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February 9–11, 2021
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Fusion Science and Technology
Former NRC chairs issue vaccine timeline recommendation to CDC
Five former chairmen of the U.S. Nuclear Regulatory Commission—Stephen Burns, Allison Macfarlane, Nils Diaz, Richard Meserve, and Dale Klein—signed a letter to José Romero, Arkansas health secretary and chair of the Centers for Disease Control and Prevention (CDC) immunization advisory committee, requesting that the advisory committee update its recommendation for COVID-19 vaccine allocation guidance for the energy workforce (including nuclear energy workers).
Currently, the CDC has four phases for the COVID-19 vaccine rollout. Those phases are numbered:
M. Salewski, M. Nocente, A. S. Jacobsen, F. Binda, C. Cazzaniga, J. Eriksson, B. Geiger, G. Gorini, C. Hellesen, V. G. Kiptily, T. Koskela, S. B. Korsholm, T. Kurki-Suonio, F. Leipold, D. Moseev, S. K. Nielsen, J. Rasmussen, P. A. Schneider, S. E. Sharapov, M. Stejner, M. Tardocchi, JET Contributors, ASDEX Upgrade Team, EUROfusion MST1 Team
Fusion Science and Technology | Volume 74 | Number 1 | July-August 2018 | Pages 23-36
Technical Paper | dx.doi.org/10.1080/15361055.2017.1380482
Articles are hosted by Taylor and Francis Online.
Bayesian integrated data analysis combines measurements from different diagnostics to jointly measure plasma parameters of interest such as temperatures, densities, and drift velocities. Integrated data analysis of fast-ion measurements has long been hampered by the complexity of the strongly non-Maxwellian fast-ion distribution functions. This has recently been overcome by velocity-space tomography. In this method two-dimensional images of the velocity distribution functions consisting of a few hundreds or thousands of pixels are reconstructed using the available fast-ion measurements. Here we present an overview and current status of this emerging technique at the ASDEX Upgrade tokamak and the JET toamak based on fast-ion D-alpha spectroscopy, collective Thomson scattering, gamma-ray and neutron emission spectrometry, and neutral particle analyzers. We discuss Tikhonov regularization within the Bayesian framework. The implementation for different types of diagnostics as well as the uncertainties are discussed, and we highlight the importance of integrated data analysis of all available detectors.