Engineering topics
Publications and source records attributed to Talou, Patrick.
This document reports on the results obtained during the 3-year AFCI-NEUP project #09-247, which aimed at improving the modeling and evaluation of nuclear data and their uncertainties for use in advanced nuclear energy transport simulations.
This project addresses three important gaps in existing evaluated nuclear data libraries that represent a significant hindrance against highly advanced modeling and simulation capabilities for the Advanced Fuel Cycle Initiative (AFCI). This project will: Develop advanced theoretical tools to compute prompt fission neutrons and gamma-ray characteristics well beyond average spectra and multiplicity, and produce new evaluated files of U and Pu isotopes, along with some minor actinides; Perform state-of-the-art fission cross-section modeling and calculations using global and microscopic model input parameters, leading to truly predictive fission cross-sections capabilities. Consistent calculations for a suite of Pu isotopes will be performed; Implement innovative data assimilation tools, which will reflect the nuclear data evaluation process much more accurately, and lead to a new generation of uncertainty quantification files. New covariance matrices will be obtained for Pu isotopes and compared to existing ones. The deployment of a fleet of safe and efficient advanced reactors that minimize radiotoxic waste and are proliferation-resistant is a clear and ambitious goal of AFCI. While in the past the design, construction and operation of a reactor were supported through empirical trials, this new phase in nuclear energy production is expected to rely heavily on advanced modeling and simulation capabilities. To be truly successful, a program for advanced simulations of innovative reactors will have to develop advanced multi-physics capabilities, to be run on massively parallel super- computers, and to incorporate adequate and precise underlying physics. And all these areas have to be developed simultaneously to achieve those ambitious goals. Of particular interest are reliable fission cross-section uncertainty estimates (including important correlations) and evaluations of prompt fission neutrons and gamma-ray spectra and uncertainties.
We review the results of NCSP sponsored data evaluation and integral data testing work performed during FY11 at LANL to support development and release of the ENDF/B-VII.1 Neutron Library.
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We have developed a new code CGMF , implementing a Monte Carlo version of the Hauser-Feshbach statistical theory of nuclear reactions and applied to the de-excitation of fission fragments. A parallel version of the code has been developed as well, and was used to produced the results presented in this report. Prompt fission neutron and gamma-ray characteristics have been computed for the thermal neutron-induced fission reactions on 235 U and 239 Pu. We discuss the status of these calculations and how the results compare to available experimental data.
We have performed sensitivity calculations using the CGMF code that implements the statistical Hauser-Feshbach equations in a Monte Carlo fashion to describe the de-excitation of fission fragments by emis sion of prompt neutrons and gamma rays. The specific importance of several input quantities is emphasized. An uncertainty quantification method, considering sources of uncertainty from both model calculations and experiments, is outlined.
The statistical theories - the Hauser-Feshbach model with the width fluctuation correction - play a central role in studying nuclear reactions in the fast energy region, hence the statistical model codes are essential for the nuclear data evaluations nowadays. In this paper, we revisit issues regarding the statistical model calculations in the fast energy range, such as the inclusion of the direct channels, and the energy averaged cross sections using different statistical assumptions. Although they have been discussed for a long time, we need more precise quantitative investigations to understand uncertainties coming from the models deficiencies in the fast energy range. For example, the partition of compound formation cross section into the elastic and inelastic channels depends on the elastic enhancement factor calculated from the statistical models. In addition, unitarity of S-matrix constrains this partition when the direct reactions are involved. Practically some simple assumptions, which many nuclear reaction model codes adopt, may work reasonably for the nuclear data evaluations. However, the uncertainties on the evaluated cross sections cannot go lower than the model uncertainty itself. We perform numerical simulations by generating the resonances using the R-matrix theory, and compare the energy (ensemble) averaged cross sections with the statistical theories, such as the theories of Moldauer, HRTW (Hofmann, Richert, Tepel, and Weidenmueller), KKM (Kawai-Kerman-McVoy), and GOE (Gaussian orthogonal ensemble).
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