Investigation of flow parameters of Reiner-Philippoff nanofluid flow with higher-order slip properties, activation energy, and bioconvection by artificial neural networks
Küçük Resim Yok
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Wiley
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, the flow parameters of Reiner-Philippoff nanofluid flow with high-order slip properties, activation energy, and bioconvection have been analyzed using artificial neural networks (ANNs). Local Nusselt number (LNN), local Sherwood number (LSN), and motile density number (MDN) are considered as flow parameters. Numerical values have been obtained by numerical methods using flow equations. To estimate the flow parameters, three different ANN models have been designed. The Levenberg-Marquardt training algorithm is used in multilayer perceptron network models with 10 neurons in the hidden layers. In all, 70% of the data set has been used for training the models, 15% for validation, and 15% for testing. The performance analysis of the network models has been made by calculating the determined performance parameters. The R values for the LNN, LSN, and MDN parameters have been calculated as 0.99261, 0.98769, and 0.99102, respectively, and the average deviation values are -0.65%, 0.06%, and -0.11%, respectively. The attained outcomes showed that the ANNs can predict the LNN, LSN, and MDN, which are the flow parameters of the Reiner-Philippoff nanofluid flow, with high accuracy.
Açıklama
Anahtar Kelimeler
activation energy, artificial neural network, bioconvection flow, higher-order slip, Reiner-Philippoff nanofluid
Kaynak
Heat Transfer
WoS Q Değeri
N/A
Scopus Q Değeri
Q2
Cilt
51
Sayı
6
