Articles | Volume 15, issue 6
https://doi.org/10.5194/gmd-15-2441-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-2441-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
22 Mar 2022
Model description paper |
| 22 Mar 2022
| 22 Mar 2022
SMAUG v1.0 – a user-friendly muon simulator for the imaging of geological objects in 3-D
Alessandro Lechmann
CORRESPONDING AUTHOR
Institute of Geological Sciences, University of Bern, Bern, 3012,
Switzerland
David Mair
Institute of Geological Sciences, University of Bern, Bern, 3012,
Switzerland
Akitaka Ariga
Albert Einstein Center for Fundamental Physics, Laboratory for High
Energy Physics, University of Bern, Bern, 3012, Switzerland
Tomoko Ariga
Faculty of Arts and Science, Kyushu University, Fukuoka, 819-0385,
Japan
Antonio Ereditato
Albert Einstein Center for Fundamental Physics, Laboratory for High
Energy Physics, University of Bern, Bern, 3012, Switzerland
Ryuichi Nishiyama
Earthquake Research Institute, The University of Tokyo, Tokyo,
113-0032, Japan
Ciro Pistillo
Albert Einstein Center for Fundamental Physics, Laboratory for High
Energy Physics, University of Bern, Bern, 3012, Switzerland
Paola Scampoli
Albert Einstein Center for Fundamental Physics, Laboratory for High
Energy Physics, University of Bern, Bern, 3012, Switzerland
Physics Department “Ettore Pancini”, University of Naples Federico
II, Naples, 80126, Italy
Mykhailo Vladymyrov
Albert Einstein Center for Fundamental Physics, Laboratory for High
Energy Physics, University of Bern, Bern, 3012, Switzerland
Fritz Schlunegger
Institute of Geological Sciences, University of Bern, Bern, 3012,
Switzerland
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Cited articles
Agostinelli, S., Allison, J., Amako, K. et al.: Geant4 – a simulation toolkit, Nucl. Instrum.
Methods Phys. Res. Sect. Accel. Spectrometers Detect. Assoc. Equip., 506,
250–303, https://doi.org/10.1016/S0168-9002(03)01368-8, 2003.
Aitchison, J.: The Statistical Analysis of Compositional Data, 1st edn., Monographs on Statistics and Applied Probability, Chapman and Hall Ltd, London & New York, ISBN 9780412280603, 1986.
Alvarez, L. W., Anderson, J. A., El Bedwei, F., Burkhard, J., Fakhry, A.,
Girgis, A., Goneid, A., Hassan, F., Iverson, D., Lynch, G., Miligy, Z.,
Moussa, A. H., Mohammed-Sharkawi, and Yazolino, L.: Search for Hidden
Chambers in the Pyramids, Science, 167, 832–839, 1970.
Ambrosino, F., Anastasio, A., Basta, D., Bonechi, L., Brianzi, M., Bross,
A., Callier, S., Caputo, A., Ciaranfi, R., Cimmino, L., D'Alessandro, R.,
D'Auria, L., Taille, C. de L., Energico, S., Garufi, F., Giudicepietro, F.,
Lauria, A., Macedonio, G., Martini, M., Masone, V., Mattone, C., Montesi, M.
C., Noli, P., Orazi, M., Passeggio, G., Peluso, R., Pla-Dalmau, A., Raux,
L., Rubinov, P., Saracino, G., Scarlini, E., Scarpato, G., Sekhniaidze, G.,
Starodubtsev, O., Strolin, P., Taketa, A., Tanaka, H. K. M., Vanzanella, A.,
and Viliani, L.: The MU-RAY project: detector technology and first data from
Mt. Vesuvius, J. Instrum., 9, C02029,
https://doi.org/10.1088/1748-0221/9/02/C02029, 2014.
Ambrosino, F., Anastasio, A., Bross, A., Béné, S., Boivin, P.,
Bonechi, L., Cârloganu, C., Ciaranfi, R., Cimmino, L., Combaret, C.,
D'Alessandro, R., Durand, S., Fehr, F., Français, V., Garufi, F.,
Gailler, L., Labazuy, P., Laktineh, I., Lénat, J.-F., Masone, V.,
Miallier, D., Mirabito, L., Morel, L., Mori, N., Niess, V., Noli, P.,
Pla-Dalmau, A., Portal, A., Rubinov, P., Saracino, G., Scarlini, E.,
Strolin, P., and Vulpescu, B.: Joint measurement of the atmospheric muon
flux through the Puy de Dôme volcano with plastic scintillators and
Resistive Plate Chambers detectors, J. Geophys. Res.-Sol. Ea., 120,
7290–7307, https://doi.org/10.1002/2015JB011969, 2015.
