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2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
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Investing in what comes next
Hash Hashemian
The 2026 ANS Annual Conference, “Net Out and Power Up,” brought the nuclear community together in Denver at the end of May. Over four days at the Sheraton Denver, we heard from exceptional speakers on the most consequential questions facing our field; how fusion and fission can complement each other, how to meet surging electricity demand, and what it takes to sustain American nuclear leadership. The embedded topicals on nuclear fuels and materials and on fusion energy added real technical depth. It was exactly the kind of gathering that reminds us why this community is so remarkable.
That energy and commitment is precisely what I want to channel as I close out my term as president of the American Nuclear Society. Because sustaining it year after year, conference after conference, requires more than enthusiasm. It requires investment.
Dong Hyuk Lee, Hyung Jin Shim, Chang Hyo Kim
Nuclear Science and Engineering | Volume 187 | Number 2 | August 2017 | Pages 154-165
Technical Paper | doi.org/10.1080/00295639.2017.1307031
Articles are hosted by Taylor and Francis Online.
The continuous-energy Monte Carlo (MC) sensitivity and uncertainty (S/U) analysis conducted using the multigroup covariance matrices has a theoretical pitfall in that it is inconsistent with the principle of continuous-energy MC neutronics calculations because the use of the multigroup covariance matrices means treating covariance data as multigroup variables rather than continuous-energy variables. As a way to get around this deficiency and perform the MC S/U analysis on the theoretically consistent principle, this paper presents a new continuous-energy MC S/U formulation which directly utilizes the continuous-energy covariance data in the evaluated nuclear data libraries instead of the multigroup covariance matrices produced by nuclear data processing codes. The validity of the new MC S/U formulation is examined in terms of the input-nuclear-data-induced k uncertainty of the Godiva critical assembly and the TMI-1 pin cell problem by inputting the continuous-energy covariance data of nuclides involved directly into the continuous-energy MC transport calculations by a Seoul National University MC code, McCARD.