Scattering-coupled adaptive source biasing for deep-penetration neutron arrival-spectrum calculations

Reliable neutron arrival spectra are needed for space radiation assessment and radiation protection, but deep-penetration Monte Carlo calculations often yield highly uneven uncertainties across energy groups. In analog Monte Carlo simulations, the nonuniform source spectrum and the energy-dependent transport behavior of neutrons can lead to relative uncertainties that differ by tens or even hundreds of times among arrival energy groups. To address this imbalance in arrival-spectrum uncertainties for deep-penetration transport, this study proposes a scattering-coupled adaptive source biasing (SC-ASB) method that uses a source-to-target response matrix to retain scattering-induced coupling from high-energy source neutrons to lower-energy arrival groups. The biased source distribution is derived by minimizing the sum of relative statistical errors (RSEs) subject to normalization and two-sided error-balance constraints, while the original source expectation is preserved by weight correction. Atmospheric neutron transport calculations showed that SC-ASB improved the relative-error distribution and increased computational efficiency. For a 15 km source height case, the figure of merit was 276 times that of analog simulation. Compared with uniform source biasing, SC-ASB showed better adaptability across source heights. In contrast to the WW variance-reduction method, SC-ASB provides more effective balancing of the RSEs across different energy groups. The method provides a variance-reduction framework for spectrum-resolved deep-penetration neutron transport.

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Publication Details

Journal
Annals of Nuclear Energy
Published
2026-10-06
DOI
https://doi.org/10.1016/j.anucene.2026.112910
Primary Topic
Nuclear reactor physics and engineering
Type
article
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article

Scattering-coupled adaptive source biasing for deep-penetration neutron arrival-spectrum calculations

Linhe Du, Xiaoqiang Li, Xinliang Pang, Peng Li et al.
Annals of Nuclear Energy
Nuclear reactor physics and engineering
article

Scattering-coupled adaptive source biasing for deep-penetration neutron arrival-spectrum calculations

Linhe Du, Xiaoqiang Li, Xinliang Pang, Peng Li, Yanbin Wang, Xiong Zhang
article en

Abstract

Reliable neutron arrival spectra are needed for space radiation assessment and radiation protection, but deep-penetration Monte Carlo calculations often yield highly uneven uncertainties across energy groups. In analog Monte Carlo simulations, the nonuniform source spectrum and the energy-dependent transport behavior of neutrons can lead to relative uncertainties that differ by tens or even hundreds of times among arrival energy groups. To address this imbalance in arrival-spectrum uncertainties for deep-penetration transport, this study proposes a scattering-coupled adaptive source biasing (SC-ASB) method that uses a source-to-target response matrix to retain scattering-induced coupling from high-energy source neutrons to lower-energy arrival groups. The biased source distribution is derived by minimizing the sum of relative statistical errors (RSEs) subject to normalization and two-sided error-balance constraints, while the original source expectation is preserved by weight correction. Atmospheric neutron transport calculations showed that SC-ASB improved the relative-error distribution and increased computational efficiency. For a 15 km source height case, the figure of merit was 276 times that of analog simulation. Compared with uniform source biasing, SC-ASB showed better adaptability across source heights. In contrast to the WW variance-reduction method, SC-ASB provides more effective balancing of the RSEs across different energy groups. The method provides a variance-reduction framework for spectrum-resolved deep-penetration neutron transport.

Annals of Nuclear EnergyVol. 242
Openalex Percentile: Top 16%
Nuclear reactor physics and engineering
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Scattering-coupled adaptive source biasing for deep-penetration neutron arrival-spectrum calculations — Linhe Du, Xiaoqiang Li, et al. · Annals of Nuclear Energy (2026) | TGRS Research Map | TGRS