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Artigo de periodico
Wet air flow rate metering based on a longwavelength sound propagation (2026)
Castro Bolivar, Johann Eduardo; Hernandez Cely, Marlon M.; Hernandez Rodriguez, Oscar Mauricio
Source: Flow Measurement and Instrumentation. Unidade: EESC
Assunto: ENGENHARIA MECÂNICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CASTRO BOLIVAR, Johann Eduardo e HERNANDEZ CELY, Marlon M. e HERNANDEZ RODRIGUEZ, Oscar Mauricio. Wet air flow rate metering based on a longwavelength sound propagation. Flow Measurement and Instrumentation, v. 107, p. 1-12, 2026Tradução . . Disponível em: http://dx.doi.org/10.1016/j.flowmeasinst.2025.103064. Acesso em: 05 dez. 2025.
APA
Castro Bolivar, J. E., Hernandez Cely, M. M., & Hernandez Rodriguez, O. M. (2026). Wet air flow rate metering based on a longwavelength sound propagation. Flow Measurement and Instrumentation, 107, 1-12. doi:10.1016/j.flowmeasinst.2025.103064
NLM
Castro Bolivar JE, Hernandez Cely MM, Hernandez Rodriguez OM. Wet air flow rate metering based on a longwavelength sound propagation [Internet]. Flow Measurement and Instrumentation. 2026 ; 107 1-12.[citado 2025 dez. 05 ] Available from: http://dx.doi.org/10.1016/j.flowmeasinst.2025.103064
Vancouver
Castro Bolivar JE, Hernandez Cely MM, Hernandez Rodriguez OM. Wet air flow rate metering based on a longwavelength sound propagation [Internet]. Flow Measurement and Instrumentation. 2026 ; 107 1-12.[citado 2025 dez. 05 ] Available from: http://dx.doi.org/10.1016/j.flowmeasinst.2025.103064
Artigo de periodico
Non-invasive mass flow and local heat transfer coefficient measurements in pulsating heat pipes (2024)
Misina, Fernando Seiti; Corrêa, Mateus Henrique; Tibiriçá, Cristiano Bigonha
Source: Flow Measurement and Instrumentation. Unidade: EESC
Subjects: TRANSFERÊNCIA DE CALOR, ESCOAMENTO BIFÁSICO, DINÂMICA DOS FLUÍDOS, ENGENHARIA MECÂNICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MISINA, Fernando Seiti e CORRÊA, Mateus Henrique e TIBIRIÇÁ, Cristiano Bigonha. Non-invasive mass flow and local heat transfer coefficient measurements in pulsating heat pipes. Flow Measurement and Instrumentation, v. 100, p. 1-16, 2024Tradução . . Disponível em: http://dx.doi.org/10.1016/j.flowmeasinst.2024.102701. Acesso em: 05 dez. 2025.
APA
Misina, F. S., Corrêa, M. H., & Tibiriçá, C. B. (2024). Non-invasive mass flow and local heat transfer coefficient measurements in pulsating heat pipes. Flow Measurement and Instrumentation, 100, 1-16. doi:10.1016/j.flowmeasinst.2024.102701
NLM
Misina FS, Corrêa MH, Tibiriçá CB. Non-invasive mass flow and local heat transfer coefficient measurements in pulsating heat pipes [Internet]. Flow Measurement and Instrumentation. 2024 ; 100 1-16.[citado 2025 dez. 05 ] Available from: http://dx.doi.org/10.1016/j.flowmeasinst.2024.102701
Vancouver
Misina FS, Corrêa MH, Tibiriçá CB. Non-invasive mass flow and local heat transfer coefficient measurements in pulsating heat pipes [Internet]. Flow Measurement and Instrumentation. 2024 ; 100 1-16.[citado 2025 dez. 05 ] Available from: http://dx.doi.org/10.1016/j.flowmeasinst.2024.102701
Artigo de periodico
Vibration-based multiphase-flow pattern classification via machine learning techniques (2023)
Sestito, Guilherme Serpa ; Álvarez-Briceño, Ricardo; Ribatski, Gherhardt ; Silva, Maíra Martins da ; Oliveira, Leopoldo Pisanelli Rodrigues de
Source: Flow Measurement and Instrumentation. Unidade: EESC
Subjects: ESCOAMENTO MULTIFÁSICO, VIBRAÇÕES, REDES NEURAIS, ENGENHARIA MECÂNICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SESTITO, Guilherme Serpa et al. Vibration-based multiphase-flow pattern classification via machine learning techniques. Flow Measurement and Instrumentation, v. 89, p. 1-12, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.flowmeasinst.2022.102290. Acesso em: 05 dez. 2025.
