EPJ Web of Conf.
Volume 284, 202315th International Conference on Nuclear Data for Science and Technology (ND2022)
|Number of page(s)||4|
|Section||Thermal Neutron Scattering|
|Published online||26 May 2023|
Validation of S(α, β) thermal neutron scattering libraries using pulsed-neutron die-away experiments
1 Gaerttner LINAC Center, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
2 Naval Nuclear Laboratory, P.O. Box 79, West Mifflin, PA 15122, USA
* e-mail: firstname.lastname@example.org
Published online: 26 May 2023
Validation of the accuracy of S(α, β) thermal scattering law (TSL) evaluations for moderator materials is an important task for the development of high-performance nuclear engineering systems. Many recent thermal neutron scattering evaluations have had limited experimental validation. Like other nuclear data, validation of TSL libraries has historically been by integral criticality benchmarks. While sufficient for general study, these benchmarks often have limited sensitivity to the tested TSLs, and compounding uncertainties from other nuclear data can make validation ambiguous. In some cases, no criticality benchmarks exist that are sensitive to the TSLs of interest. With the development of high-performance next-generation thermal nuclear reactors, alternative validation of applicable TSLs is of high importance. By performing thermal neutron measurements via pulsed-neutron die-away (PNDA) experiments, along with parallel simulations, the integral performance of various TSL evaluations can be compared to measured experimental data. An experimental testbed using a D-T neutron generator, moderator sample, and thermal neutron detector was assembled at Rensselaer Polytechnic Institute. A Thermo Scientific D211 Deuterium-Tritium Neutron generator is used to generate 10 μs neutron pulses. Various targets of different sizes and geometries are used to moderate the neutrons. Multiple detector types and configurations were tested to optimize the experiment. The room-temperature polyethylene TSL evaluation is well vetted and is similar across different evaluations. This makes it an ideal evaluation to compare with the experimental results.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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