A New Degassing Model to Infer Magma Dynamics from Radioactive Disequilibria in Volcanic Plumes

Terray, Luca; Gauthier, Pierre‐Jean; Salerno, Giuseppe; Spina, Alessandro La; Caltabiano, Tommaso; Sellitto, Pasquale; Briole, Pierre

doi:10.3390/geosciences8010027

Cited by 9 publications

(14 citation statements)

References 46 publications

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“…This observation strongly suggests for the first time that the plume is enriched in radon. Moreover, covariations of radon activity in the air and volcanic activity have been noticed and indicate that radon activity in magmatic gas plumes could also be an interesting parameter to monitor, as was previously proposed by theoretical modeling [ 9 ]. Finally, this study has also revealed very high radon activities (up to 8 kBq/m 3 ) in the air in a few zones of the Mt.…”

Section: Introduction and State-of-the-artmentioning

confidence: 71%

From Sensor to Cloud: An IoT Network of Radon Outdoor Probes to Monitor Active Volcanoes

Terray

Royer

Sarramia

et al. 2020

Sensors

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While radon in soil gases has been identified for decades as a potential precursor of volcanic eruptions, there has been a recent interest for monitoring radon in air on active volcanoes. We present here the first network of outdoor air radon sensors that was installed successfully on Mt. Etna volcano, Sicily, Italy in September 2019. Small radon sensors designed for workers and home dosimetry were tropicalized in order to be operated continuously in harsh volcanic conditions with an autonomy of several months. Two stations have been installed on the south flank of the volcano at ~3000 m of elevation. A private network has been deployed in order to transfer the measurements from the stations directly to a server located in France, using a low-power wide-area transmission technology from Internet of Things (IoT) called LoRaWAN. Data finally feed a data lake, allowing flexibility in data management and sharing. A first analysis of the radon datasets confirms previous observations, while adding temporal information never accessed before. The observed performances confirm IoT solutions are very adapted to active volcano monitoring in terms of range, autonomy, and data loss.

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Section: Introduction and State-of-the-artmentioning

confidence: 71%

From Sensor to Cloud: An IoT Network of Radon Outdoor Probes to Monitor Active Volcanoes

Terray

Royer

Sarramia

et al. 2020

Sensors

Self Cite

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“…Our code will also be made available in the open-source form for the community to enhance. Besides improving the plume model, coupling the volcanic plume model with magma reservoir models (e.g., Terray et al, 2018), which could provide more accurate eruption conditions, might improve accuracy of the volcanic plume simulation.…”

Section: Discussionmentioning

confidence: 99%

“…The cloud microphysics predicts the mass of hydrometeors in liquid and ice phases (Herzog et al, 1998). Additional modules, including gas-phase chemistry (Trentmann et al, 2002) and gas scavenging by hydrometeors (Textor et al, 2003), were added lately. A further extension was made to include particle aggregation (Textor et al, 2006b, a).…”

Section: Existing Plume Modelsmentioning

confidence: 99%

Plume-SPH 1.0: a three-dimensional, dusty-gas volcanic plume model based on smoothed particle hydrodynamics

et al. 2018

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Abstract. Plume-SPH provides the first particle-based simulation of volcanic plumes. Smoothed particle hydrodynamics (SPH) has several advantages over currently used mesh-based methods in modeling of multiphase free boundary flows like volcanic plumes. This tool will provide more accurate eruption source terms to users of volcanic ash transport and dispersion models (VATDs), greatly improving volcanic ash forecasts. The accuracy of these terms is crucial for forecasts from VATDs, and the 3-D SPH model presented here will provide better numerical accuracy. As an initial effort to exploit the feasibility and advantages of SPH in volcanic plume modeling, we adopt a relatively simple physics model (3-D dusty-gas dynamic model assuming well-mixed eruption material, dynamic equilibrium and thermodynamic equilibrium between erupted material and air that entrained into the plume, and minimal effect of winds) targeted at capturing the salient features of a volcanic plume. The documented open-source code is easily obtained and extended to incorporate other models of physics of interest to the large community of researchers investigating multiphase free boundary flows of volcanic or other origins. The Plume-SPH code (https://doi.org/10.5281/zenodo. 572819) also incorporates several newly developed techniques in SPH needed to address numerical challenges in simulating multiphase compressible turbulent flow. The code should thus be also of general interest to the much larger community of researchers using and developing SPH-based tools. In particular, the SPH−ε turbulence model is used to capture mixing at unresolved scales. Heat exchange due to turbulence is calculated by a Reynolds analogy, and a corrected SPH is used to handle tensile instability and deficiency of particle distribution near the boundaries. We also developed methodology to impose velocity inlet and pressure outlet boundary conditions, both of which are scarce in traditional implementations of SPH. The core solver of our model is parallelized with the message passing interface (MPI) obtaining good weak and strong scalability using novel techniques for data management using space-filling curves (SFCs), object creation time-based indexing and hash-table-based storage schemes. These techniques are of interest to researchers engaged in developing particles in cell-type methods. The code is first verified by 1-D shock tube tests, then by comparing velocity and concentration distribution along the central axis and on the transverse cross with experimental results of JPUE (jet or plume that is ejected from a nozzle into a uniform environment). Profiles of several integrated variables are compared with those calculated by existing 3-D plume models for an eruption with the same mass eruption rate (MER) estimated for the Mt. Pinatubo eruption of 15 June 1991. Our results are consistent with existing 3-D plume models. Analysis of the plume evolution process demonstrates that this model is able to reproduce the physics of plume development.

