible to observe the spatial variation of the relative neutron noise, even relatively far from the noise source. This was achieved through reduced uncertainties using long measurements, the installation of numerous, robust and efficient detectors at a variety of positions in the near vicinity or inside the core, as well as new post-processing methods. For the numerical simulation tools, modeling the spatial variations of the neutron noise behavior in zero-power research reactors is an extremely challenging problem, because of the small magnitude of the noise field; and because deviations from a point-kinetics behavior are most visible in portions of the core that are especially difficult to be precisely represented by simulation codes, such as experimental channels. Nonetheless the limitations of the simulation tools reported in the paper were not an issue for the CORTEX project, as most of the computational biases are found close to the noise source.
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