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Author |
Tortajada, S.; Albiol, F.; Caballero, L.; Albiol, A.; Leganes-Nieto, J.L. |
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Title |
A portable geometry-independent tomographic system for gamma-ray, a next generation of nuclear waste characterization |
Type |
Journal Article |
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Year |
2023 |
Publication |
Scientific Reports |
Abbreviated Journal |
Sci Rep |
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Volume |
13 |
Issue |
1 |
Pages |
12284 - 10pp |
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Keywords |
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Abstract |
One of the main activities of the nuclear industry is the characterisation of radioactive waste based on the detection of gamma radiation. Large volumes of radioactive waste are classified according to their average activity, but often the radioactivity exceeds the maximum allowed by regulators in specific parts of the bulk. In addition, the detection of the radiation is currently based on static detection systems where the geometry of the bulk is fixed and well known. Furthermore, these systems are not portable and depend on the transport of waste to the places where the detection systems are located. However, there are situations where the geometry varies and where moving waste is complex. This is especially true in compromised situations.We present a new model for nuclear waste management based on a portable and geometry-independent tomographic system for three-dimensional image reconstruction for gamma radiation detection. The system relies on a combination of a gamma radiation camera and a visible camera that allows to visualise radioactivity using augmented reality and artificial computer vision techniques. This novel tomographic system has the potential to be a disruptive innovation in the nuclear industry for nuclear waste management. |
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Address |
[Tortajada, Salvador; Albiol, Francisco; Caballero, Luis] Univ Valencia, CSIC, Inst Fis Corpuscular, E-46980 Paterna Valencia, Spain, Email: s.tortajada@ific.uv.es |
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Nature Portfolio |
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English |
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ISSN |
2045-2322 |
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Conference |
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Notes |
WOS:001041587900052 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5612 |
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Author |
Muñoz, E.; Ros, A.; Borja-Lloret, M.; Barrio, J.; Dendooven, P.; Oliver, J.F.; Ozoemelam, I.; Roser, J.; Llosa, G. |
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Title |
Proton range verification with MACACO II Compton camera enhanced by a neural network for event selection |
Type |
Journal Article |
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Year |
2021 |
Publication |
Scientific Reports |
Abbreviated Journal |
Sci Rep |
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Volume |
11 |
Issue |
1 |
Pages |
9325 - 12pp |
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Keywords |
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Abstract |
The applicability extent of hadron therapy for tumor treatment is currently limited by the lack of reliable online monitoring techniques. An active topic of investigation is the research of monitoring systems based on the detection of secondary radiation produced during treatment. MACACO, a multi-layer Compton camera based on LaBr3 scintillator crystals and SiPMs, is being developed at IFIC-Valencia for this purpose. This work reports the results obtained from measurements of a 150 MeV proton beam impinging on a PMMA target. A neural network trained on Monte Carlo simulations is used for event selection, increasing the signal to background ratio before image reconstruction. Images of the measured prompt gamma distributions are reconstructed by means of a spectral reconstruction code, through which the 4.439 MeV spectral line is resolved. Images of the emission distribution at this energy are reconstructed, allowing calculation of the distal fall-off and identification of target displacements of 3 mm. |
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Address |
[Munoz, Enrique; Ros, Ana; Borja-Lloret, Marina; Barrio, John; Oliver, Josep F.; Roser, Jorge; Llosa, Gabriela] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, Valencia, Spain, Email: Enrique.Munoz@ific.uv.es |
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Publisher |
Nature Research |
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English |
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ISSN |
2045-2322 |
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Conference |
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Notes |
WOS:000651603500001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4836 |
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Author |
Khachatryan, M. et al, Coloma, P. |
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Title |
Electron-beam energy reconstruction for neutrino oscillation measurements |
Type |
Journal Article |
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Year |
2021 |
Publication |
Nature |
Abbreviated Journal |
Nature |
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Volume |
599 |
Issue |
7886 |
Pages |
565-570 |
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Keywords |
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Abstract |
Neutrinos exist in one of three types or 'flavours'-electron, muon and tau neutrinos-and oscillate from one flavour to another when propagating through space. This phenomena is one of the few that cannot be described using the standard model of particle physics (reviewed in ref. (1)), and so its experimental study can provide new insight into the nature of our Universe (reviewed in ref. (2)). Neutrinos oscillate as a function of their propagation distance (L) divided by their energy (E). Therefore, experiments extract oscillation parameters by measuring their energy distribution at different locations. As accelerator-based oscillation experiments cannot directly measure E, the interpretation of these experiments relies heavily on phenomenological models of neutrino-nucleus interactions to infer E. Here we exploit the similarity of electron-nucleus and neutrino-nucleus interactions, and use electron scattering data with known beam energies to test energy reconstruction methods and interaction models. We find that even in simple interactions where no pions are detected, only a small fraction of events reconstruct to the correct incident energy. More importantly, widely used interaction models reproduce the reconstructed energy distribution only qualitatively and the quality of the reproduction varies strongly with beam energy. This shows both the need and the pathway to improve current models to meet the requirements of next-generation, high-precision experiments such as Hyper-Kamiokande (Japan)(3) and DUNE (USA)(4). Electron scattering measurements are shown to reproduce only qualitatively state-of-the-art lepton-nucleus energy reconstruction models, indicating that improvements to these particle-interaction models are required to ensure the accuracy of future high-precision neutrino oscillation experiments. |
