A correlated sampling technique has been implemented to estimate the impact of cross section modifications on the neutron transport and in Monte Carlo simulations in one single calculation. This implementation has been coupled to a Total Monte Carlo approach which consists in propagating nuclear data uncertainties with random cross section files. The TMC-CS (Total Monte Carlo with Correlated Sampling) approach offers an interesting speed-up of the associated computation time. This methodology is detailed in this paper, together with two application cases to validate and illustrate the gain provided by this technique: the highly enriched uranium/iron metal core reflected by a stainless-steel reflector HMI-001 benchmark, and the PETALE experi...
Random sampling methods are used for nuclear data (ND) uncertainty propagation, often in combination...
This paper shows how Total Monte Carlo (TMC) method and Perturbation Theory (PT) can be applied to q...
The applications of nuclear physics are many with one important being nuclear power, which can help ...
The production of useful and high-quality nuclear data requires measurements with high precision and...
The Bayesian Monte Carlo technics requires individual evaluations of random cross section files base...
The quantification of uncertainties of various calculation results, caused by the uncertainties asso...
The PETALE experimental programme in the CROCUS reactor intends to provide integral measurements to ...
The aim of this work is to review different Monte Carlo techniques used to propagate nuclear data un...
Two distinct methods of propagation for basic nuclear data uncertainties to large scale systems will...
Nuclear data uncertainty propagation based on stochastic sampling ( SS) is becoming more attractive ...
Random sampling methods are used for nuclear data (ND) uncertainty propagation, often in combination...
We present an approach to uncertainty quantification for nuclear applica-tions, which combines the c...
Nuclear thermal propulsion (NTP) designs include large margins for manufacturing, thermal, and neutr...
Random sampling methods are used for nuclear data (ND) uncertainty propagation, often in combination...
This paper shows how Total Monte Carlo (TMC) method and Perturbation Theory (PT) can be applied to q...
The applications of nuclear physics are many with one important being nuclear power, which can help ...
The production of useful and high-quality nuclear data requires measurements with high precision and...
The Bayesian Monte Carlo technics requires individual evaluations of random cross section files base...
The quantification of uncertainties of various calculation results, caused by the uncertainties asso...
The PETALE experimental programme in the CROCUS reactor intends to provide integral measurements to ...
The aim of this work is to review different Monte Carlo techniques used to propagate nuclear data un...
Two distinct methods of propagation for basic nuclear data uncertainties to large scale systems will...
Nuclear data uncertainty propagation based on stochastic sampling ( SS) is becoming more attractive ...
Random sampling methods are used for nuclear data (ND) uncertainty propagation, often in combination...
We present an approach to uncertainty quantification for nuclear applica-tions, which combines the c...
Nuclear thermal propulsion (NTP) designs include large margins for manufacturing, thermal, and neutr...
Random sampling methods are used for nuclear data (ND) uncertainty propagation, often in combination...
This paper shows how Total Monte Carlo (TMC) method and Perturbation Theory (PT) can be applied to q...
The applications of nuclear physics are many with one important being nuclear power, which can help ...