Overview of the JET preparation for deuterium–tritium operation with the ITER like-wall
user-5fe1a78c4c775e6ec07359f9(2019)
摘要
For the past several years, the JET scientific programme (Pamela et al 2007 Fusion Eng. Des.
82 590) has been engaged in a multi-campaign effort, including experiments in D, H and T,
leading up to 2020 and the first experiments with 50%/50% D–T mixtures since 1997 and the
first ever D–T plasmas with the ITER mix of plasma-facing component materials. For this
purpose, a concerted physics and technology programme was launched with a view to prepare
the D–T campaign (DTE2). This paper addresses the key elements developed by the JET
programme directly contributing to the D–T preparation. This intense preparation includes
the review of the physics basis for the D–T operational scenarios, including the fusion power
predictions through first principle and integrated modelling, and the impact of isotopes in the
operation and physics of D–T plasmas (thermal and particle transport, high confinement mode
(H-mode) access, Be and W erosion, fuel recovery, etc). This effort also requires improving
several aspects of plasma operation for DTE2, such as real time control schemes, heat load
control, disruption avoidance and a mitigation system (including the installation of a new
shattered pellet injector), novel ion cyclotron resonance heating schemes (such as the threeions
scheme), new diagnostics (neutron camera and spectrometer, active Alfven eigenmode
antennas, neutral gauges, radiation hard imaging systems…) and the calibration of the JET
neutron diagnostics at 14 MeV for accurate fusion power measurement. The active preparation
of JET for the 2020 D–T campaign provides an incomparable source of information and a
basis for the future D–T operation of ITER, and it is also foreseen that a large number of key
physics issues will be addressed in support of burning plasmas.
更多查看译文
关键词
Fusion power,High-confinement mode,Nuclear engineering,Neutron,Injector,Spectrometer,Plasma,Thermal,Deuterium,Environmental science
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要