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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Fusion Science and Technology
Latest News
The Frisch-Peierls memorandum: A seminal document of nuclear history
The Manhattan Project is usually considered to have been initiated with Albert Einstein’s letter to President Franklin Roosevelt in October 1939. However, a lesser-known document that was just as impactful on wartime nuclear history was the so-called Frisch-Peierls memorandum. Prepared by two refugee physicists at the University of Birmingham in Britain in early 1940, this manuscript was the first technical description of nuclear weapons and their military, strategic, and ethical implications to reach high-level government officials on either side of the Atlantic. The memorandum triggered the initiation of the British wartime nuclear program, which later merged with the Manhattan Engineer District.
Ander Gray, Andrew Davis, Edoardo Patelli
Fusion Science and Technology | Volume 77 | Number 7 | November 2021 | Pages 802-812
Technical Paper | doi.org/10.1080/15361055.2021.1895667
Articles are hosted by Taylor and Francis Online.
In this paper we perform nuclear data uncertain propagation with Total Monte Carlo, where the transport simulation is repeated for random evaluations of the data. The Oktavian Iron, Oktavian Nickel, and the Frascati Neutron Generator (FNG) neutron streaming SINBAD benchmarks were evaluated with OpenMC. Gaussian random deviates were drawn from the ENDF/B-VII.1 and TENDL-2017 libraries where the covariances were available. Uncertainty from multiple nuclides was propagated simultaneously assuming inter-nuclide independence. When the individual statistical uncertainty is negligible compared to the data uncertainty, then standard probability theory may be applied. If this is not the case and both need to be considered, we use Imprecise Probabilities (IP) to perform further analysis. We show how uncertain experimental data may be compared to uncertain simulation in the context of IP, and show how an uncertainty-based sensitivity analysis can be performed with IP.