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“…The cloud microphysics predicts the mass of hydrometeors in liquid and ice phases . Additional modules, including gas-phase chemistry (Trentmann et al, 2002) and gas scavenging by hydrometeors (Textor et al, 2003), were added lately. A further extension was made to include particle aggregation (Textor et al, 2006b, a).…”

Section: Existing Plume Modelsmentioning

confidence: 99%

Response to Review 2 -- Please see modified paper in attachment

Patra¹

2018

Preprint

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Plume-SPH provides the first particle-based simulation of volcanic plumes. Smoothed particle hydrodynamics (SPH) has several advantages over currently used meshbased methods in modeling of multiphase free boundary flows like volcanic plumes. This tool will provide more accurate eruption source terms to users of volcanic ash transport and dispersion models (VATDs), greatly improving volcanic ash forecasts. The accuracy of these terms is crucial for forecasts from VATDs, and the 3-D SPH model presented here will provide better numerical accuracy. As an initial effort to exploit the feasibility and advantages of SPH in volcanic plume modeling, we adopt a relatively simple physics model (3-D dusty-gas dynamic model assuming well-mixed eruption material, dynamic equilibrium and thermodynamic equilibrium between erupted material and air that entrained into the plume, and minimal effect of winds) targeted at capturing the salient features of a volcanic plume. The documented open-source code is easily obtained and extended to incorporate other models of physics of interest to the large community of researchers investigating multiphase free boundary flows of volcanic or other origins.The Plume-SPH code (https://doi.org/10.5281/zenodo. 572819) also incorporates several newly developed techniques in SPH needed to address numerical challenges in simulating multiphase compressible turbulent flow. The code should thus be also of general interest to the much larger community of researchers using and developing SPH-based tools. In particular, the SPH − ε turbulence model is used to capture mixing at unresolved scales. Heat exchange due to turbulence is calculated by a Reynolds analogy, and a corrected SPH is used to handle tensile instability and deficiency of particle distribution near the boundaries. We also developed methodology to impose velocity inlet and pressure outlet boundary conditions, both of which are scarce in traditional implementations of SPH.The core solver of our model is parallelized with the message passing interface (MPI) obtaining good weak and strong scalability using novel techniques for data management using space-filling curves (SFCs), object creation time-based indexing and hash-table-based storage schemes. These techniques are of interest to researchers engaged in developing particles in cell-type methods. The code is first verified by 1-D shock tube tests, then by comparing velocity and concentration distribution along the central axis and on the transverse cross with experimental results of JPUE (jet or plume that is ejected from a nozzle into a uniform environment). Profiles of several integrated variables are compared with those calculated by existing 3-D plume models for an eruption with the same mass eruption rate (MER) estimated for the Mt. Pinatubo eruption of 15 June 1991. Our results are consistent with existing 3-D plume models. Analysis of the plume evolution process demonstrates that this model is able to reproduce the physics of plume development.

show abstract

A New Degassing Model to Infer Magma Dynamics from Radioactive Disequilibria in Volcanic Plumes

Cited by 9 publications

References 46 publications

From Sensor to Cloud: An IoT Network of Radon Outdoor Probes to Monitor Active Volcanoes

From Sensor to Cloud: An IoT Network of Radon Outdoor Probes to Monitor Active Volcanoes

Plume-SPH 1.0: a three-dimensional, dusty-gas volcanic plume model based on smoothed particle hydrodynamics

Response to Review 2 -- Please see modified paper in attachment

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