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Mike Kramer: Navigating power deals in the new data economy
Mike Kramer has a background in finance, not engineering, but a combined 20 years at Exelon and Constellation and a key role in the deals that have Meta and Microsoft buying power from Constellation’s Clinton and Crane sites have made him something of a nuclear expert.
Kramer spoke with Nuclear News staff writer Susan Gallier in late August, just after a visit to Clinton in central Illinois to celebrate a power purchase agreement (PPA) with Meta that closed in June. As Constellation’s vice president for data economy strategy, Kramer was part of the deal-making—not just the celebration.
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.