Bayesian inference of plasma parameters from collective Thomson scattering technique on a gas-puff near stagnation.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
10 Aug 2023
10 Aug 2023
Historique:
received:
26
12
2022
accepted:
02
08
2023
medline:
11
8
2023
pubmed:
11
8
2023
entrez:
10
8
2023
Statut:
epublish
Résumé
The Collective Thomson scattering technique has been implemented to study the stagnation of a single liner gas-puff. The plasma parameters are determined by theoretically modelling the scattering form factor in combination with Bayesian inference to provide the set of the most probable parameters that describe the experimental data. Analysis of the data reveal that incoming flows are able to interpenetrate partially. Estimation of the mean free path shows a gradual transition from a weakly collisional to a collisional regime as the plasma gets to the axis. Furthermore, we find that the ion energy at [Formula: see text] is [Formula: see text] and is mostly kinetic in nature and represents [Formula: see text] of the total energy. This kinetic energy is far greater than the value on axis of [Formula: see text] which is [Formula: see text] of the total energy. Energy transfer to the electrons and radiation losses are found to be negligible by this time. A possible explanation for this energy imbalance is the presence of an azimuthal magnetic field larger than [Formula: see text] that deflect the ions vertically. The uncertainties quoted represent 68% credible intervals.
Identifiants
pubmed: 37563239
doi: 10.1038/s41598-023-40014-x
pii: 10.1038/s41598-023-40014-x
pmc: PMC10415259
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
13002Subventions
Organisme : Fondo Nacional de Desarrollo Científico y Tecnológico
ID : 1220533
Organisme : Fondo Nacional de Desarrollo Científico y Tecnológico
ID : 1220533
Organisme : Fondo Nacional de Desarrollo Científico y Tecnológico
ID : 1220533
Organisme : Fondo Nacional de Desarrollo Científico y Tecnológico
ID : 1220533
Informations de copyright
© 2023. Springer Nature Limited.
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