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Address |
[Khachatryan, M.; Hauenstein, F.; Weinstein, L. B.] Old Domin Univ, Norfolk, VA USA, Email: adishka@mit.edu |
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Corporate Author |
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Publisher |
Nature Portfolio |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0028-0836 |
ISBN |
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Conference |
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Notes |
WOS:000722366200013 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5073 |
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Author |
Wilson, J.N. et al; Algora, A. |
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Title |
Angular momentum generation in nuclear fission |
Type |
Journal Article |
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Year |
2021 |
Publication |
Nature |
Abbreviated Journal |
Nature |
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Volume |
590 |
Issue |
7847 |
Pages |
566-570 |
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Keywords |
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Abstract |
When a heavy atomic nucleus splits (fission), the resulting fragments are observed to emerge spinning(1); this phenomenon has been a mystery in nuclear physics for over 40 years(2,3). The internal generation of typically six or seven units of angular momentum in each fragment is particularly puzzling for systems that start with zero, or almost zero, spin. There are currently no experimental observations that enable decisive discrimination between the many competing theories for the mechanism that generates the angular momentum(4-12). Nevertheless, the consensus is that excitation of collective vibrational modes generates the intrinsic spin before the nucleus splits (pre-scission). Here we show that there is no significant correlation between the spins of the fragment partners, which leads us to conclude that angular momentum in fission is actually generated after the nucleus splits (post-scission). We present comprehensive data showing that the average spin is strongly mass-dependent, varying in saw-tooth distributions. We observe no notable dependence of fragment spin on the mass or charge of the partner nucleus, confirming the uncorrelated post-scission nature of the spin mechanism. To explain these observations, we propose that the collective motion of nucleons in the ruptured neck of the fissioning system generates two independent torques, analogous to the snapping of an elastic band. A parameterization based on occupation of angular momentum states according to statistical theory describes the full range of experimental data well. This insight into the role of spin in nuclear fission is not only important for the fundamental understanding and theoretical description of fission, but also has consequences for the gamma-ray heating problem in nuclear reactors(13,14), for the study of the structure of neutron-rich isotopes(15,16), and for the synthesis and stability of super-heavy elements(17,18). gamma-ray spectroscopy experiments on the origin of spin in the products of nuclear fission of spin-zero nuclei suggest that the fission fragments acquire their spin after scission, rather than before. |
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Address |
[Wilson, J. N.; Thisse, D.; Lebois, M.; Jovancevic, N.; Adsley, P.; Babo, M.; Chakma, R.; Delafosse, C.; Haefner, G.; Hauschild, K.; Ibrahim, F.; Ljungvall, J.; Lopez-Martens, A.; Lozeva, R.; Matea, I; Nemer, J.; Popovitch, Y.; Qi, L.; Tocabens, G.; Verney, D.] Univ Paris Saclay, IJC Lab, CNRS, IN2P3, Orsay, France, Email: jonathan.wilson@ijclab.in2p3.fr |
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Publisher |
Nature Research |
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English |
Summary Language |
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ISSN |
0028-0836 |
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Conference |
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Notes |
WOS:000621583600006 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4717 |
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Author |
Conde, D.; Castillo, F.L.; Escobar, C.; García, C.; Garcia Navarro, J.E.; Sanz, V.; Zaldívar, B.; Curto, J.J.; Marsal, S.; Torta, J.M. |
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Title |
Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning |
Type |
Journal Article |
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Year |
2023 |
Publication |
Space Weather |
Abbreviated Journal |
Space Weather |
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Volume |
21 |
Issue |
11 |
Pages |
e2023SW003474 - 27pp |
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Keywords |
geomagnetic storms; deep learning; forecasting; SYM-H; uncertainties; hyper-parameter optimization |
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Abstract |
Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high-latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground-based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non-linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine-learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM-H index characterizing geomagnetic storms multiple-hour ahead, using public interplanetary magnetic field (IMF) data from the Sun-Earth L1 Lagrange point and SYM-H data. We implement a type of machine-learning model called long short-term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep-learning model in the context of forecasting the SYM-H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper-parameters of the LSTM network and robustness tests. |
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Address |
[Conde, D.; Escobar, C.; Garcia, C.; Garcia, J. E.; Sanz, V.; Zaldivar, B.] Univ Valencia, CSIC, Ctr Mixto, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: Daniel.Conde@ific.uv.es |
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Publisher |
Amer Geophysical Union |
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English |
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Notes |
WOS:001104189700001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5804 |
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