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.
Pradeep Ramuhalli, Surajit Roy, Jangbom Chai
Nuclear Science and Engineering | Volume 182 | Number 2 | February 2016 | Pages 228-242
Technical Paper | doi.org/10.13182/NSE14-127
Articles are hosted by Taylor and Francis Online.
This paper describes research toward developing prognostics technologies for light water nuclear power reactor components. The focus of this paper is on passive components (those that do not need to change state or move to perform their function), although the technologies are applicable to other classes of components as well. A prototypic failure mechanism (high-cycle fatigue) is used to focus the efforts and provide context for the development effort. A Bayesian framework is proposed for the prognostics of remaining useful life and applied to simulated data sets representing nondestructive measurements of high-cycle fatigue damage. The initial results of the prognostics based on simulated data sets are presented.