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.
Division Spotlight
Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
Meeting Spotlight
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
Latest Magazine Issues
May 2024
Jan 2024
Latest Journal Issues
Nuclear Science and Engineering
June 2024
Nuclear Technology
Fusion Science and Technology
Latest News
The busyness of the nuclear fuel supply chain
Ken Petersenpresident@ans.org
With all that is happening in the industry these days, the nuclear fuel supply chain is still a hot topic. The Russian assault in Ukraine continues to upend the “where” and “how” of attaining nuclear fuel—and it has also motivated U.S. legislators to act.
Two years into the Russian war with Ukraine, things are different. The Inflation Reduction Act was passed in 2022, authorizing $700 million in funding to support production of high-assay low-enriched uranium in the United States. Meanwhile, the Department of Energy this January issued a $500 million request for proposals to stimulate new HALEU production. The Emergency National Security Supplemental Appropriations Act of 2024 includes $2.7 billion in funding for new uranium enrichment production. This funding was diverted from the Civil Nuclear Credits program and will only be released if there is a ban on importing Russian uranium into the United States—which could happen by the time this column is published, as legislation that bans Russian uranium has passed the House as of this writing and is headed for the Senate. Also being considered is legislation that would sanction Russian uranium. Alternatively, the Biden-Harris administration may choose to ban Russian uranium without legislation in order to obtain access to the $2.7 billion in funding.
Robert Nshimirimana, Ajith Abraham, Gawie Nothnagel, Andries Engelbrecht
Nuclear Technology | Volume 207 | Number 1 | January 2021 | Pages 147-166
Technical Paper | doi.org/10.1080/00295450.2020.1740562
Articles are hosted by Taylor and Francis Online.
A manual approach to radiography process optimization is a time-consuming and labor-intensive process. Therefore, a virtual environment in which all of the processes of optimization for a desired radiography experiment or setup are conducted is highly desirable. Such an environment should be able to provide the capability to arrive at radiographic scanning parameters that are optimized to within preset criteria for design purposes. In this paper, a simplified approach toward achieving this is described, and calculated radiography results are benchmarked against experiments. A ray-tracing technique combined with the exponential law of attenuation was used to provide the primary function of such a virtual environment, which is the modeling of the radiography system. Radiography quality parameters such as contrast, penetration, unsharpness, and resolution were calculated using predefined definitions and fed directly into a particle swarm optimization routine that searched for the best radiography design parameters in an iterative feedback loop between the simulator and the optimizer modules. The aim of this paper is to show that a rather simple radiography simulation approach can already provide sufficient data for system design optimization purposes without the need to develop or utilize a comprehensive, competitive radiography simulator. The simplified approach provides a direct “uncomplicated” virtual environment for basic radiography training and basic experimental planning.