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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.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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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Proving DRACO will deliver
The United States is now closer than it has been in over five decades to launching the first nuclear thermal rocket into space, thanks to DRACO—the Demonstration Rocket for Agile Cislunar Orbit.
Zoltán Perkó, Danny Lathouwers, Jan Leen Kloosterman, Tim H. J. J. van der Hagen
Nuclear Science and Engineering | Volume 180 | Number 3 | July 2015 | Pages 345-377
Technical Note | doi.org/10.13182/NSE14-17
Articles are hosted by Taylor and Francis Online.
The nuclear community relies heavily on computer codes both in research and in the operation of installations. The results of such computations are useful only if they are augmented with sensitivity and uncertainty studies. This technical note presents some theoretical considerations regarding traditional first-order sensitivity analysis and uncertainty quantification involving constrained quantities. The focus is on linear constraints, which are often encountered in reactor physics problems due to energy and angle distributions, or the correlation between the isotopic abundances of elements.
A consistent theory is given for the derivation and interpretation of constrained first-order sensitivity coefficients; covariance matrix normalization procedures; their interrelation; and the treatment of constrained inputs with polynomial chaos expansion, which was the main motivation of this research. It is shown that if the covariance matrix violates the “generic zero column and row sum” condition, normalizing it is equivalent to constraining the sensitivities, but since both can be done in many ways, different sensitivity coefficients and uncertainties can be derived. This makes results ambiguous, underlining the need for proper covariance data. Furthermore, it is highlighted that certain constraining procedures can result in biased or unphysical uncertainty estimates. To confirm our conclusions, we demonstrate the presented theory on three analytical and two numerical examples including fission spectrum, isotopic distribution, and power distribution-related uncertainties, as well as the correlation between mass, volume, and density.