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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1985

Neutron-induced 2.2 MeV background in gamma ray telescopes

Neutron-induced gamma ray production is an important source of background in Compton scatter gamma ray telescopes where organic scintillator material is used. Most important is deuteron formation when atmospheric albedo and locally produced neutrons are thermalized and subsequently absorbed in the hydrogenous material. The resulting 2.2 MeV gamma ray line radiation essentially represents a continuous isotropic source within the scintillator itself. Interestingly, using a scintillator material with a high hydrogen-to-carbon ratio to minimize the scintillator material with a high hydrogen-to-carbon ratio to minimize the neutron-induced 4.4 MeV carbon line favors the np reaction. The full problem of neutron-induced background in Compton scatter telescopes has been previously discussed. Results are presented of observations with the University of California balloon-borne Compton scatter telescope where the 2.2 MeV induced line emission is prominently seen.

Zanrosso, E. M.↗

DOE OSTI2024

Embedding Neural Thermal Scattering (NeTS) Modules in SERPENT for Higher Fidelity Advanced Reactor Analysis

When a neutron born in fission thermalizes to the order of $k$ $B$ $T$, it’s de-Broglie wavelength and energy approach the order of inter-atomic spacing and elementary lattice oscillations, respectively. $S$($a,β,t$) or the scattering law, uuantify these temperature-dependent crystallographic contributions to total cross section (or reaction rate). In a Monte Carlo analysis, cumulative distribution functions (CDFs) of $S$($a,β,t$) are loaded to memory from “A Compact ENDF” (ACE) files for stochastically selecting thermal scattered neutron trajectories. In this work, novel neural thermal scattering (NeTS) modules for $S$($a,β,t$) CDFs are designed, trained, serialized and embedded within SERPENT using Python’s limited C-API for on-the-fly deployment of crystalline graphite $S$($a,β,t$) sampling. Torchscript tracing and Numba just-in-time (JIT) compilation streamline neural inference on NVIDIA GPUs with CUDA libraries. Demonstrations of bare sphere thermalization of fast and thermal sources show excellent agreement between embedded NeTS in SERPENT and MCNP. With an explicit model of the reactor, NeTS can predict on-the-fly changes in TREAT neutron spectra as a function of local temperature, which can serve to improve transient and accident predictions in a multiphysics analysis framework. This framework can be further extended to account on-the-fly for changes in local graphitic microstructure to scattering cross sections, and outlines a novel coupling of modern machine learning with state-of-the-art reactor physics methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Status of the Atlas of Neutron Resonances [Slides]

The Atlas of Neutron Resonances is the most comprehensive compilation of neutron resonances, thermal cross sections, resonance integrals and Maxwellian averaged cross sections generally available. For decades, the Atlas was carefully curated and maintained by Dr. Said Mughabghab who sadly passed on during the summer of 2018 after publishing the 2018 edition of the Atlas . We are continuing the development of this important compendium. To a large extent, the Atlas book is generated from a series of text files given in a single purpose domain-specific format. Therefore, we developed a software API and began the systematic assessment of the Atlas files. With this work past, we are now focusing on new efforts to expand the quality and scope of the Atlas . Current and recently completed projects include a cross comparison of the Atlas bibliography with Nuclear Science References and the EXFOR data library, a better determination of average resonance parameters, and using machine learning to assess the correctness of the spin group assignments of resonances tabulated in the Atlas .