Anghel, V., Armitage, J., Baig, F., Boniface, K., Boudjemline, K., Bueno,
J., Charles, E., Drouin, P.-L., Erlandson, A., Gallant, G., Gazit, R.,
Godin, D., Golovko, V. V., Howard, C., Hydomako, R., Jewett, C., Jonkmans,
G., Liu, Z., Robichaud, A., Stocki, T. J., Thompson, M., and Waller, D.: A
plastic scintillator-based muon tomography system with an integrated muon
spectrometer, Nucl. Instrum. Methods Phys. Res. Sect. Accel. Spectrometers
Detect. Assoc. Equip., 798, 12–23,
https://doi.org/10.1016/j.nima.2015.06.054, 2015.
Ariga, A., Ariga, T., Ereditato, A., Käser, S., Lechmann, A., Mair, D.,
Nishiyama, R., Pistillo, C., Scampoli, P., Schlunegger, F., and Vladymyrov,
M.: A Nuclear Emulsion Detector for the Muon Radiography of a Glacier
Structure, Instruments, 2, 7, https://doi.org/10.3390/instruments2020007,
2018.
ASTM C914-09: Standard Test Method for Bulk Density and Volume of Solid Refactories by Wax Immersion, ASTM International, West Conshohocken, PA, https://doi.org/10.1520/C0914-09R15, 2015.
Barnaföldi, G. G., Hamar, G., Melegh, H. G., Oláh, L., Surányi,
G., and Varga, D.: Portable cosmic muon telescope for environmental
applications, Nucl. Instrum. Methods Phys. Res. Sect. Accel. Spectrometers
Detect. Assoc. Equip., 689, 60–69,
https://doi.org/10.1016/j.nima.2012.06.015, 2012.
Barnoud, A., Cayol, V., Niess, V., Cârloganu, C., Lelièvre, P.,
Labazuy, P., and Le Ménédeu, E.: Bayesian joint muographic and
gravimetric inversion applied to volcanoes, Geophys. J. Int., 218,
2179–2194, https://doi.org/10.1093/gji/ggz300, 2019.
Bellman, R. E.: Adaptive Control Processes A Guided Tour, Princeton
University Press, Princeton, ISBN 9781400874668, 2016.
Betancourt, M. J. and Girolami, M.: Hamiltonian Monte Carlo for Hierarchical Models, arXiv [preprint], arXiv:1312.0906, 3 December 2013.
Blake, G. R. and Hartge, K. H.: Bulk Density, in: Methods of Soil Analysis:
Part 1 – Physical and Mineralogical Methods, vol. 9, edited by: Klute, A.,
American Society of Agronomy and Soil Science Society of America, Madison,
363–375, https://doi.org/10.2136/sssabookser5.1.2ed, 1986.
Bonechi, L., D'Alessandro, R., Mori, N., and Viliani, L.: A projective
reconstruction method of underground or hidden structures using atmospheric
muon absorption data, JINST, 10, P02003,
https://doi.org/10.1088/1748-0221/10/02/P02003, 2015.
Bugaev, E. V., Misaki, A., Naumov, V. A., Sinegovskaya, T. S., Sinegovsky,
S. I., and Takahashi, N.: Atmospheric Muon Flux at Sea Level, Underground,
and Underwater, Phys. Rev. D, 58, 054001,
https://doi.org/10.1103/PhysRevD.58.054001, 1998.
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B.: Bayesian Data Analysis, 3rd edn., Texts in Statistical Science, CRC Press, Taylor & Francis Group, Boca Raton, ISBN 9781439840955, 2013.
Gerya, T.: Introduction to numerical geodynamic modelling, 1st edn., Cambridge
University Press, Cambridge, New York, ISBN 9780521887540, 2010.
Groom, D. E., Mokhov, N. V., and Striganov, S. I.: MUON STOPPING POWER AND
RANGE TABLES 10 MeV–100 TeV, At. Data Nucl. Data Tables, 78, 183–356,
https://doi.org/10.1006/adnd.2001.0861, 2001.
Guardincerri, E., Rowe, C., Schultz-Fellenz, E., Roy, M., George, N.,
Morris, C., Bacon, J., Durham, M., Morley, D., Plaud-Ramos, K., Poulson, D.,
Baker, D., Bonneville, A., and Kouzes, R.: 3D Cosmic Ray Muon Tomography
from an Underground Tunnel, Pure Appl. Geophys., 174, 2133–2141,
https://doi.org/10.1007/s00024-017-1526-x, 2017.
