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Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
15.09.2022
Verantwortlich:
Smolka, Alexander
Autorinnen / Autoren:
Smolka, Alexander ; Nikolic, Dragan ; Gscheidle, Christian ; Reiss, Philipp
Institutionszugehörigkeit:
TUM
Herausgeber:
TUM
Titel:
Lunar Hydrogen Exosphere Predictions
Identifikator:
doi:10.14459/2022mp1686124
Enddatum der Datenerzeugung:
22.08.2022
Fachgebiet:
DAT Datenverarbeitung, Informatik; MAT Mathematik; NAT Naturwissenschaften (allgemein)
zusätzliche Fachgebiete:
Space Science
Quellen der Daten:
Simulationen / simulations
Datentyp:
Tabellen / tables
Methode der Datenerhebung:
Data generated by the Julia based Monte-Carlo simulation model.
Beschreibung:
"Smolka2022 - Lunar Hydrogen Exosphere Predictions" The dataset contains the three subfolders "mean_loss", "mean_surface_number_density", and "raw_julia". The first two folders contain eight CSV files, one for each of the eight performed studies, which list the empirical mean value over all (4000) Monte-Carlo steps for the losses and the surface number densities, respectively. The losses are given as globally lost particles per second, sorted by the loss mechanism (rows) and the elements H, H2, OH, and H2O (columns). The surface number densities are given as particles per cubic centimeters at the numerical grid points, which are supplied in the form of local time (first column) and subsolar latitude (second column). The used numerical grid is a structured grid with 180 points along the local time and 45 points along the latitude, which discretizes the upper hemisphere, assuming equatorial symmetry. The last folder "raw_julia" contains the compressed Julia data of all Monte-Carlo steps, in ".jld2" format. These can be extracted using the "JLD2" package with the command "jldopen( < path > .jld2)".
Links:
This dataset relates to the publication: https://www.sciencedirect.com/science/article/abs/pii/S0019103523000854?dgcid=author
Schlagworte:
Moon, Exosphere, Simulation, Density, Hydrogen, Water
Technische Hinweise:
View and download (7,5 GB total, 33 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1686124):
rsync rsync://m1686124@dataserv.ub.tum.de/m1686124/
Sprache:
en
 BibTeX