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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Deep Space: The new frontier of radiation controls
In commercial nuclear power, there has always been a deliberate tension between the regulator and the utility owner. The regulator fundamentally exists to protect the worker, and the utility, to make a profit. It is a win-win balance.
From the U.S. nuclear industry has emerged a brilliantly successful occupational nuclear safety record—largely the result of an ALARA (as low as reasonably achievable) process that has driven exposure rates down to what only a decade ago would have been considered unthinkable. In the U.S. nuclear industry, the system has accomplished an excellent, nearly seamless process that succeeds to the benefit of both employee and utility owner.
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.