Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Jean C. Ragusa"'
Publikováno v:
Energies, Vol 15, Iss 11, p 3948 (2022)
Subchannel codes have been widely used for thermal-hydraulics analyses in nuclear reactors. This paper details the development of a novel subchannel code within the Idaho National Laboratory’s (INL) Multi-physics Object Oriented Simulation Environm
Externí odkaz:
https://doaj.org/article/7de59fa7bb4849159bbaebdafafdbb99
Publikováno v:
Fluids, Vol 6, Iss 8, p 266 (2021)
This work presents a data-driven Reduced-Order Model (ROM) for parametric convective heat transfer problems in porous media. The intrusive Proper Orthogonal Decomposition aided Reduced-Basis (POD-RB) technique is employed to reduce the porous medium
Externí odkaz:
https://doaj.org/article/fc491feab2df477c99eb96307cdd18c2
Physics-Informed Neural Network with Fourier Features for Radiation Transport in Heterogeneous Media
Publikováno v:
Nuclear Science and Engineering. :1-14
Autor:
Mauricio E. Tano, Jean C. Ragusa
Publikováno v:
Nuclear Technology. 207:1599-1614
In the high-temperature reactor design, it is common practice to leave gaps between the graphite blocks of the reflectors to accommodate thermal dilatation and material swelling, as well as to prov...
Publikováno v:
Nuclear Science and Engineering. 194:903-926
The Simplified P N ( S P N ) approximation is often used to model radiation transport phenomena, but it converges to the true solution of the transport equation only in one-dimensional slab geometr...
Publikováno v:
SIAM Journal on Numerical Analysis. 58:519-540
We introduce a (linear) positive and asymptotic-preserving method for solving the one-group radiation transport equation. The approximation in space is discretization agnostic: the space approximat...
Dynamic Mode Decomposition (DMD) is a model-order reduction approach, whereby spatial modes of fixed temporal frequencies are extracted from numerical or experimental data sets. The DMD low-rank or reduced operator is typically obtained by singular v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e4a1e0016a679e23292f5083c99e586
Publikováno v:
SSRN Electronic Journal.
Autor:
Patrick Behne, Jean C. Ragusa
Publikováno v:
Annals of Nuclear Energy. 180:109432
Publikováno v:
Journal of Computational Physics. 469:111525