APA
Sestito, G. S., Álvarez-Briceño, R., Ribatski, G., Silva, M. M. da, & Oliveira, L. P. R. de. (2023). Vibration-based multiphase-flow pattern classification via machine learning techniques. Flow Measurement and Instrumentation, 89, 1-12. doi:10.1016/j.flowmeasinst.2022.102290
NLM
Sestito GS, Álvarez-Briceño R, Ribatski G, Silva MM da, Oliveira LPR de. Vibration-based multiphase-flow pattern classification via machine learning techniques [Internet]. Flow Measurement and Instrumentation. 2023 ; 89 1-12.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.flowmeasinst.2022.102290
Vancouver
Sestito GS, Álvarez-Briceño R, Ribatski G, Silva MM da, Oliveira LPR de. Vibration-based multiphase-flow pattern classification via machine learning techniques [Internet]. Flow Measurement and Instrumentation. 2023 ; 89 1-12.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.flowmeasinst.2022.102290
Artigo de periodico
Machine-learning classification of environmental conditions inside a tank by analyzing radar curves in industrial level measurements (2021)
Borg, Denis; Sestito, Guilherme Serpa ; Silva, Maíra Martins da
Source: Flow Measurement and Instrumentation. Unidade: EESC
Subjects: APRENDIZADO COMPUTACIONAL, RADAR, TURBULÊNCIA, ENGENHARIA MECÂNICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BORG, Denis e SESTITO, Guilherme Serpa e SILVA, Maíra Martins da. Machine-learning classification of environmental conditions inside a tank by analyzing radar curves in industrial level measurements. Flow Measurement and Instrumentation, v. 79, p. 1-9, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.flowmeasinst.2021.101940. Acesso em: 05 dez. 2025.
APA
Borg, D., Sestito, G. S., & Silva, M. M. da. (2021). Machine-learning classification of environmental conditions inside a tank by analyzing radar curves in industrial level measurements. Flow Measurement and Instrumentation, 79, 1-9. doi:10.1016/j.flowmeasinst.2021.101940
NLM
Borg D, Sestito GS, Silva MM da. Machine-learning classification of environmental conditions inside a tank by analyzing radar curves in industrial level measurements [Internet]. Flow Measurement and Instrumentation. 2021 ; 79 1-9.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.flowmeasinst.2021.101940
Vancouver
Borg D, Sestito GS, Silva MM da. Machine-learning classification of environmental conditions inside a tank by analyzing radar curves in industrial level measurements [Internet]. Flow Measurement and Instrumentation. 2021 ; 79 1-9.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.flowmeasinst.2021.101940
Artigo de periodico
Water film thickness measurement system for oil-water pipe flow (2019)
Bonilla Riaño, Adriana; Velasco Peña, Hugo Fernando; Bannwart, Antonio Carlos; Prasser, H. M.; Hernandez Rodriguez, Oscar Mauricio
Source: Flow Measurement and Instrumentation. Unidade: EESC
Subjects: FLUXO DOS LÍQUIDOS, FILMES FINOS, ENGENHARIA MECÂNICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BONILLA RIAÑO, Adriana et al. Water film thickness measurement system for oil-water pipe flow. Flow Measurement and Instrumentation, v. 66, p. 86-98, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.flowmeasinst.2019.02.007. Acesso em: 05 dez. 2025.
APA
Bonilla Riaño, A., Velasco Peña, H. F., Bannwart, A. C., Prasser, H. M., & Hernandez Rodriguez, O. M. (2019). Water film thickness measurement system for oil-water pipe flow. Flow Measurement and Instrumentation, 66, 86-98. doi:10.1016/j.flowmeasinst.2019.02.007
NLM
Bonilla Riaño A, Velasco Peña HF, Bannwart AC, Prasser HM, Hernandez Rodriguez OM. Water film thickness measurement system for oil-water pipe flow [Internet]. Flow Measurement and Instrumentation. 2019 ; 66 86-98.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.flowmeasinst.2019.02.007
Vancouver
Bonilla Riaño A, Velasco Peña HF, Bannwart AC, Prasser HM, Hernandez Rodriguez OM. Water film thickness measurement system for oil-water pipe flow [Internet]. Flow Measurement and Instrumentation. 2019 ; 66 86-98.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.flowmeasinst.2019.02.007

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