Competence support for technical non-proliferation and safeguards research at Uppsala University 2023-2025

Details

  • Period: 2023-01-01 – 2025-12-31
  • Funder: Swedish Radiation Safety Authority

Description

Project title: Competence support for technical non-proliferation and safeguards research at Uppsala University 2023-2025
Main applicant: Sophie Grape, Division of Applied Nuclear Physics
Co-applicants: Erik Branger, Vaibhav Mishra, Débora Montano Trombetta, Division of Applied Nuclear Physics
Grant amount: SEK 3 000 000 over a period of two years

This application concerns a continuation of the competence support that SSM has been granting Uppsala University (UU) for many years. The motivation for the grant is to continue the successful research activities conducted by the group in the field of safeguards for many years and to broaden it towards technical non-proliferation. The two recently established competence centres at UU – Alva Myrdal Centrum for nuclear disarmament (AMC) and ANltA (Akademiskt-industriellt kärntekniskt initiativ för att uppnå en framtida hållbar energiförsörjning) focused on the deployment of small modular reactors in Sweden – create a unique research environment that benefits the safeguards research group and supports the research activities. The funding will be used to support a number of positions, all of which include research as well as supervision of PhD students in ongoing and future projects (see separate PhD project application under same call by SSM).

The competence support includes an activity level of 25% for the research group leader to lead and coordinate the work, and partial salary support for two researchers and one postdoc. Within this project, we plan to conduct research in the areas of safeguards verification of spent nuclear fuel during regular inspections and before encapsulations and final storage, machine learning for safeguards purposes, safeguarding new generations of nuclear energy systems and technical nuclear non-proliferation.

Research activities include simulations of nuclear fuel, data analysis of fuel properties, development of machine learning algorithms to support nuclear safeguards evaluations, measurements of spent nuclear fuel at Clab, analysis of measurement data, and the development of nuclear safeguards approaches and verification techniques for future nuclear energy systems including small modular reactors.

Research results will be made available in primarily peer-reviewed scientific journals and at national and international conferences. It will also enable us to participate in international research collaborations in organisations such as IAEA, Esarda and INMM.

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