Cargando…
Toward empirical correlations for estimating the specific heat capacity of nanofluids utilizing GRG, GP, GEP, and GMDH
When nanoparticles are dispersed and stabilized in a base-fluid, the resulting nanofluid undergoes considerable changes in its thermophysical properties, which can have a substantial influence on the performance of nanofluid-flow systems. With such necessity and importance, developing a set of mathe...
Autores principales: | Deymi, Omid, Hadavimoghaddam, Fahimeh, Atashrouz, Saeid, Nedeljkovic, Dragutin, Abuswer, Meftah Ali, Hemmati-Sarapardeh, Abdolhossein, Mohaddespour, Ahmad |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10676388/ https://www.ncbi.nlm.nih.gov/pubmed/38007563 http://dx.doi.org/10.1038/s41598-023-47327-x |
Ejemplares similares
-
Solubility of gaseous hydrocarbons in ionic liquids using equations of state and machine learning approaches
por: Nakhaei-Kohani, Reza, et al.
Publicado: (2022) -
Modeling the solubility of light hydrocarbon gases and their mixture in brine with machine learning and equations of state
por: Mohammadi, Mohammad-Reza, et al.
Publicado: (2022) -
Modeling of H(2)S solubility in ionic liquids: comparison of white-box machine learning, deep learning and ensemble learning approaches
por: Mousavi, Seyed-Pezhman, et al.
Publicado: (2023) -
Insights into modeling refractive index of ionic liquids using chemical structure-based machine learning methods
por: Esmaeili, Ali, et al.
Publicado: (2023) -
Modeling hydrogen solubility in hydrocarbons using extreme gradient boosting and equations of state
por: Mohammadi, Mohammad-Reza, et al.
Publicado: (2021)