Machine-Learning-Assisted Analysis of Visible Spectroscopy in Pulsed-Power-Driven Plasmas

Machine-Learning-Assisted Analysis of Visible Spectroscopy in Pulsed-Power-Driven Plasmas

We use machine-learning (ML) models to predict ion density and electron temperature from visible emission spectra, in a high-energy density pulsed-power-driven aluminum plasma, generated by an exploding wire array. Radiation transport simulations, which use spectral emissivity and opacity values gen...

Full description

Bibliographic Details
Main Authors: Datta, Rishabh, Ahmed, Faez, Hare, Jack D.
Other Authors: Massachusetts Institute of Technology. Plasma Science and Fusion Center
Format: Article
Published: Institute of Electrical and Electronics Engineers 2024
Online Access:https://hdl.handle.net/1721.1/155296

Internet

https://hdl.handle.net/1721.1/155296

Similar Items