4 papers
Machine Learning for neutron source distributions
Jose Ignacio Robledo, Norberto Schmidt, Klaus Lieutenant +3
In light of the recent advancements in machine learning, we propose a novel approach to neutron source distribution estimation through the utilisation of probabilistic generative m…
Small Angle Neutron Scattering in McStas: optimization for high throughput virtual experiments
Jose Robledo, Klaus Lieutenant, Peter Willendrup
In this work we present the development of small angle scattering components in McStas that describe the neutron interaction with 70 different form and structure factors. We descri…
KDSource, a tool for the generation of Monte Carlo particle sources using kernel density estimation
N. S. Schmidt, O. I. Abbate, Z. M. Prieto +4
Monte Carlo radiation transport simulations have clearly contributed to improve the design of nuclear systems. When performing in-beam or shielding simulations a complexity arises…
Development of neutron scattering kernels for cold neutron reflector materials
José Rolando Granada, José Ignacio Márquez Damián, Javier Dawidowski +4
The newest neutron scattering applications are highly intensity-limited techniques that demand reducing the neutron losses between source and detectors. In addition, the nuclear in…