Simultaneous diagnosis of radial profiles and mix in NIF ignition-scale implosions via X-ray spectroscopy

Orlando Ciricosta, H. Scott, P. Durey, B. A. Hammel, R. Epstein, T. R. Preston, S P Regan, S. M. Vinko, N. C. Woolsey, J S Wark

Research output: Contribution to journalArticlepeer-review

Abstract

In a National Ignition Facility implosion, hydrodynamic instabilities may cause the cold material from the imploding shell to be injected into the hot-spot (hot-spot mix), enhancing the radiative and conductive losses, which in turn may lead to a quenching of the ignition process. The bound-bound features of the spectrum emitted by high-Z ablator dopants that get mixed into the hot-spot have been previously used to infer the total amount of mixed mass; however, the typical errorbars are larger than the maximum tolerable mix. We present here an improved 2D model for mix spectroscopy which can be used to retrieve information on both the amount of mixed mass and the full imploded plasma profile. By performing radiation transfer and simultaneously fitting all of the features exhibited by the spectra, we are able to constrain self-consistently the effect of the opacity of the external layers of the target on the emission, thus improving the accuracy of the inferred mixed mass. The model's predictive capabilities are first validated by fitting simulated spectra arising from fully characterized hydrodynamic simulations, and then, the model is applied to previously published experimental results, providing values of mix mass in agreement with previous estimates. We show that the new self consistent procedure leads to better constrained estimates of mix and also provides insight into the sensitivity of the hot-spot spectroscopy to the spatial properties of the imploded capsule, such as the in-flight aspect ratio of the cold fuel surrounding the hotspot.

Original languageEnglish
Article number112703
Pages (from-to)1-9
Number of pages9
JournalPhysics of Plasmas
Volume24
Issue number11
DOIs
Publication statusPublished - 6 Nov 2017

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