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Panelists discuss U.S. path to criticality in ANS webinar
The American Nuclear Society recently hosted a panel discussion featuring prominent figures from the nuclear sector who discussed the industry’s ongoing push for criticality.
Yasir Arafat, chief technical officer of Aalo Atomics; Jordan Bramble, CEO of Antares Nuclear; and Rita Baranwal, chief nuclear officer of Radiant Industries, participated in the discussion and covered their recent progress in the Department of Energy’s Reactor Pilot Program. Nader Satvat, director of nuclear systems design at Kairos Power, gave an update on the company’s ongoing demonstration projects taking place outside of the landscape of DOE authorization.
E. E. Bende, A. H. Hogenbirk, J. L. Kloosterman, H. van Dam
Nuclear Science and Engineering | Volume 133 | Number 2 | October 1999 | Pages 147-162
Technical Paper | doi.org/10.13182/NSE99-A2078
Articles are hosted by Taylor and Francis Online.
An analytical expression was derived for the average Dancoff factor of a fuel kernel (Cfk) in a pebble of a high-temperature gas-cooled reactor. This Dancoff factor accounts for the probability that a neutron escaping from a fuel kernel enters another fuel kernel, in the same pebble or in other pebbles, without colliding with a moderator nucleus in between. If the fuel zone of the pebble is thought to be of infinite dimensions, the Dancoff factor becomes equal to the so-called infinite-medium Dancoff factor Cfk. The Cfk has been determined by the evaluation of three existing analytical expressions and by two Monte Carlo calculations performed with the MCNP-4A code, for various coated-particle densities. The Dancoff factor Cfk can be written as Cfk times a correction factor. The latter has been calculated for different fuel zone radii and pebble shell thicknesses. For the standard pebble, Cfk as a function of the number of coated particles has been calculated both analytically and with MCNP. The results of both methods are in good agreement. The analytical calculation method is preferred because it consumes practically no CPU time and obviates the building of MCNP models.