Hastings, W. K.: Monte Carlo sampling methods using Markov chains and their
applications, Biometrika, 57, 97–109,
https://doi.org/10.1093/biomet/57.1.97, 1970.
Hebbeker, T. and Timmermans, C.: A Compilation of High Energy Atmospheric
Muon Data at Sea Level, Astropart. Phys., 18, 107–127,
https://doi.org/10.1016/S0927-6505(01)00180-3, 2002.
Jonkmans, G., Anghel, V. N. P., Jewett, C., and Thompson, M.: Nuclear waste
imaging and spent fuel verification by muon tomography, Ann. Nucl. Energy,
53, 267–273, https://doi.org/10.1016/j.anucene.2012.09.011, 2013.
Jourde, K., Gibert, D., and Marteau, J.: Improvement of density models of geological structures by fusion of gravity data and cosmic muon radiographies, Geosci. Instrum. Method. Data Syst., 4, 177–188, https://doi.org/10.5194/gi-4-177-2015, 2015.
Jourde, K., Gibert, D., Marteau, J., de Bremond d'Ars, J., and Komorowski,
J.-C.: Muon dynamic radiography of density changes induced by hydrothermal
activity at the La Soufrière of Guadeloupe volcano, Sci. Rep., 6, 33406,
https://doi.org/10.1038/srep33406, 2016.
Kjaerulff, U. B. and Madsen, A. L.: Bayesian Networks and Influence
Diagrams: A Guide to Construction and Analysis, in: Information Science and Statistics, 1st edn., Springer, New York, ISBN 9780387741000, https://doi.org/10.1007/978-0-387-74101-7, 2008.
Kudryavtsev, V. A.: Muon simulation codes MUSIC and MUSUN for underground
physics, Comput. Phys. Commun., 180, 339–346,
https://doi.org/10.1016/j.cpc.2008.10.013, 2009.
Kusagaya, T. and Tanaka, H. K. M.: Development of the very long-range cosmic-ray muon radiographic imaging technique to explore the internal structure of an erupting volcano, Shinmoe-dake, Japan, Geosci. Instrum. Method. Data Syst., 4, 215–226, https://doi.org/10.5194/gi-4-215-2015, 2015.
Lechmann, A., Mair, D., Ariga, A., Ariga, T., Ereditato, A., Nishiyama, R., Pistillo, C., Scampoli, P., Schlunegger, F., and Vladymyrov, M.: The effect of rock composition on muon tomography measurements, Solid Earth, 9, 1517–1533, https://doi.org/10.5194/se-9-1517-2018, 2018.
Lechmann, A., Mair, D., Ariga, A., Ariga, T., Ereditato, A., Nishiyama, R.,
Pistillo, C., Scampoli, P., Schlunegger, F., and Vladymyrov, M.: Muon
tomography in geoscientific research – a guide to best practice,
Earth-Sci. Rev., 222, 103842,
https://doi.org/10.1016/j.earscirev.2021.103842, 2021a.
Lechmann, A., Mair, D., Ariga, A., Ariga, T., Ereditato, A., Nishiyama, R.,
Pistillo, C., Scampoli, P., Schlunegger, F., and Vladymyrov, M.: SMAUG – A
Simulator for Muon Applications Under Ground (Version 1.0), Zenodo [code and data set],
https://doi.org/10.5281/zenodo.5547356, 2021b.
Lelièvre, P. G., Barnoud, A., Niess, V., Cârloganu, C., Cayol, V.,
and Farquharson, C. G.: Joint inversion methods with relative density offset
correction for muon tomography and gravity data, with application to volcano
imaging, Geophys. J. Int., 218, 1685–1701,
https://doi.org/10.1093/gji/ggz251, 2019.
Lesparre, N., Gibert, D., Marteau, J., Déclais, Y., Carbone, D., and
Galichet, E.: Geophysical muon imaging: feasibility and limits, Geophys. J.
Int., 183, 1348–1361, https://doi.org/10.1111/j.1365-246X.2010.04790.x,
2010.
Lesparre, N., Gibert, D., and Marteau, J.: Bayesian dual inversion of
experimental telescope acceptance and integrated flux for geophysical muon
tomography, Geophys. J. Int., 188, 490–497,
https://doi.org/10.1111/j.1365-246X.2011.05268.x, 2012.
Lesparre, N., Cabrera, J., and Marteau, J.: 3-D density imaging with muon
flux measurements from underground galleries, Geophys. J. Int., 208,
1579–1591, https://doi.org/10.1093/gji/ggw482, 2017.
