Data Publication

Experimental dataset for the influence of grain size distribution on experimental volcanic lightning

GFZ Data Services

(2022)

Descriptions

This data publication provides data from 96 experiments from 2020 to 2022 in the gas-mixing lab at the Ludwig-Maximilians-Universität München (Germany). The experiments were conducted to investigate the influence of grain size distribution, especially the influence of very fines [<10 µm] on the generation of experimental volcanic lightning (VL). The influence of grain size distribution was tested for three different materials. Experimental discharges during rapid decompression were evaluated by their number and their total magnitude. The three materials used in this study are a tholeiitic basalt (TB), industrial manufactured soda-lime glass beads (GB) and a phonolitic pumice from the lower Laacher See unit (LSB). The samples were sieved into several grain size fractions, and coarse and fines were mixed to test the influence of the added fines on the discharge behaviour. For the tholeiitic basalt, the coarse grain size fraction is 180-250 µm, for the glass beads 150-250 µm and for the phonolitic pumice, two coarse grain size fractions, 180-250 µm and 90-300 µm were tested. The experiments were carried out in a new experimental setup, a modification of the shock tube experiments first described by Alidibirov and Dingwell (1996) and its further modifications (Cimarelli et al., 2014; Gaudin & Cimarelli, 2019; Stern et al., 2019). A mixture of coarse and fine sample material is placed into an autoclave and continuously set under pressure with argon gas up to the desired decompression pressure (⁓10 MPa). Then, rapid decompression is initialized, and the sample material is ejected from the autoclave through a nozzle into a gas-tight particle collector tank. The particle collector tank is insulated from the nozzle and the ground and serves as a Faraday cage (FC). All discharges going from the erupting gas-particle mixture, the jet, to the nozzle will be recorded by a datalogger. All the discharges measured during the first 5 ms of ejection were taken into the evaluation of the discharge behaviour. The raw signals of the experiments were evaluated by a processing code developed by Gaudin and Cimarelli (2019). Additionally, the jet behaviour was recorded by a high-speed camera: the gas-exit angle and the exit angle of the gas-particle mixture were determined. The background of the high-speed video was divided into a black side and a white side. The gas-exit angle and the exit angle gas-particle-mixture were determined as the mean of the deviation angle of a straight trajectory angle of both sides.

Keywords

Originally assigned keywords

ash

electric charge

Faraday cage

shock-tube

jet

rapid decompression

phonolite

tholeiite

glass beads

EPOS

multi-scale laboratories

rock and melt physical properties

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC ELECTRICITY > LIGHTNING

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC PHENOMENA > LIGHTNING

EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > VOLCANIC ERUPTIONS

EARTH SCIENCE > SOLID EARTH > TECTONICS > VOLCANIC ACTIVITY > ERUPTION DYNAMICS > ASH/DUST DISPERSION

EARTH SCIENCE > SOLID EARTH > TECTONICS > VOLCANIC ACTIVITY > ERUPTION DYNAMICS > VOLCANIC EXPLOSIVITY

EARTH SCIENCE SERVICES > ENVIRONMENTAL ADVISORIES > GEOLOGICAL ADVISORIES > VOLCANIC ACTIVITY

EARTH SCIENCE SERVICES > ENVIRONMENTAL ADVISORIES > WEATHER/CLIMATE ADVISORIES > DUST/ASH ADVISORIES

Corresponding MSL vocabulary keywords

phonolite

glass microspheres

MSL enriched keywords

igneous rock - extrusive

intermediate extrusive

phonolite

analogue modelling material

granular modelling material

synthetic granular material

glass microspheres

Measured property

grain size distribution

Measured property

grain size distribution

Analyzed feature

grain size and configuration

grain size

grain size distribution

basic extrusive

basalt

volcanic glass

pumice

unconsolidated sediment

tephra

pumice

natural granular material

pumice

Apparatus

analogue modelling

deformation experiments

shock tube

Ancillary equipment

model surface monitoring (2D)

camera

MSL enriched sub domains i

rock and melt physics

analogue modelling of geologic processes

microscopy and tomography

Source

https://dataservices.gfz-potsdam.de/panmetaworks/showshort.php?id=1121fa1a-9fa1-11ec-a8b4-7d2338b1cdf0

Source publisher

GFZ Data Services

DOI

10.5880/fidgeo.2022.009

Creators

Springsklee, Christina

Ludwig-Maximilians-Universität München, Munich, Germany

ORCID:

https://orcid.org/0000-0001-7830-9794

Scheu, Bettina

Ludwig-Maximilians-Universität München, Munich, Germany

ORCID:

https://orcid.org/0000-0002-0478-1049

Manga, Michael

Ludwig-Maximilians-Universität München, Munich, Germany | University of California, Berkeley, US

ORCID:

https://orcid.org/0000-0003-3286-4682

Cigala, Valeria

Ludwig-Maximilians-Universität München, Munich, Germany

ORCID:

https://orcid.org/0000-0003-2410-136X

Cimarelli, Corrado

Ludwig-Maximilians-Universität München, Munich, Germany

ORCID:

https://orcid.org/0000-0002-5707-5930

Dingwell, Donald B.

Ludwig-Maximilians-Universität München, Munich, Germany

ORCID:

https://orcid.org/0000-0002-3332-789X

Contributors

Springsklee, Christina

ContactPerson

Ludwig-Maximilians-Universität München, Munich, Germany

ORCID:

https://orcid.org/0000-0001-7830-9794

Springsklee, Christina

DataCollector

Ludwig-Maximilians-Universität München, Munich, Germany

ORCID:

https://orcid.org/0000-0001-7830-9794

Scheu, Bettina

ContactPerson

Ludwig-Maximilians-Universität München, Munich, Germany

ORCID:

https://orcid.org/0000-0002-0478-1049

Scheu, Bettina

DataCollector

Ludwig-Maximilians-Universität München, Munich, Germany

ORCID:

https://orcid.org/0000-0002-0478-1049

Fragmentation Lab (Ludwig-Maximilians-University Munich, Germany)

HostingInstitution

Ludwig-Maximilians University of Munich, Munich, Germany

labid:

9cd562c216daa82792972a074a222c52

Springsklee, Christina

ContactPerson

Ludwig-Maximilians University of Munich, Munich, Germany

Scheu, Bettina

ContactPerson

Ludwig-Maximilians University of Munich, Munich, Germany

References

10.1029/2022jb024390

10.1007/s004450050149

10.1130/g34802.1

10.1016/j.epsl.2019.02.024

10.1029/2019gl084678

Citation

Springsklee, C., Scheu, B., Manga, M., Cigala, V., Cimarelli, C., & Dingwell, D. B. (2022). Experimental dataset for the influence of grain size distribution on experimental volcanic lightning [Data set]. GFZ Data Services. https://doi.org/10.5880/FIDGEO.2022.009

Dates

Created:

2020-08-18

Issued:

2022

Rights

Creative Commons Attribution 4.0 International