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Russia withdraws from 25-year-old weapons-grade plutonium agreement
Russia’s lower house of Parliament, the State Duma, approved a measure to withdraw from a 25-year-old agreement with the United States to cut back on the leftover plutonium from Cold War–era nuclear weapons.
S. I. Abdel-Khalik, Pierre-André Haldy, Anil Kumar
Fusion Science and Technology | Volume 5 | Number 2 | March 1984 | Pages 189-208
Technical Paper | Experimental Devices | doi.org/10.13182/FST84-A23093
Articles are hosted by Taylor and Francis Online.
The first in a series of fusion-fission hybrid blanket assemblies to be tested in the LOTUS test facility at the Swiss Federal Institute of Technology in Lausanne (EPFL) is described. The aim of the EPFL program is to conduct integral neutronic benchmark experiments with design features resembling genuine blanket design approaches. The assembly described here simulates fission-suppressed thorium blankets of the type used in direct enrichment hybrid designs. The neutronic studies on which the design is based are described in detail. The blanket assembly is a parallelepiped 85 em thick, 100 em high, and 140 em wide. It is to be placed in front of a Haefely sealed neutron generator with an intensity of 5 × 1012 14-MeV neutron/s. It consists of a 2-mm-thick stainless steel sheet simulating the first wall, followed by a 100-mm-thick lead plate for neutron multiplication, a 35-mm-thick spectrum adjustment zone of lithium carbonate blocks encased in aluminum, a 277.2-mm-thick fissile breeding zone of aluminum-clad thorium oxide rods, a 150-mm-thick tritium breeding zone of lithium carbonate blocks encased in aluminum, a 250-mm-thick graphite reflector, and, finally, a 35-mm-thick scavenging zone of lithium carbonate. The experiments were to begin in 1984. They will provide integral neutronic data for comparison with predictions of current calculational techniques and cross-section libraries. Such comparison will provide an estimate of the uncertainties in calculated hybrid blanket neutronic performance and, together with sensitivity studies, will help identify specific areas of data and/or modeling improvement.