Lohmann, W., Kopp, R., and Voss, R.: Energy Loss of Muons in the Energy
Range 1–10000 GeV, CERN, Geneva, https://doi.org/10.5170/CERN-1985-003, 1985.
Lo Presti, D., Gallo, G., Bonanno, D. L., Bonanno, G., Bongiovanni, D. G.,
Carbone, D., Ferlito, C., Immè, J., La Rocca, P., Longhitano, F.,
Messina, A., Reito, S., Riggi, F., Russo, G., and Zuccarello, L.: The MEV
project: Design and testing of a new high-resolution telescope for muography
of Etna Volcano, Nucl. Instrum. Methods Phys. Res. Sect. Accel.
Spectrometers Detect. Assoc. Equip., 904, 195–201,
https://doi.org/10.1016/j.nima.2018.07.048, 2018.
Mair, D., Lechmann, A., Herwegh, M., Nibourel, L., and Schlunegger, F.: Linking Alpine deformation in the Aar Massif basement and its cover units – the case of the Jungfrau–Eiger mountains (Central Alps, Switzerland), Solid Earth, 9, 1099–1122, https://doi.org/10.5194/se-9-1099-2018, 2018.
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and
Teller, E.: Equation of State Calculations by Fast Computing Machines, J.
Chem. Phys., 21, 1087–1092, https://doi.org/10.1063/1.1699114, 1953.
Morishima, K., Kuno, M., Nishio, A., Kitagawa, N., Manabe, Y., Moto, M.,
Takasaki, F., Fujii, H., Satoh, K., Kodama, H., Hayashi, K., Odaka, S.,
Procureur, S., Attié, D., Bouteille, S., Calvet, D., Filosa, C.,
Magnier, P., Mandjavidze, I., Riallot, M., Marini, B., Gable, P., Date, Y.,
Sugiura, M., Elshayeb, Y., Elnady, T., Ezzy, M., Guerriero, E., Steiger, V.,
Serikoff, N., Mouret, J.-B., Charlès, B., Helal, H., and Tayoubi, M.:
Discovery of a big void in Khufu's Pyramid by observation of cosmic-ray
muons, Nature, 552, 386–390, https://doi.org/10.1038/nature24647, 2017.
Niess, V., Barnoud, A., Cârloganu, C., and Le Ménédeu, E.:
Backward Monte-Carlo applied to muon transport, Comput. Phys. Commun., 229, 54–67,
https://doi.org/10.1016/j.cpc.2018.04.001, 2018.
Nishiyama, R., Tanaka, Y., Okubo, S., Oshima, H., Tanaka, H. K. M., and
Maekawa, T.: Integrated processing of muon radiography and gravity anomaly
data toward the realization of high-resolution 3-D density structural
analysis of volcanoes: Case study of Showa-Shinzan lava dome, Usu, Japan, J.
Geophys. Res.-Sol. Ea., 119, 699–710,
https://doi.org/10.1002/2013JB010234, 2014.
Nishiyama, R., Ariga, A., Ariga, T., Käser, S., Lechmann, A., Mair, D.,
Scampoli, P., Vladymyrov, M., Ereditato, A., and Schlunegger, F.: First
measurement of ice-bedrock interface of alpine glaciers by cosmic muon
radiography, Geophys. Res. Lett., 44, 6244–6251,
https://doi.org/10.1002/2017GL073599, 2017.
Nishiyama, R., Ariga, A., Ariga, T., Lechmann, A., Mair, D., Pistillo, C.,
Scampoli, P., Valla, P. G., Vladymyrov, M., Ereditato, A., and Schlunegger,
F.: Bedrock sculpting under an active alpine glacier revealed from
cosmic-ray muon radiography, Sci. Rep., 9, 6970,
https://doi.org/10.1038/s41598-019-43527-6, 2019.
Noli, P., Ambrosino, F., Bonechi, L., Bross, A., Cimmino, L., D'Alessandro,
R., Masone, V., Mori, N., Passeggio, G., Pla-Dalmau, A., Saracino, G.,
Scarlini, E., and Strolin, P.: Muography of the Puy de Dôme, Ann.
Geophys., 60, S0105, https://doi.org/10.4401/ag-7380, 2017.
Oláh, L., Barnaföldi, G. G., Hamar, G., Melegh, H. G., Surányi,
G., and Varga, D.: Cosmic Muon Detection for Geophysical Applications,
Adv. High Energy Phys., 560192, https://doi.org/10.1155/2013/560192, 2013.
