Development of the very long-range cosmic-ray muon radiographic imaging technique to explore the internal structure of an erupting volcano, Shinmoe-dake, Japan

Kusagaya, Taro; Tanaka, Hiroyuki

doi:10.5194/gi-4-215-2015

Cited by 17 publications

(14 citation statements)

References 30 publications

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“…The former describes the abundance of cosmic-ray muons for different energies and zenith angles at the surface of the Earth. This has been well documented in literature (see, for example, Lesparre et al, 2010). The differences between models and experimental data, and hence the systematic model uncertainty, can be as large as 15 % for vertical muons (Hebbeker and Timmermans, 2002).…”

Section: Introductionsupporting

confidence: 62%

“…Besides these applications, which have mainly been designed for archaeological and civil engineering purposes, scientists have begun to deploy particle detectors to investigate and map geological structures. In recent years, this has been done for various volcanoes in Japan (Nishiyama et al, 2014;Tanaka et al, 2005Tanaka et al, , 2014, including the Shinmoedake volcano (Kusagaya and Tanaka, 2015), the lava dome at Unzen (Tanaka, 2016) and most recently the Sakurajima volcano (Oláh et al, 2018). Further experiments have been conducted in the Caribbean, in France (Ambrosino et al, 2015;Jourde et al, 2013Jourde et al, , 2015Lesparre et al, 2012;Marteau et al, 2015) and in Italy on Etna (Lo Presti et al, 2018) and Stromboli (Tioukov et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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The effect of rock composition on muon tomography measurements

et al. 2018

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Abstract. In recent years, the use of radiographic inspection with cosmic-ray muons has spread into multiple research and industrial fields. This technique is based on the high-penetration power of cosmogenic muons. Specifically, it allows the resolution of internal density structures of large-scale geological objects through precise measurements of the muon absorption rate. So far, in many previous works, this muon absorption rate has been considered to depend solely on the density of traversed material (under the assumption of a standard rock) but the variation in chemical composition has not been taken seriously into account. However, from our experience with muon tomography in Alpine environments, we find that this assumption causes a substantial bias in the muon flux calculation, particularly where the target consists of high {Z2∕A} rocks (like basalts and limestones) and where the material thickness exceeds 300 m. In this paper, we derive an energy loss equation for different minerals and we additionally derive a related equation for mineral assemblages that can be used for any rock type on which mineralogical data are available. Thus, for muon tomography experiments in which high {Z2∕A} rock thicknesses can be expected, it is advisable to plan an accompanying geological field campaign to determine a realistic rock model.

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Section: Introductionsupporting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

The effect of rock composition on muon tomography measurements

et al. 2018

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“…Lehner (2007) measured the thicknesses of the casing stones to be 82,67,45,66,44, and 45 cm from the lower edge of the upper zone to the apex. The size of the stones with the exception of those near the lower edge has been calculated to be an average of 53 cm.…”

Section: Weight Of the Pyramidmentioning

confidence: 99%

Muographic data analysis method for medium-sized rock overburden inspections

Tanaka

Ohshiro

2016

Geosci. Instrum. Method. Data Syst.

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Abstract. Muographic measurements of rock overburdens are of particular interest because they can be applied to natural resources and undiscovered cave explorations, and even to searching for hidden chambers in historic architectural structures. In order to derive the absolute density distribution of the overburden, we conventionally needed to know accurate information about the measurement conditions, e.g., the detector's geometrical acceptance, detection efficiency, and measurement time, in order to derive the absolute value of the transmitted muon flux. However, in many cases, it is not a simple task to accurately gauge such conditions. Open-sky muon data taken with the same detector are useful as reference data to cancel these factors; however, if the detector is not transportable, this data taking method is not feasible. In this work, we found that the transmitted muon flux will follow a simple function of the areal density along the muon path as long as the incident muon energies are below a few hundred GeV. Based on this finding, we proposed a simple analysis method that does not require detailed knowledge of the detector's conditions by combining the independently measured density information for the partial volume of the target. We anticipate that this simple method is applicable to future muographic measurements of rock overburdens.

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“…In the last two decades, muography has been developed for the density imaging (e.g. Tanaka et al 2001;Lesparre et al 2012;Kusagaya & Tanaka 2015) and monitoring (e.g. Tanaka et al 2014;Jourde et al 2015b) of volcanoes.…”

Section: Introductionmentioning

confidence: 99%

Bayesian joint muographic and gravimetric inversion applied to volcanoes

Barnoud

Cayol

Niess

et al. 2019

Geophysical Journal International

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SUMMARY Gravimetry is a technique widely used to image the structure of the Earth. However, inversions are ill-posed and the imaging power of the technique rapidly decreases with depth. To overcome this limitation, muography, a new imaging technique relying on high energy atmospheric muons, has recently been developed. Because muography only provides integrated densities above the detector from a limited number of observation points, inversions are also ill-posed. Previous studies have shown that joint muographic and gravimetric inversions better reconstruct the 3-D density structure of volcanic edifices than independent density inversions. These studies address the ill-posedness of the joint problem by regularizing the solution with respect to a prior density model. However, the obtained solutions depend on some hyperparameters, which are either determined relative to a single test case or rely on ad-hoc parameters. This can lead to inaccurate retrieved models, sometimes associated with artefacts linked to the muon data acquisition. In this study, we use a synthetic example based on the Puy de Dôme volcano to determine a robust method to obtain the resulting model closest to the synthetic model and devoid of acquisition artefacts. We choose a Bayesian approach to include an a priori density model and a smoothing by a Gaussian spatial correlation function relying on two hyperparameters: an a priori density standard deviation and an isotropic spatial correlation length. This approach has the advantage to provide a posteriori standard deviations on the resulting densities. Using our synthetic volcano, we investigate the most reliable criterion to determine the hyperparameters. Our results suggest that k-fold Cross-Validation Sum of Squares and the Leave One Out methods are more robust criteria than the classically used L-curves. The determined hyperparameters allow to overcome the artefacts linked to the data acquisition geometry, even when only a limited number of muon telescopes is available. We also illustrate the behaviour of the inversion in case of offsets in the a priori density or in the data and show that they lead to recognizable structures that help identify them.

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Development of the very long-range cosmic-ray muon radiographic imaging technique to explore the internal structure of an erupting volcano, Shinmoe-dake, Japan

Abstract: Development of the very long-range cosmic-ray muon radiographic imaging technique to explore the internal structure of an erupting volcano, Shinmoe-dake, Japan Abstract.

Cited by 17 publications

References 30 publications

The effect of rock composition on muon tomography measurements

The effect of rock composition on muon tomography measurements

Muographic data analysis method for medium-sized rock overburden inspections

Bayesian joint muographic and gravimetric inversion applied to volcanoes

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