| Particle swarm optimization: A powerful technique for solving engineering problems BSG de Almeida, VC Leite Swarm intelligence-recent advances, new perspectives and applications, 31-51, 2019 | 124 | 2019 |
| Nek5000 developments in support of industry and the NRC D Shaver, A Obabko, A Tomboulides, V Coppo-Leite, YH Lan, M Min, ... Argonne National Lab.(ANL), Argonne, IL (United States), 2020 | 16 | 2020 |
| High-fidelity simulation of mixing phenomena in large enclosures V Coppo Leite, E Merzari, J Mao, V Petrov, A Manera Nuclear Science and Engineering 198 (7), 1386-1403, 2024 | 14 | 2024 |
| Development of innovative overlapping-domain coupling between sam and nekrs A Huxford, V Petrov, A Manera, VC Leite, E Merzari, L Zou Proc. Proceedings of NURETH, 2022 | 11 | 2022 |
| Convolutional Neural Network–Aided Temperature Field Reconstruction: An Innovative Method for Advanced Reactor Monitoring VC Leite, E Merzari, R Ponciroli, L Ibarra Nuclear Technology 209 (5), 645-666, 2023 | 8 | 2023 |
| Data-driven Hi2Lo for coarse-grid system thermal hydraulic modeling AS Iskhakov, NT Dinh, VC Leite, E Merzari arXiv preprint arXiv:2203.03577, 2022 | 7 | 2022 |
| A hybrid domain overlapping method for coupling System Thermal Hydraulics and CFD codes A Huxford, VC Leite, E Merzari, L Zou, V Petrov, A Manera Annals of Nuclear Energy 189, 109842, 2023 | 6 | 2023 |
| Data-driven high-to-low for coarse grid system thermal hydraulics AS Iskhakov, V Coppo Leite, E Merzari, NT Dinh Nuclear Science and Engineering 198 (7), 1426-1438, 2024 | 5 | 2024 |
| Energy Exascale Computational Fluid Dynamics Simulations With the Spectral Element Method E Merzari, V Coppo Leite, J Fang, D Shaver, M Min, S Kerkemeier, ... Journal of Fluids Engineering 146 (4), 2024 | 3 | 2024 |
| Machine learning from RANS and LES to inform coarse grid simulations AS Iskhakov, NT Dinh, VC Leite, E Merzari Progress in Nuclear Energy 163, 104809, 2023 | 3 | 2023 |
| NEAMS IRP challenge problem 3: Mixing in large enclosures and thermal stratification A Manera, A Iskhakov, V Leite, J Mao, C Tai, V Vishwakarma, R Wiser, ... Proc. 20th Int. Topl. Mtg. Nuclear Reactor Thermal Hydraulics (NURETH-20), 2023 | 3 | 2023 |
| A comparison between markovian models and Bayesian networks for treating some dependent events in reliability evaluations JP Duarte, VC Leite, PF Melo | 3 | 2013 |
| A Study on Convolution Neural Network for Reconstructing the Temperature Field of Wall-Bounded Flows VC Leite, E Merzari, R Ponciroli, L Ibarra arXiv preprint arXiv:2202.00435, 2022 | 2 | 2022 |
| Turbulent Channel Flow With Spatially Dependent Viscosity: A Numerical Study VC Leite, E Merzari Journal of Fluids Engineering 144 (1), 011303, 2022 | 2 | 2022 |
| The effect of varying viscosity in turbulent channel flow V Coppo Leite, E Merzari Fluids Engineering Division Summer Meeting 83730, V003T05A019, 2020 | 2 | 2020 |
| Particle swarm optimization applied to the nuclear fuel bundle spacer grid spring design VC Leite, R Schirru, MM Neto Nuclear Technology 205 (5), 637-645, 2019 | 2 | 2019 |
| Otimização por enxame de partículas aplicado á estrutura mecânica da mola da grade espaçadora do elemento combustível de um reator nuclear VC Leite Rio de Janeiro: COPPE/UFRJ, 2017 | 2 | 2017 |
| Modelagem por redes bayesianas de eventos dependentes no cálculo de atributos de confiabilidade de sistemas de segurança de instalações nucleares VC Leite Universidade Federal do Rio de Janeiro, 2014 | 2 | 2014 |
| CFD simulations of Molten Salt Fast Reactor core cavity flows J Fang, M Tano, N Saini, A Tomboulides, V Coppo-Leite, E Merzari, ... Nuclear Engineering and Design 424, 113294, 2024 | 1 | 2024 |
| Discrete-Time Bayesian Networks Applied to Flexible Coping Strategies of Nuclear Power Plant Systems E Sahin, VC Leite, KM Kim, N Burns, J Pacheco Duarte Nuclear Science and Engineering 197 (11), 2800-2817, 2023 | 1 | 2023 |
