![]() |
![]() |
University of Birmingham > Talks@bham > Particle Physics Seminars > Remote Reactor Monitoring via Antineutrinos
Remote Reactor Monitoring via AntineutrinosAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Prof Ian Kenyon. Nuclear reactors and neutrino research have enjoyed a long and productive history together. This ‘partnership’ began in the 1950s, when Cowan and Reines used the Savannah River reactors to confirm the existence of (anti)neutrinos. In the decades since, a series of reactor neutrino experiments—such as Chooz, KamLAND, and Daya Bay—have given us insight into the properties of neutrinos. Complementing this fundamental scientific research, reactor antineutrinos can also be used for the practical purpose of nuclear non-proliferation. The copious flux of antineutrinos produced by a nuclear reactor provides an unshieldable signal. With a suitable detector, this signal can be used to discover clandestine reactors and monitor known reactors from a distance. For non-proliferation applications, it is useful to determine both the existence of a clandestine reactor (potentially in the presence of a known reactor), and the distance to that reactor. In this presentation, I will discuss potential designs for such a detector, and the R&D underway to realise those designs. I will also present the results from studies that demonstrate the potential for discovering and ranging a distant reactor. _ This talk is part of the Particle Physics Seminars series. This talk is included in these lists:Note that ex-directory lists are not shown. |
Other listsPhysics and Astronomy Colloquia Centre for Systems Biology Coffee Mornings Postgraduate Seminars in the School of Computer ScienceOther talksTitle tbc TBA Kneser Graphs are Hamiltonian Kolmogorov-Smirnov type testing for structural breaks: A new adjusted-range based self-normalization approach Sylow branching coefficients for symmetric groups Parameter estimation for macroscopic pedestrian dynamics models using trajectory data |