ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Aug 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
October 2026
Nuclear Technology
September 2026
Fusion Science and Technology
August 2026
Latest News
Front-end nuclear fuel supply cooperation: Turning allied interdependence into strategic advantage
The global nuclear revival, which is fueled by unprecedented demand for firm, affordable, dispatchable power for artificial intelligence and data center build-out, energy security imperatives, and climate commitments, has exposed a structural reality of the Western fuel cycle: No single allied nation currently possesses the full suite of front-end capabilities. From mining through conversion, enrichment, fabrication, and the emerging deconversion and metallization steps required for reactor fuels, capability is distributed across Canada, France, Japan, the United Kingdom, and the United States (collectively, the “Sapporo Five”), as well as a small group of close partners.
Thomas M. Sutton
Nuclear Science and Engineering | Volume 185 | Number 1 | January 2017 | Pages 174-183
Technical Paper | doi.org/10.13182/NSE15-131
Articles are hosted by Taylor and Francis Online.
In the study of Monte Carlo statistical uncertainties for iterated-fission-source calculations, an important distinction is made between the real and the apparent variances. The former is the actual variance of a Monte Carlo calculation result, while the latter is an estimate of the former obtained using the results of the fission generations in the formula for uncorrelated random variates. For years it has been known that the apparent variance is a biased estimate of the real variance, and the reason for the bias has been understood. More recently, several authors have noted various interesting phenomena regarding the apparent and the real variances and the relationships among them. Some of these are an increase in the apparent variance near surfaces with reflecting boundary conditions, a nonuniform spatial distribution of the ratio of the apparent-to-real variance, the dependence of this ratio on the size of the region over which the result is tallied, and a rate of convergence of the real variance that is less than the inverse of the number of neutron histories run. This paper discusses a theoretical description of the Monte Carlo process using a discretized phase-space and then uses it to explain the causes of these phenomena.