Data from: Data-driven analysis of oscillations in Hall thruster simulations & Data-driven sparse modeling of oscillations in plasma space propulsion

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Dataset information

Country of origin
Updated
2024.10.09 00:00
Created
2022.01.01
Available languages
English
Keywords
Ion transit time, Breathing mode, Higher order dynamic mode decomposition, Data-driven analysis, Hall effect thruster
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Dataset description

Data from: Data-driven analysis of oscillations in Hall thruster simulations   - Authors: Davide Maddaloni, Adrián Domínguez Vázquez, Filippo Terragni, Mario Merino - Contact email: dmaddalo@ing.uc3m.es - Date: 2022-03-24 - Keywords: higher order dynamic mode decomposition, hall effect thruster, breathing mode, ion transit time, data-driven analysis - Version: 1.0.4 - Digital Object Identifier (DOI): 10.5281/zenodo.6359505 - License: This dataset is made available under the Open Data Commons Attribution License   Abstract   This dataset contains the outputs of the HODMD algorithm and the original simulations used in the journal publication: Davide Maddaloni, Adrián Domínguez Vázquez, Filippo Terragni, Mario Merino, "Data-driven analysis of oscillations in Hall thruster simulations", 2022 Plasma Sources Sci. Technol. 31:045026. Doi: 10.1088/1361-6595/ac6444. Additionally, the raw simulation data is also employed in the following journal publication: Borja Bayón-Buján and Mario Merino, "Data-driven sparse modeling of oscillations in plasma space propulsion", 2024 Mach. Learn.: Sci. Technol. 5:035057. Doi: 10.1088/2632-2153/ad6d29   Dataset description   The simulations from which data stems have been produced using the full 2D hybrid PIC/fluid code HYPHEN, while the HODMD results have been produced using an adaptation of the original HODMD algorithm with an improved amplitude calculation routine. Please refer to the relative article for further details regarding any of the parameters and/or configurations.   Data files   The data files are in standard Matlab .mat format. A recent version of Matlab is recommended. The HODMD outputs are collected within 18 different files, subdivided into three groups, each one referring to a different case. For the file names, "case1" refers to the nominal case, "case2" refers to the low voltage case and "case3" refers to the high mass flow rate case. Following, the variables are referred as: "n" for plasma density "Te" for electron temperature "phi" for plasma potential "ji" for ion current density (both single and double charged ones) "nn" for neutral density "Ez" for axial electric field "Si" for ionization production term "vi1" for single charged ions axial velocity In particular, axial electric field, ionization production term and single charged ions axial velocity are available only for the first case. Such files have a cell structure: the first row contains the frequencies (in Hz), the second row contains the normalized modes (alongside their complex conjugates), the third row collects the growth rates (in 1/s) while the amplitudes (dimensionalized) are collected within the last row. Additionally, the time vector is simply given as "t", common to all cases and all variables. The raw simulation data are collected within additional 15 variables, following the same nomenclature as above, with the addition of the suffix "_raw" to differentiate them from the HODMD outputs.   Citation   Works using this dataset or any part of it in any form shall cite it as follows. The preferred means of citation is to reference the publication associated to this dataset, as soon as it is available. Optionally, the dataset may be cited directly by referencing the DOI: 10.5281/zenodo.6359505.   Acknowledgments   This work has been supported by the Madrid Government (Comunidad de Madrid) under the Multiannual Agreement with UC3M in the line of ‘Fostering Young Doctors Research’ (MARETERRA-CM-UC3M), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation). F. Terragni was also supported by the Fondo Europeo de Desarrollo Regional, Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación, under grants MTM2017-84446-C2-2-R and PID2020-112796RB-C22.
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