Benedikt Schmitz
Lecturer
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About
Benedikt Schmitz is a Lecturer at Darmstadt University of Applied Sciences in Germany. His research interests include predictive modeling using artificial neural networks, particle-in-cell simulations combined with deep learning, and the analysis of laser-proton acceleration experiments. Recent articles authored by him focus on neutron yield predictions, automated reconstruction of laser-accelerated ion beams, and the development of empirical scaling laws in laser-driven experiments.
Articles (4)
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.
Year:
2024
Year:
2023
Year:
2022
Year:
2021
Collaborators (3)
Oliver Boine-Frankenheim
Professor
Technische Universität Darmstadt
Stefan Scheuren
Technische Universität Darmstadt
Marc Zimmer
Head of Laser Driven Radiation Sources
FOCUS C. R. L.
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