Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/72662
Título: | Thermal conductivity of nanofluids: a review on prediction models, controversies and challenges |
Autor(es): | Gonçalves, Inês Souza, Reinaldo Coutinho, Gonçalo Miranda, João Moita, Ana Pereira, José Eduardo Moreira, António Lima, Rui Alberto Madeira Macedo |
Palavras-chave: | Nanofluids Nanoparticles Thermal conductivity Heat transfer Machine learning |
Data: | 11-Mar-2021 |
Editora: | Multidisciplinary Digital Publishing Institute (MDPI) |
Revista: | Applied Sciences |
Citação: | Gonçalves, I.; Souza, R.; Coutinho, G.; Miranda, J.; Moita, A.; Pereira, J.E.; Moreira, A.; Lima, R. Thermal Conductivity of Nanofluids: A Review on Prediction Models, Controversies and Challenges. Appl. Sci. 2021, 11, 2525. https://doi.org/10.3390/app11062525 |
Resumo(s): | In recent years, the nanofluids (NFs) have become the main candidates for improving or even replacing traditional heat transfer fluids. The possibility of NFs to be used in various technological applications, from renewable energies to nanomedicine, has made NFs and their thermal conductivity one of the most studied topics nowadays. Hence, this review presents an overview of the most important advances and controversial results related to the NFs thermal conductivity. The different techniques used to measure the thermal conductivity of NFs are discussed. Moreover, the fundamental parameters that affect the NFs thermal conductivity are analyzed, and possible improvements are addressed, such as the increase of long-term stability of the nanoparticles (NPs).The most representative prediction classical models based on fluid mechanics, thermodynamics, and experimental fittings are presented. Also, the recent statistical machine learning-based prediction models are comprehensively addressed, and the comparison with the classical empirical ones is made, whenever possible. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/72662 |
DOI: | 10.3390/app11062525 |
e-ISSN: | 2076-3417 |
Versão da editora: | https://www.mdpi.com/2076-3417/11/6/2525 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | MEtRICs - Artigos em revistas internacionais/Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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applsci-11-02525.pdf | 2,5 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons