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Team brings quantum computing into FLiBe chemistry calculations
Researchers have reported using a combination of quantum and classical computing to calculate chemistry connected to tritium speciation in a FLiBe—lithium fluoride and beryllium fluoride—molten salt blanket, demonstrating a promising direction for unlocking tritium breeding in fusion machines.
Hyung Jin Shim, Chang Hyo Kim
Nuclear Science and Engineering | Volume 177 | Number 2 | June 2014 | Pages 184-192
Technical Paper | doi.org/10.13182/NSE13-29
Articles are hosted by Taylor and Francis Online.
It is very time-consuming to obtain a high-precision Monte Carlo (MC) estimate of the fuel temperature reactivity coefficient (FTC) through direct subtraction of two reactivity values from MC calculations at two different fuel temperatures. As an alternative to the direct subtraction MC estimate of the FTC, this paper presents a new method based on the adjoint-weighted correlated sampling technique. The new method translates the change in fuel temperature as the corresponding changes in both the microscopic cross sections and the transfer probabilities in scattering kernels described by the free gas model. The effectiveness of the new method is examined through continuous-energy MC neutronics calculations for pressurized water reactor pin cell and CANDU pressurized heavy water reactor lattice problems. The isotope-wise and reaction-type–wise contributions to the FTCs in the two problems are examined for two free gas models: the constant-cross-section and the resonance-cross-section models. It is demonstrated that the new MC method can predict the reactivity change due to fuel temperature variation as accurately as the conventional, more time-consuming direct subtraction MC method.