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Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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
Latest Journal Issues
Nuclear Science and Engineering
Fusion Science and Technology
Study indicates pilot facility could significantly reduce waste volumes
Waste disposal start-up Deep Isolation and fusion tech company SHINE Technologies have announced the completion of a collaborative study assessing the costs of disposing of radioactive byproducts from a pilot spent nuclear fuel recycling facility.
David J. Kropaczek, Ryan Walden
Nuclear Science and Engineering | Volume 193 | Number 5 | May 2019 | Pages 523-536
Technical Paper | doi.org/10.1080/00295639.2018.1550970
Articles are hosted by Taylor and Francis Online.
The constraint annealing method is presented and demonstrated for the solution of large-scale, multiconstrained problems in light water reactor fuel cycle optimization. Constraint annealing is a penalty-free method that eliminates the need for traditional constraint weighting factors by treating each objective function and constraint as separate and concurrently solved minimization problems within a global optimization search framework. The current application seeks to demonstrate the effectiveness of constraint annealing for a complex core loading pattern design problem containing multiple objective functions and constraints without the need for additional ad hoc control parameters. Two problems of varying degrees of complexity are analyzed. The first problem is defined by a single objective function based on maximizing cycle energy with two constraints based on power peaking and peak rod exposure. The second problem expands upon the first by adding an additional objective function for vessel fluence and four additional constraints based on controlled power peaking, steaming rate, moderator temperature coefficient, and alternate source term. Results demonstrate that constraint annealing inherently addresses issues of scaling associated with different objective function and constraint formulations as well as the impact on cycle energy.