EPJ Web Conf.
Volume 247, 2021PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
|Number of page(s)||9|
|Published online||22 February 2021|
EXPERIMENTAL VALIDATION OF NUCLEAR REACTION DATA FOR INVENTORY SIMULATIONS ON MOLYBDENUM
Culham Centre for Fusion Energy, UKAEA, Culham Science centre, Abingdon, Oxfordshire, UK, OX14 3DB
Published online: 22 February 2021
Molybdenum is being considered as a potential material for future nuclear fusion experiments and power plants. It has good thermo-mechanical properties and can be easily fabricated, making it attractive as an alternative first wall material to tungsten, which is the current leading candidate. Unfortunately, according to simulations, fusion-neutron irradiated Mo may become too activated during reactor operation to maintain the objective of fusion of avoiding the generation of long-term, higher-level radioactive waste.
However, these simulated predictions rely heavily on having high-quality, accurate nuclear reaction data. For example, reliable simulations of the radiological response of isotopically-tailored Mo would be required by reactor designers and eventually nuclear regulators to assess if it is a viable low-activation fusion solution (in comparison to pure Mo). In recent years, UKAEA has developed benchmarks to test and validate the FISPACT-II inventory code and the input international nuclear data libraries against experimental measurements. This paper presents nuclear code prediction comparisons to new data acquired from γ-spectroscopy measurements of Mo irradiated in the ASP 14 MeV facility at AWE in the UK.
Results demonstrate that FISPACT-II predictions for Mo are remarkably accurate; particularly for activity generated from the shorter-lived radionuclides explored by these laboratory experiments, such as 91Mo and 97Nb, etc., and their metastable isomeric states.
Key words: Molybdenum / fusion irradiation / experimental validation / nuclear data
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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