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RAZMARA, Naiyer et al. Efficient CH4/CO2 gas mixture separation through nanoporous graphene membrane designs. Energies, v. 14, n. 9, p. 1-16, 2021Tradução . . Disponível em: https://doi.org/10.3390/en14092488. Acesso em: 15 nov. 2024.
APA
Razmara, N., Kirch, A., Meneghini, J. R., & Miranda, C. R. (2021). Efficient CH4/CO2 gas mixture separation through nanoporous graphene membrane designs. Energies, 14( 9), 1-16. doi:10.3390/en14092488
NLM
Razmara N, Kirch A, Meneghini JR, Miranda CR. Efficient CH4/CO2 gas mixture separation through nanoporous graphene membrane designs [Internet]. Energies. 2021 ; 14( 9): 1-16.[citado 2024 nov. 15 ] Available from: https://doi.org/10.3390/en14092488
Vancouver
Razmara N, Kirch A, Meneghini JR, Miranda CR. Efficient CH4/CO2 gas mixture separation through nanoporous graphene membrane designs [Internet]. Energies. 2021 ; 14( 9): 1-16.[citado 2024 nov. 15 ] Available from: https://doi.org/10.3390/en14092488
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MARUM, Victor J. de Oliveira et al. Performance analysis of a water ejector using Computational Fluid Dynamics (CFD) simulations and mathematical modeling. Energy - Selected papers from the International Conference on Computational Heat, Mass and Momentum Transfer (ICCHMT2019), v. 220, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.energy.2021.119779. Acesso em: 15 nov. 2024.
APA
Marum, V. J. de O., Reis, L. B., Maffei, F. S., Ranjbarzadeh, S., Korkischko, I., Gioria, R. dos S., & Meneghini, J. R. (2021). Performance analysis of a water ejector using Computational Fluid Dynamics (CFD) simulations and mathematical modeling. Energy - Selected papers from the International Conference on Computational Heat, Mass and Momentum Transfer (ICCHMT2019), 220. doi:10.1016/j.energy.2021.119779
NLM
Marum VJ de O, Reis LB, Maffei FS, Ranjbarzadeh S, Korkischko I, Gioria R dos S, Meneghini JR. Performance analysis of a water ejector using Computational Fluid Dynamics (CFD) simulations and mathematical modeling [Internet]. Energy - Selected papers from the International Conference on Computational Heat, Mass and Momentum Transfer (ICCHMT2019). 2021 ; 220[citado 2024 nov. 15 ] Available from: https://doi.org/10.1016/j.energy.2021.119779
Vancouver
Marum VJ de O, Reis LB, Maffei FS, Ranjbarzadeh S, Korkischko I, Gioria R dos S, Meneghini JR. Performance analysis of a water ejector using Computational Fluid Dynamics (CFD) simulations and mathematical modeling [Internet]. Energy - Selected papers from the International Conference on Computational Heat, Mass and Momentum Transfer (ICCHMT2019). 2021 ; 220[citado 2024 nov. 15 ] Available from: https://doi.org/10.1016/j.energy.2021.119779
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FLÓREZ-ORREGO, Daniel Alexander et al. Optimal design of power hubs for offshore petroleum platforms. Energy, v. 235, p. 1-15, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.energy.2021.121353. Acesso em: 15 nov. 2024.
APA
Flórez-Orrego, D. A., Albuquerque Neto, C., Silva, J. A. M. da, Freire, R. L. A., & Oliveira Júnior, S. de. (2021). Optimal design of power hubs for offshore petroleum platforms. Energy, 235, 1-15. doi:10.1016/j.energy.2021.121353
NLM
Flórez-Orrego DA, Albuquerque Neto C, Silva JAM da, Freire RLA, Oliveira Júnior S de. Optimal design of power hubs for offshore petroleum platforms [Internet]. Energy. 2021 ; 235 1-15.[citado 2024 nov. 15 ] Available from: https://doi.org/10.1016/j.energy.2021.121353
Vancouver
Flórez-Orrego DA, Albuquerque Neto C, Silva JAM da, Freire RLA, Oliveira Júnior S de. Optimal design of power hubs for offshore petroleum platforms [Internet]. Energy. 2021 ; 235 1-15.[citado 2024 nov. 15 ] Available from: https://doi.org/10.1016/j.energy.2021.121353
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PELLEGRINI, Sérgio de Paula e TRIGO, Flávio Celso e GONZÁLEZ LIMA, Raúl. Adaptive Kalman filter-based information fusion in electricalimpedance tomography for a two-phase flow. Mechanical Systems and Signal Processing, v. 150, p. 1-21, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.ymssp.2020.107326. Acesso em: 15 nov. 2024.
APA
Pellegrini, S. de P., Trigo, F. C., & González Lima, R. (2021). Adaptive Kalman filter-based information fusion in electricalimpedance tomography for a two-phase flow. Mechanical Systems and Signal Processing, 150, 1-21. doi:10.1016/j.ymssp.2020.107326
NLM
Pellegrini S de P, Trigo FC, González Lima R. Adaptive Kalman filter-based information fusion in electricalimpedance tomography for a two-phase flow [Internet]. Mechanical Systems and Signal Processing. 2021 ; 150 1-21.[citado 2024 nov. 15 ] Available from: https://doi.org/10.1016/j.ymssp.2020.107326
Vancouver
Pellegrini S de P, Trigo FC, González Lima R. Adaptive Kalman filter-based information fusion in electricalimpedance tomography for a two-phase flow [Internet]. Mechanical Systems and Signal Processing. 2021 ; 150 1-21.[citado 2024 nov. 15 ] Available from: https://doi.org/10.1016/j.ymssp.2020.107326
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SALVIANO, Leandro Oliveira et al. Sensitivity analysis and optimization of a CO2 centrifugal compressor impeller with a vaneless diffuser. Structural and Multidisciplinary Optimization, v. 64, p. 1607–1627, 2021Tradução . . Disponível em: https://doi.org/10.1007/s00158-021-02914-2. Acesso em: 15 nov. 2024.
APA
Salviano, L. O., Gasparin, E. E., Vitor Cesar Nogueira Mattos,, Barbizan, B., Saltara, F., Mello, P. E. B. de, et al. (2021). Sensitivity analysis and optimization of a CO2 centrifugal compressor impeller with a vaneless diffuser. Structural and Multidisciplinary Optimization, 64, 1607–1627. doi:10.1007/s00158-021-02914-2
NLM
Salviano LO, Gasparin EE, Vitor Cesar Nogueira Mattos, Barbizan B, Saltara F, Mello PEB de, Dezan DJ, Yanagihara JI. Sensitivity analysis and optimization of a CO2 centrifugal compressor impeller with a vaneless diffuser [Internet]. Structural and Multidisciplinary Optimization. 2021 ; 64 1607–1627.[citado 2024 nov. 15 ] Available from: https://doi.org/10.1007/s00158-021-02914-2
Vancouver
Salviano LO, Gasparin EE, Vitor Cesar Nogueira Mattos, Barbizan B, Saltara F, Mello PEB de, Dezan DJ, Yanagihara JI. Sensitivity analysis and optimization of a CO2 centrifugal compressor impeller with a vaneless diffuser [Internet]. Structural and Multidisciplinary Optimization. 2021 ; 64 1607–1627.[citado 2024 nov. 15 ] Available from: https://doi.org/10.1007/s00158-021-02914-2