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
September 2026
Nuclear Technology
Fusion Science and Technology
August 2026
Latest News
Undeclared uranium hitches a ride on cobalt exports from Congo, study says
Philippe (left) and Manzuk quantified the amount of uranium that has been exported from the DRC in cobalt shipments or left behind in the environment. (Photo: Joel Hallberg/UW–Madison)
Researchers at the University of Wisconsin–Madison and Princeton University have published a study in Nature Communications that calls attention to a blind spot in nuclear nonproliferation: The Democratic Republic of the Congo (DRC) has exported thousands of metric tons of uranium, and there is no accounting for where it has gone.
In partnership with Lighthouse Reports and the Financial Times, UW–Madison nuclear engineering professor and nuclear security expert Sébastien Philippe and Ryan Manzuk, a geologist and research fellow in Philippe’s group and at Princeton, conducted the study using countrywide mineralization and geochemical data.
Gee-Yong Park, Heung-Seop Eom, Seung Cheol Jang, Hyun Gook Kang
Nuclear Technology | Volume 183 | Number 1 | July 2013 | Pages 107-118
Technical Paper | Nuclear Plant Operations and Control | doi.org/10.13182/NT13-A16996
Articles are hosted by Taylor and Francis Online.
This paper describes a method of estimating the probability of failure for trip-functioning software of a fully digitalized reactor protection system. The Bayesian inference is used to estimate and update the probability of software failure along the software development life cycle. At the requirements and design phases, the probability of software failure is estimated from qualitative quality information based on a specific verification and validation process. This probability of failure is updated at the implementation/testing phases, based on the test data for trip functions implemented by software.
