Publications (8)
Lasso Monte Carlo, a Variation on Multi Fidelity Methods for High Dimensional Uncertainty Quantification
Arnau AlbÃ, Romana Boiger, Dimitri Rochman +1
Uncertainty quantification (UQ) is an active area of research, and an essential technique used in all fields of science and engineering. The most common methods for UQ are Monte Ca…
Fast Uncertainty Quantification of Spent Nuclear Fuel with Neural Networks
Arnau AlbÃ, Andreas Adelmann, Lucas Münster +2
The accurate calculation and uncertainty quantification of the characteristics of spent nuclear fuel (SNF) play a crucial role in ensuring the safety, efficiency, and sustainabilit…
Conception and software implementation of a nuclear data evaluation pipeline
Georg Schnabel, Henrik Sjöstrand, Joachim Hansson +3
We discuss the design and software implementation of a nuclear data evaluation pipeline applied for a fully reproducible evaluation of neutron-induced cross sections of Fe a…
Combining Total Monte Carlo and Benchmarks for nuclear data uncertainty propagation on an LFRs safety parameters
Erwin Alhassan, Henrik Sjöstrand, Junfeng Duan +5
Analyses are carried out to assess the impact of nuclear data uncertainties on keff for the European Lead Cooled Training Reactor (ELECTRA) using the Total Monte Carlo method. A la…
EASY-II: a system for modelling of n, d, p, γ and α activation and transmutation processes
Jean-Christophe Sublet, James Eastwood, Guy Morgan +2
EASY-II is designed as a functional replacement for the previous European Activation System, EASY-2010. It has extended nuclear data and new software, FISPACT-II, written in object…
Uncertainty Quantification on Spent Nuclear Fuel with LMC
Arnau AlbÃ, Andreas Adelmann, Dimitri Rochman
The recently developed method Lasso Monte Carlo (LMC) for uncertainty quantification is applied to the characterisation of spent nuclear fuel. The propagation of nuclear data uncer…