L3:RTM.MCH.P19.06: Neutronics UQ

Technical Report · Mon Sep 30 04:00:00 EDT 2019

DOI:https://doi.org/10.2172/3002118· OSTI ID:3002118

Ducru, Pablo ^[1]; Alhajri, Abdulla ^[1]; Meyer, Isaac ^[1]; Sobes, Vladamir ^[2]; Forget, Benoit ^[1]

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1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
2. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

This report summarizes some of the work performed in the last year on the nuclear data uncertainty tasks using the multipole representation. This approach was proposed to provide a simple and integrated way of evaluating the nuclear data uncertainty in a Monte Carlo simulation and evaluating their impact on multigroup cross sections. As previously described, the windowed multipole format allows for a resonance based representation of the cross sections with direct Doppler broadening. This representation also lends itself nicely to the evaluation of sensitivities of resonance parameters and the direct perturbation of resonance parameters in the simulation environment. Both of these approaches rely on the need of conversion of the covariance data (File 32 of the ENDF library) into a pole and residues form: i.e. into a multipole covariance. Section 5 details the current pathways that have been used so far to achieve this. In order to verify the conversion process of the covariance data, the sensitivies to the resonance parameters and the sampling from these parameters, an analytical benchmark of the slowing process was developed. The benchmark provides a closed-form solution for the flux in the presence of Hydrogen and multiple resonant nuclides. Section 2 details the analytical benchmark and provides the closed-form solutions for the flux and its sensitivity to resonance parameters. A verification of the proposed methodology is performed and compared with the analytic solution to demonstrate the accuracy of the benchmark and the applicability of our embedded resonance perturbation approach in a small Monte Carlo code. Papers are currently being drafted documenting the benchmark and the generation of sensitivities. As paths to best generate multipole covariance matrices are being compared, we also explored new methods to propagate nuclear data uncertainty across the Monte Carlo neutron transport calculation. Section 4 studies the use of multipole covariance matrices to perform sensitivity analysis. Section 3.2 documents the results of our investigations into a new way of propagating nuclear data uncertainty across Monte Carlo transport simulations by sampling new epistemic cross sections for each new neutron.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 3002118
• Report Number(s): CASL-U--2019-2073-000
• Country of Publication: United States
• Language: English

Related Subjects

73 NUCLEAR PHYSICS AND RADIATION PHYSICS
97 MATHEMATICS AND COMPUTING