Abstract
The limits for the heat loads on the DEMO first wall are significantly stricter compared to those of ITER due to cooling and breeding blanket requirements. Fast particles in the form of NBI ions can escape the confinement due to magnetic perturbations and produce a significant power load on the first wall. In this contribution, we use the fast ion orbit-following code ASCOT to study NBI losses under the effects of 3D magnetic perturbations, including toroidal field ripple and ferritic inserts. The losses were found to not endanger the integrity of the wall, with loads remaining below 40 kW/m2 even with unmitigated ripple, and losses did not increase above 2.5 % even with 16 toroidal field coils. Ionization in the scrape-off layer was not found to increase the losses significantly for realistic density profiles, and the design of the wall allows for some flexibility in the distance between the plasma and the first wall tiles.
| Original language | English |
|---|---|
| Pages (from-to) | 1615-1619 |
| Journal | Fusion Engineering and Design |
| Volume | 146 |
| DOIs | |
| Publication status | Published - Sept 2019 |
| MoE publication type | A1 Journal article-refereed |
Funding
This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 under grant agreement No 633053. This work was partially funded by the Academy of Finland project No. 259675 , and has also received funding from Tekes – the Finnish Funding Agency for Innovation under the FinnFusion Consortium. The work was carried out using the HELIOS supercomputer system at International Fusion Energy Research Centre, Aomori, Japan, under the Broader Approach collaboration between Euratom and Japan, implemented by Fusion for Energy and JAEA. Part of the work was carried out on the EUROfusion High Performance Computer (Marconi-Fusion). The supercomputing resources of CSC – IT center for science were utilised in the studies. Some of the calculations were performed using computer resources within the Aalto University School of Science “Science-IT” project.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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