4 citations · 9 across the 6 of their papers we have counts for
5 papers · 1 filter
In search of the best nuclear data file for proton induced reactions: varying both models and their parameters
E. Alhassan, D. Rochman, A. Vasiliev +4
A lot of research work has been carried out in fine tuning model parameters to reproduce experimental data for neutron induced reactions. This however is not the case for proton in…
Bayesian updating for data adjustments and multi-level uncertainty propagation within Total Monte Carlo
E. Alhassan, D. Rochman, H. Sjöstrand +3
In this work, a method is proposed for combining differential and integral benchmark experimental data within a Bayesian framework for nuclear data adjustments and multi-level unce…
Propagation of nuclear data uncertainties for ELECTRA burn-up calculations
H. Sjöstrand, E. Alhassan, J. Duan +5
The European Lead-Cooled Training Reactor (ELECTRA) has been proposed as a training reactor for fast systems within the Swedish nuclear program. It is a low-power fast reactor cool…
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…
Uncertainty study of nuclear model parameters for the n+ ^{56}Fe reactions in the fast neutron region below 20 MeV
Junfeng Duan, Stephan Pomp, Henrik Sjöstrand +5
In this work, we study the uncertainty of nuclear model parameters for neutron induced ^{56}Fe reactions in fast neutron region by using the Total Monte Carlo method. We perform a…