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Godzilla is helping ITER prepare for tokamak assembly
ITER employees stand by Godzilla, the most powerful commercially available industrial robot available. (Photo: ITER)
Many people are familiar with Godzilla as a giant reptilian monster that emerged from the sea off the coast of Japan, the product of radioactive contamination. These days, there is a new Godzilla, but it has a positive—and entirely fact-based—association with nuclear energy. This one has emerged inside the Tokamak Assembly Preparation Building of ITER in southern France.
A. Ziya Akcasu, Alison M. Stolle
Nuclear Science and Engineering | Volume 113 | Number 1 | January 1993 | Pages 31-55
Technical Paper | doi.org/10.13182/NSE93-A23992
Articles are hosted by Taylor and Francis Online.
The application of the Langevin equation method to the study of fluctuations in the space- and velocity-dependent neutron density as well as in the detector outputs in nuclear reactors is presented. In this case, the Langevin equation is the stochastic linear neutron transport equation with a space- and velocity-dependent random neutron source, often referred to as the noise equivalent source (NES). The power spectral densities (PSDs) of the NESs in the transport equation, as well as in the accompanying detection rate equations, are obtained, and the cross- and auto-power spectral densities of the outputs of pairs of detectors are explicitly calculated. The transport-level expression for the R(ω) ratio measured in the 252Cf source-driven noise analysis method is also derived. Finally, the implementation of the Langevin equation approach at different levels of approximation is discussed, and the stochastic one-speed transport and one-group P1 equations are derived by first integrating the stochastic transport equation over speed and then eliminating the angular dependence by a spherical harmonics expansion. By taking the large transport rate limit in the P1 description, the stochastic diffusion equation is obtained as well as the PSD of the NES in it. This procedure also leads directly to the stochastic Fick’s law.