Numerical analysis of the Monte-Carlo noise for the resolution of the deterministic and uncertain linear Boltzmann equation (comparison of non-intrusive gPC and MC …
G Poëtte - Journal of Computational and Theoretical Transport, 2022 - Taylor & Francis
Abstract Monte Carlo-generalized Polynomial Chaos (MC-gPC) has already been
thoroughly studied in the literature. MC-gPC both builds a gPC based reduced model of a …
thoroughly studied in the literature. MC-gPC both builds a gPC based reduced model of a …
Efficient uncertain keff computations with the Monte Carlo resolution of generalised Polynomial Chaos based reduced models
G Poëtte, E Brun - Journal of Computational Physics, 2022 - Elsevier
In this paper, we are interested in taking into account uncertainties for k eff computations in
neutronics. More generally, the material of this paper can be applied to propagate …
neutronics. More generally, the material of this paper can be applied to propagate …
Multigroup-like MC resolution of generalised Polynomial Chaos reduced models of the uncertain linear Boltzmann equation (+ discussion on hybrid intrusive/non …
G Poëtte - Journal of Computational Physics, 2023 - Elsevier
In this paper, we are interested in propagating uncertainties through the linear Boltzmann
equation. Such model is intensively used in neutronics, photonics, socio-economics …
equation. Such model is intensively used in neutronics, photonics, socio-economics …
Uncertainty benchmarks for time-dependent transport problems
W Bennett, RG McClarren - Nuclear Science and Engineering, 2024 - Taylor & Francis
Verification solutions for uncertainty quantification (UQ) are presented for time-dependent
transport problems where, the scattering ratio, is uncertain. The method of polynomial chaos …
transport problems where, the scattering ratio, is uncertain. The method of polynomial chaos …
An analogy between solving Partial Differential Equations with Monte-Carlo schemes and the Optimisation process in Machine Learning (and few illustrations of its …
In this document, we revisit classical Machine Learning (ML) notions and algorithms under
the point of view of the numerician, ie the one who is interested in the resolution of partial …
the point of view of the numerician, ie the one who is interested in the resolution of partial …
Séminaire SISMA
G POËTTE - www-lihpc.cea.fr
Many physical applications rely on Monte-Carlo (MC) codes to solve partial differential
equations. The MC resolution implies the sampling of the variables $\mathscr (x, t, v) …
equations. The MC resolution implies the sampling of the variables $\mathscr (x, t, v) …
SISMA Seminar
G POËTTE - www-lihpc.cea.fr
Many physical applications rely on Monte-Carlo (MC) codes to solve partial differential
equations. The MC resolution implies the sampling of the variables $\mathscr (x, t, v) …
equations. The MC resolution implies the sampling of the variables $\mathscr (x, t, v) …