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Division Spotlight
Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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!
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Latest News
Norway’s Halden reactor takes first step toward decommissioning
The government of Norway has granted the transfer of the Halden research reactor from the Institute for Energy Technology (IFE) to the state agency Norwegian Nuclear Decommissioning (NND). The 25-MWt Halden boiling water reactor operated from 1958 to 2018 and was used in the research of nuclear fuel, reactor internals, plant procedures and monitoring, and human factors.
Workshop
Thursday, April 8, 2021|11:45AM–1:00PM EDT
Session Chair:
Xu Wu
Alternate Chair:
Ishita Trivedi
Session Organizer:
Edward Chen (NC State Univ.)
Track Organizer:
Session Producers:
Roberto Fairhurst-Agosta (Univ. of Ill., Urbana-Champaign)
Modern predictive simulations have a special focus on the systematic treatment of input, model and data uncertainties and their propagation through a computational model to produce predictions of Quantities-of-Interest (QoIs) with quantified uncertainty. Although the modeling of nuclear reactors has made tremendous progress, there are always discrepancies between ideal in silico designed systems and real-world manufactured ones. As a consequence, uncertainties must be quantified along with simulation to facilitate optimal design and decision making, ensure robustness, performance and safety margins. This workshop will provide an overview of the fundamental concepts in Uncertainty Quantification (UQ) and Sensitivity Analysis (SA), as well as comparative reviews of forward/inverse UQ and SA approaches. Topics on quantifying prediction uncertainties in Machine Learning models will also be briefly covered.
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