Neutron Yield Predictions with Artificial Neural Networks: A Predictive Modeling Approach
Author:
Affiliation:
1. Institut für Kernphysik (IKP), Technische Universität Darmstadt, Schlossgartenstr. 9, 64289 Darmstadt, Germany
2. Elektrotechnik und Informationstechnik (EIT), Hochschule Darmstadt, Birkenweg 8, 64295 Darmstadt, Germany
Abstract
Funder
HMWK through the LOEWE center “Nuclear Photonics”
Graduate School CE within the Centre for Computational Engineering at Technische Universität Darmstadt
Trumpf GmbH & Co. KG
Publisher
MDPI AG
Link
https://www.mdpi.com/2673-4362/5/2/9/pdf
Reference20 articles.
1. RIKEN Compact Neutron Systems with Fast and Slow Neutrons;Otake;Plasma Fusion Res.,2018
2. The Jülich high-brilliance neutron source project;Cronert;Eur. Phys. J. Plus,2016
3. First steps toward the development of SONATE, a Compact Accelerator driven Neutron Source;Thulliez;EPJ Web Conf.,2020
4. ESFRI Physical Sciences and Engineering Strategy Working Group-NeutronLandscape Group (2015). Neutron Scattering Facilities in Europe—Present Status and Future Perspectives, European Strategy Forum on Research Infrastructures.
5. Conrad, H. (2021). Handbook of Particle Detection and Imaging, Springer International Publishing. Chapter Spallation: Neutrons Beyond Nuclear Fission.
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