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Conference Spotlight
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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Trump Media to merge with fusion startup TAE Technologies in $6B deal
Trump Media & Technology Group, the American media and technology company majority owned by President Trump, and California-based fusion company TAE Technologies, announced on Thursday the signing of a definitive merger agreement to combine in an all-stock transaction valued at more than $6 billion.
Andrew Holcomb, Luiz Leal, Farzad Rahnema, Dorothea Wiarda
Nuclear Science and Engineering | Volume 186 | Number 2 | May 2017 | Pages 147-155
Technical Paper | doi.org/10.1080/00295639.2016.1273632
Articles are hosted by Taylor and Francis Online.
A new method for constructing probability tables in the unresolved resonance region (URR) has been developed. This new methodology is an extensive modification of the single-level Breit-Wigner (SLBW) pseudo-resonance pair sequence method commonly used to generate probability tables in the URR. The new method uses a Monte Carlo process to generate many pseudo-resonance sequences by first sampling the average resonance parameter data in the URR and then converting the sampled resonance parameters to the more robust R-matrix limited (RML) format. For each sampled set of pseudo-resonance sequences, the temperature-dependent cross sections are reconstructed on a small grid around the energy of reference using the Reich-Moore formalism and the Leal-Hwang Doppler broadening methodology. The effective cross sections calculated at the energies of reference are then used to construct probability tables in the URR. The RML cross-section reconstruction algorithm has been rigorously tested for a variety of isotopes, including 16O, 19F, 35Cl, 56Fe, 63Cu, and 65Cu. The new URR method also produced normalized cross-section factor probability tables for 238U that were found to be in agreement with current standards. The modified 238U probability tables were shown to produce keff results in excellent agreement with several standard benchmarks, including the IEUMET- FAST-007 (BIG TEN), IEU-MET-FAST-003, and IEU-COMP-FAST-004 benchmarks.
