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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Dades bibliogràfiques
Autors principals:	Lixin Zhang, Jie Chen, Shunan Zhao, Yongbao Chen, Huijuan Song, Jingnan Liu
Format:	Article
Idioma:	English
Publicat:	Wiley 2023-08-01
Col·lecció:	Energy Science & Engineering
Matèries:	cooling tower filler RBF ANN resistance performance thermal performance
Accés en línia:	https://doi.org/10.1002/ese3.1498

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