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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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Latest News
Lightbridge announces first U-Zr fuel rod samples extruded at INL
Lightbridge Corporation announced today that it has reached “a critical milestone” in the development of its extruded solid fuel technology. Coupon samples using an alloy of zirconium and depleted uranium—not the high-assay low-enriched uranium (HALEU) that Lightbridge plans to use to manufacture its fuel for the commercial market—were extruded at Idaho National Laboratory’s Materials and Fuels Complex.
L. Gilli, D. Lathouwers, J. L. Kloosterman, T. H. J. J. van der Hagen
Nuclear Science and Engineering | Volume 175 | Number 2 | October 2013 | Pages 172-187
Technical Paper | doi.org/10.13182/NSE12-92
Articles are hosted by Taylor and Francis Online.
In this paper we present the derivation and the application of an adaptive nonintrusive spectral technique for uncertainty quantification. Spectral techniques can be used to reconstruct stochastic quantities of interest by means of a Fourier-like expansion. Their application to uncertainty propagation problems can be performed in a nonintrusive fashion by evaluating a set of projection integrals that is used to reconstruct the spectral expansion. We present the derivation of a new adaptive quadrature algorithm, based on the definition of a sparse grid, which can be used to evaluate these spectral coefficients. This new adaptive algorithm is applied to a reference uncertainty quantification problem consisting of a coupled time-dependent model. The benefits of using such an adaptive method are analyzed and discussed from the uncertainty propagation and computational points of view.