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On moving fast and breaking things
Craig Piercycpiercy@ans.org
So much of what is happening in federal nuclear policy these days seems driven by a common approach popularized in the technology sector. Silicon Valley calls it “move fast and break things,” a phrase originally associated with Facebook’s early culture under Mark Zuckerberg. The idea emerged in the early 2000s as software companies discovered that rapid iteration, frequent experimentation, and a willingness to tolerate failure could dramatically accelerate innovation. This philosophy helped drive the growth of the social media, smartphones, cloud computing, and digital platforms that now underpin modern economic and social life.
Today, that mindset is also influencing federal nuclear policy. The Trump administration views accelerated nuclear deployment as part of a broader competition with China for technological and AI leadership. In that context, it seems willing to accept greater operational risk in pursuit of strategic advantage and long-term economic and security objectives.
Ilham Variansyah, Benjamin R. Betzler, William R. Martin
Nuclear Science and Engineering | Volume 194 | Number 11 | November 2020 | Pages 1025-1043
Technical Paper | doi.org/10.1080/00295639.2020.1743578
Articles are hosted by Taylor and Francis Online.
Multigroup constants for deterministic methods that preserve the time-dependent physics of the neutron transport equations are derived. Alternative multigroup constant weighting spectra are discussed: (1) the fundamental k-eigenfunction, (2) the fundamental α-eigenfunction, and (3) a composite of several α-modes. To generate the fundamental α-eigenfunction for calculating the multigroup constants, a static fundamental α-eigenvalue method is implemented into the open source Monte Carlo code OpenMC. Several static and kinetic problems are devised to verify the implementations and to investigate the relative performance of the alternative multigroup constant weighting spectra. Results emphasize that as a multigroup constant weighting spectrum, the fundamental α-eigenfunction offers physical characteristics that make it advantageous (in producing accurate solutions) over the typically used fundamental k-eigenfunction.