| Autor: |
Benedikt Schmitz, Stefan Scheuren |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Journal of Nuclear Engineering, Vol 5, Iss 2, Pp 114-127 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2673-4362 |
| DOI: |
10.3390/jne5020009 |
| Popis: |
The development of compact neutron sources for applications is extensive and features many approaches. For ion-based approaches, several projects with different parameters exist. This article focuses on ion-based neutron production below the spallation barrier for proton and deuteron beams with arbitrary energy distributions with kinetic energies from 3 MeV to 97 MeV. This model makes it possible to compare different ion-based neutron source concepts against each other quickly. This contribution derives a predictive model using Monte Carlo simulations (an order of 50,000 simulations) and deep neural networks. It is the first time a model of this kind has been developed. With this model, lengthy Monte Carlo simulations, which individually take a long time to complete, can be circumvented. A prediction of neutron spectra then takes some milliseconds, which enables fast optimization and comparison. The models’ shortcomings for low-energy neutrons (<0.1 MeV) and the cut-off prediction uncertainty (±3 MeV) are addressed, and mitigation strategies are proposed. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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