Abstract
Surface morphology and its evolution during the plasma irradiation is known to have a large influence on the erosion and resulting lifetime of plasma-facing components as well as tritium retention. For instance, surface roughness can affect physical sputtering, re-deposition, as well as angular distributions of the sputtered species. In this study the effect of surface roughness is implemented into the 3D Monte-Carlo code ERO2.0. First modelling results for molybdenum (Mo) irradiated with deuterium (D) in the conditions foreseen for the planned experiments at the linear plasma device PSI-2 are presented. Using the constructed examples of surfaces with various (regular and fractal) roughness types it is shown that the effective sputtering yield decreases for rough surfaces in comparison to smooth ones. The angular distribution of particles escaping from the rough surface collimates with the increase of the surface structure's aspect ratio. Moreover, the modelling predicts flattening of the surface during the plasma irradiation due to the preferable re-deposition in the “valleys” and sputtering of the peak tops.
Original language | English |
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Pages (from-to) | 13-18 |
Number of pages | 6 |
Journal | Nuclear Materials and Energy |
Volume | 19 |
DOIs | |
State | Published - May 2019 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2019
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 supported by Czech Science Foundation project GA16-14228S and by the IT4Innovations Centre of Excellence project ( CZ.1.05/1.1.00/02.0070 ). The views and opinions expressed herein do not necessarily reflect those of the European Commission . The authors gratefully acknowledge the computing time granted through JARA-HPC on the supercomputer JUQUEEN at Forschungszentrum Jülich. 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 supported by Czech Science Foundation project GA16-14228S and by the IT4Innovations Centre of Excellence project (CZ.1.05/1.1.00/02.0070). The views and opinions expressed herein do not necessarily reflect those of the European Commission. The authors gratefully acknowledge the computing time granted through JARA-HPC on the supercomputer JUQUEEN at Forschungszentrum Jülich.
Funders | Funder number |
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Euratom research and training programme 2014–2018 | |
IT4Innovations Centre of Excellence | CZ.1.05/1.1.00/02.0070 |
Horizon 2020 Framework Programme | 633053 |
H2020 Euratom | |
Grantová Agentura České Republiky | GA16-14228S |