Cargando…
Prediction of the Thermal Conductivity of Refrigerants by Computational Methods and Artificial Neural Network
Background: The thermal conductivity of fluids can be calculated by several computational methods. However, these methods are reliable only at the confined levels of density, and there is no specific computational method for calculating thermal conductivity in the wide ranges of density. Methods: In...
Autores principales: | Ghaderi, Forouzan, Ghaderi, Amir H., Ghaderi, Noushin, Najafi, Bijan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5694760/ https://www.ncbi.nlm.nih.gov/pubmed/29188217 http://dx.doi.org/10.3389/fchem.2017.00099 |
Ejemplares similares
-
Artificial Neural
Network Model for the Prediction
of Thermal Conductivity of Saturated Liquid Refrigerants and n-Alkanes
por: Meng, Xiangsheng, et al.
Publicado: (2022) -
A Molecular Dynamics Simulation Study of In- and Cross-Plane Thermal Conductivity of Bilayer Graphene
por: Mohammadi, Rafat, et al.
Publicado: (2023) -
A Physics-Informed Assembly of Feed-Forward Neural Network Engines to Predict Inelasticity in Cross-Linked Polymers
por: Ghaderi, Aref, et al.
Publicado: (2020) -
Epidemiological Profile of Salivary Gland Tumors in Southern Iranian Population: A Retrospective Study of 405 Cases
por: Ghaderi, Hamid, et al.
Publicado: (2023) -
Artificial neural network based gynaecological image-guided adaptive brachytherapy treatment planning correction of intra-fractional organs at risk dose variation
por: Jaberi, Ramin, et al.
Publicado: (2017)