Research of cooling tower filler based on radial basis function artificial neural network (RBF ANN)

Research of cooling tower filler based on radial basis function artificial neural network (RBF ANN)

Abstract The filler is the core component of the cooling tower, filler performance refers to both its thermal and flow resistance characteristics, which use empirical formulas of tower characteristic N, volumetric mass transfer coefficient βxv, and pressure drop ΔP obtained through experimentation u...

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Bibliografische gegevens
Hoofdauteurs: Lixin Zhang, Jie Chen, Shunan Zhao, Yongbao Chen, Huijuan Song, Jingnan Liu
Formaat: Artikel
Taal:English
Gepubliceerd in: Wiley 2023-08-01
Reeks:Energy Science & Engineering
Onderwerpen:
cooling tower
filler
RBF ANN
resistance performance
thermal performance
Online toegang:https://doi.org/10.1002/ese3.1498

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