Muon Scattering Radiography (MSR) measurements on blocks of ice in laboratory, and on simulated snowpack
Creators
- 1. Muon Tomography Systems S.L - Bilbao, Spain
- 2. Centre d'Etudes Spatiales de la Biosphère (CESBIO) - Université de Toulouse, CNRS/CNES/IRD/INRA/UPS - Toulouse, France
- 3. Instituto de Fı́sica de Cantabria (IFCA) - Universidad de Cantabria - Santander, Spain
Description
Experimental setup (scenario 5):
Muon data used in this work has been collected with our muon detection system. This muon monitoring system is currently in use for both scientific and industrial purposes (Martínez-Ruiz del Árbol et al., 2022). The particle detectors are composed of four Multi-Wire Proportional Chambers (MWPC) and each chamber has two layers with 224 detection wires, all of them separated by 4 mm. The two layers form a two-dimensional grid of wires which covers an area of 89.6 x 89.6 cm and detects the positions where muons cross it.
When a muon event is identified, our system detects four points located in the horizontal two-dimensional grids, two points before the particle goes through the target and another two points after the particle traverses it. With this data, way-in and way-out trajectories can be reconstructed, and muon deviations calculated. Specifically, in the numerical analysis of this work, we utilised the projection of muon deviations in two planes perpendicular to the detection wires.
Simulation setup (scenarios 1 to 4):
The snowpack was simulated using a one-dimensional snow model forced by surface meteorological data. We have used the SNOWPACK model (Bartelt & Lehning, 2002) to realistically simulate the behaviour of the snowpack along two seasons, 2015/2016 (1_Modelling) and 2016/2017 (2_Testing). SNOWPACK was forced by the ERA5-Land surface reanalysis (Muñoz-Sabater et al., 2021). The simulations were performed in the Pyrenees, using the ERA5-Land cell whose centroid falls closer to the Monte Perdido massif (42.7°N, -0.1°E), at an elevation of 2041m asl.
We coupled the SNOWPACK simulations with a full MSR simulation setup that uses the Cosmic RaY generator (Hagmann et al., 2012) to reproduce the atmosphere muon flux and GEANT4 (Agostinelli et al., 2003) to simulate the muon scattering caused by the snowpack. GEANT4 is a state-of-the-art software designed and maintained at CERN to simulate the interactions of particles and matter in high-energy and nuclear physics. Our simulation framework contains a model of our experimental setup including the muon detectors and their response. This framework has been successfully applied to multiple industrial problems, for instance, to steel-made pipe wear (Martínez-Ruiz del Árbol et al., 2018). Similar simulation frameworks are typically used to research applications of muography (Mori et al., 2017).
We expanded the one-dimensional snowpack geometry to a 1m² snow column, assuming homogeneous snow layers in the longitude and latitude dimensions. Then, we propagated and measured muons penetrating the whole snow column, virtually reproducing the detection process using GEANT4. We collected muon deviations and their Root-mean-square (RMS) value for different accumulations of snow during the two simulated seasons.
Files
1_Modelling.zip
Additional details
References
- Agostinelli, S., Allison, J., Amako, K., Apostolakis, J., Araujo, H., Arce, P., Asai, M., Axen, D., Banerjee, S., Barrand, G., Behner, F., Bellagamba, L., Boudreau, J., Broglia, L., Brunengo, A., Burkhardt, H., Chauvie, S., Chuma, J., Chytracek, R., … Zschiesche, D. (2003). GEANT4—A simulation toolkit. Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 506(3), 250-303. https://doi.org/10.1016/S0168-9002(03)01368-8
- Bartelt, P., & Lehning, M. (2002). A physical SNOWPACK model for the Swiss avalanche warning Part I: Numerical model. Cold Regions Science and Technology, 35(3). https://doi.org/10.1016/S0165-232X(02)00074-5
- Hagmann, C., Lange, D., & Wright, D. (2012). Cosmic-ray shower generator (CRY) for Monte Carlo transport codes. 2007 IEEE Nuclear Science Symposium Conference Record. https://doi.org/10.1109/NSSMIC.2007.4437209
- Martínez-Ruiz del Árbol, P., Gómez-García, P., Díez-González, C. D., & Orio-Alonso, A. (2018). Non-destructive testing of industrial equipment using muon radiography. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 377(2137). https://doi.org/10.1098/rsta.2018.0054
- Martínez-Ruiz del Árbol, P., Orio-Alonso, A., Díez-González, C., & Gómez-Garcıa, P. (2022). Applications of Muography to the Industrial Sector. Journal of Advanced Instrumentation in Science. https://doi.org/10.31526/jais.2022.267
- Mori, N., Ambrosino, F., Bonechi, L., Cimmino, L., D'alessandro, R., Noli, P., Saracino, G., Strolin, P., & Viliani, L. (2017). A geant4 framework for generic simulations of atmospheric muon detection experiments. Annals of Geophysics, 60(1). https://doi.org/10.4401/AG-7383
- Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., & Thépaut, J.-N. (2021). ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data, 13(9), 4349-4383. https://doi.org/10.5194/essd-13-4349-2021