journal article·2026-05Open access

Image-based deformation measurements of fusion divertor armour under high heat flux loading

Adel Tayeb, Lloyd Fletcher, Mike Gorley, Allan Harte, Cory Hamelin

Abstract

Engineering components within a fusion reactor are subjected to extreme environments including high heat flux, strong magnetic fields and neutron irradiation. Simulations are required to predict the in-service lifetimes of fusion components and ensuring credibility of these simulations requires validation over testable domains. Divertors are responsible for extracting heat and ash from the fusion reaction and protecting the vacuum vessel from thermal loads. In this work, we conduct an image-based experimental assessment of a divertor armour component design under a steady-state, high heat flux of ~ 5 MW/{m}2 under vacuum conditions. The heat flux was applied to the water-cooled component using the Heating by Induction to Verify Extremes (HIVE) facility at the UK Atomic Energy Authority. We used digital image correlation (DIC) to measure the surface strain of the component and thermocouples to measure the temperature during the high heat flux pulse. We used synthetic image deformation simulations to analyse sources of random and systematic errors in our DIC measurements and to select DIC processing parameters for subsequent analysis. Our results show that DIC is a valuable tool for the validation of multi-physics simulations by providing information about the geometrical arrangement of components as well as high resolution data indicating areas of disagreement between the simulation and experiment. The results of our study are the first image-based simulation validation dataset for a divertor component under fusion relevant conditions.
Source: crossref · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Fusion materials and technologies · Magnetic confinement fusion research · Cold Fusion and Nuclear Reactions

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

UKAEA South Yorkshire, UKAEA, Rotherham, UK

Culham Campus, UKAEA, Abingdon, UK

References (41)

Show source-provided references
1. 10.1016/j.fusengdes.2022.11301010.1016/j.fusengdes.2022.113010 ↗
2. Schwer LE, Mair H, Crane R. Guide for verification and validation in computational solid mechanics. ASME 2006; 10.
3. 10.1017/CBO978051176039610.1017/CBO9780511760396 ↗
4. Kaizer J. Credibility assessment framework for critical boiling transition models: a generic safety case to determine the credibility of crucial heat flux and critical power models. US Nuclear Regulatory Commission, Office of Nuclear Reactor Regulation, 2019.
5. Lindquist EG. High heat flux testing facilities and an electrothermal-arc plasma source for plasma-material interaction studies and diagnostic development. 2020. https://trace.tennessee.edu/cgi/viewcontent.cgi?article=1009&context=utk_nuclpubs.
6. 10.1016/j.fusengdes.2023.11369910.1016/j.fusengdes.2023.113699 ↗
7. 10.1016/j.fusengdes.2023.11368910.1016/j.fusengdes.2023.113689 ↗
8. Sutton MA, Orteu JJ, Schreier H. Image correlation for shape, motion and deformation measurements: basic concepts, theory and applications. Springer Science & Business Media, 2009.
9. 10.1007/s11340-010-9418-310.1007/s11340-010-9418-3 ↗
10. Hild F, Roux S. Digital image correlation. In: Rastogi P, Hack E (eds) Optical methods for solid mechanics. A full-field approach. Vol. 367. Wiley-VCH, 2012, pp.183–228.
11. 10.1007/s11340-023-01006-010.1007/s11340-023-01006-0 ↗
12. 10.1016/j.optlaseng.2019.10594210.1016/j.optlaseng.2019.105942 ↗
13. 10.1007/s11340-021-00723-810.1007/s11340-021-00723-8 ↗
14. 10.1016/j.optlaseng.2009.03.00710.1016/j.optlaseng.2009.03.007 ↗
15. 10.1016/j.optlaseng.2009.08.01310.1016/j.optlaseng.2009.08.013 ↗
16. Jones EM, Iadicola MA. A good practices guide for digital image correlation. Int Digit Image Correlat Soc 2018; 10: 1–110.
17. 10.1016/j.ijsolstr.2011.02.01010.1016/j.ijsolstr.2011.02.010 ↗
18. 10.1177/030932471245340910.1177/0309324712453409 ↗
19. 10.1111/str.1235010.1111/str.12350 ↗
20. 10.1111/str.1247310.1111/str.12473 ↗
21. 10.1111/str.1239710.1111/str.12397 ↗
22. 10.1007/s11012-023-01706-w10.1007/s11012-023-01706-w ↗
23. 10.1007/s11340-023-00973-810.1007/s11340-023-00973-8 ↗
24. 10.1007/s11340-017-0259-110.1007/s11340-017-0259-1 ↗
25. 10.1007/s11340-015-0065-610.1007/s11340-015-0065-6 ↗
26. 10.1007/s11340-016-0158-x10.1007/s11340-016-0158-x ↗
27. 10.1111/str.1213410.1111/str.12134 ↗
28. 10.1111/str.1217010.1111/str.12170 ↗
29. 10.1177/030932472097114010.1177/0309324720971140 ↗
30. 10.1177/0309324721105908410.1177/03093247211059084 ↗
31. 10.1016/j.fusengdes.2015.03.03110.1016/j.fusengdes.2015.03.031 ↗
32. 10.1016/j.nme.2016.02.00510.1016/j.nme.2016.02.005 ↗
33. 10.1016/j.fusengdes.2019.03.01010.1016/j.fusengdes.2019.03.010 ↗
34. 10.1109/TMAG.2008.200294110.1109/TMAG.2008.2002941 ↗
35. 10.1016/j.ijsolstr.2011.09.02510.1016/j.ijsolstr.2011.09.025 ↗
36. 10.1016/j.fusengdes.2018.04.13210.1016/j.fusengdes.2018.04.132 ↗
37. 10.1016/j.fusengdes.2019.06.00710.1016/j.fusengdes.2019.06.007 ↗
38. 10.1016/j.fusengdes.2020.11183110.1016/j.fusengdes.2020.111831 ↗
39. ITER IO. ITER structural design criteria for in-vessel components (SDC-IC). G; 2012.
40. 10.1063/5.008422210.1063/5.0084222 ↗
41. 10.1021/ie50324a02710.1021/ie50324a027 ↗