Oláh, L., Tanaka, H. K. M., Ohminato, T., and Varga, D.: High-definition
and low-noise muography of the Sakurajima volcano with gaseous tracking
detectors, Sci. Rep., 8, 3207, https://doi.org/10.1038/s41598-018-21423-9,
2018.
Reyna, D.: A Simple Parameterization of the Cosmic-Ray Muon Momentum Spectra
at the Surface as a Function of Zenith Angle, arXiv [preprint], arXiv:hep-ph/0604145, 1 June 2006.
Rosas-Carbajal, M., Jourde, K., Marteau, J., Deroussi, S., Komorowski,
J.-C., and Gibert, D.: Three-dimensional density structure of La Soufrière de Guadeloupe lava dome from simultaneous muon radiographies and garvity data, Geophys. Res.
Lett., 44, 6743–6751, https://doi.org/10.1002/2017GL074285, 2017.
Saracino, G., Amato, L., Ambrosino, F., Antonucci, G., Bonechi, L., Cimmino,
L., Consiglio, L., D'Alessandro, R., Luzio, E. D., Minin, G., Noli, P.,
Scognamiglio, L., Strolin, P., and Varriale, A.: Imaging of underground
cavities with cosmic-ray muons from observations at Mt. Echia (Naples), Sci.
Rep., 7, 1181, https://doi.org/10.1038/s41598-017-01277-3, 2017.
Stoer, J. and Burlisch, R.: Introduction to Numerical Analysis, 3rd edn., Springer, New York, ISBN 978-0-387-95452-3, https://doi.org/10.1007/978-0-387-21738-3, 2002.
Takahasi, H. and Mori, M.: Double Exponential Formulas for Numerical
Integration, Publ. Res. Inst. Math. Sci., 9, 721–741,
https://doi.org/10.2977/prims/1195192451, 1974.
Takamatsu, K., Takegami, H., Ito, C., Suzuki, K., Ohnuma, H., Hino, R., and
Okumura, T.: Cosmic-ray muon radiography for reactor core observation, Ann.
Nucl. Energy, 78, 166–175, https://doi.org/10.1016/j.anucene.2014.12.017,
2015.
Tanabashi, M., Hagiwara, K., Hikasa, K., et al.: (Particle Data Group): Review of Particle Physics,
Phys. Rev. D, 98, 030001, https://doi.org/10.1103/PhysRevD.98.030001, 2018.
Tanaka, H. K. M.: Instant snapshot of the internal structure of Unzen lava
dome, Japan with airborne muography, Sci. Rep., 6, 39741,
https://doi.org/10.1038/srep39741, 2016.
Tang, A., Horton-Smith, G., Kudryavtsev, V. A., and Tonazzo, A.: Muon
Simulations for Super-Kamiokande, KamLAND and CHOOZ, Phys. Rev. D, 74,
053007, https://doi.org/10.1103/PhysRevD.74.053007, 2006.
Tarantola, A.: Inverse Problem Theory and Methods for Model Parameter Estimation, 1st edn., Other Titles in Applied Mathematics, Siam, Philadelphia ISBN 9780898715729, https://doi.org/10.1137/1.9780898717921, 2005.
Thompson, L. F., Stowell, J. P., Fargher, S. J., Steer, C. A., Loughney, K.
L., O'Sullivan, E. M., Gluyas, J. G., Blaney, S. W., and Pidcock, R. J.:
Muon tomography for railway tunnel imaging, Phys. Rev. Res., 2, 023017,
https://doi.org/10.1103/PhysRevResearch.2.023017, 2020.
Tioukov, V., Lellis, G. D., Strolin, P., Consiglio, L., Sheshukov, A.,
Orazi, M., Peluso, R., Bozza, C., Sio, C. D., Stellacci, S. M., Sirignano,
C., D'Ambrosio, N., Miyamoto, S., Nishiyama, R., and Tanaka, H. K. M.:
Muography with nuclear emulsions – Stromboli and other projects, Ann.
Geophys., 60, S0111, https://doi.org/10.4401/ag-7386, 2017.
Vermeesch, P.: On the visualisation of detrital age distributions, Chemical
Geology, 312–313, 190–194, https://doi.org/10.1016/j.chemgeo.2012.04.021,
2012.
Short summary
Muon tomography is a technology that is used often in geoscientific research. The know-how of data analysis is, however, still possessed by physicists who developed this technology. This article aims at providing geoscientists with the necessary tools to perform their own analyses. We hope that a lower threshold to enter the field of muon tomography will allow more geoscientists to engage with muon tomography. SMAUG is set up in a modular way to allow for its own modules to work in between.
Muon tomography is a technology that is used often in geoscientific research. The know-how of...
