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...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Lixin Zhang, Jie Chen, Shunan Zhao, Yongbao Chen, Huijuan Song, Jingnan Liu
Aineistotyyppi: Artikkeli
Kieli:English
Julkaistu: Wiley 2023-08-01
Sarja:Energy Science & Engineering
Aiheet:
cooling tower
filler
RBF ANN
resistance performance
thermal performance
Linkit:https://doi.org/10.1002/ese3.1498

Internet

https://doi.org/10.1002/ese3.1498

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