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...

書誌詳細
主要な著者:	Lixin Zhang, Jie Chen, Shunan Zhao, Yongbao Chen, Huijuan Song, Jingnan Liu
フォーマット:	論文
言語:	English
出版事項:	Wiley 2023-08-01
シリーズ:	Energy Science & Engineering
主題:	cooling tower filler RBF ANN resistance performance thermal performance
オンライン･アクセス:	https://doi.org/10.1002/ese3.1498

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