Modeling and characteristic analysis of fouling in a wet cooling tower based on wavelet neural networks-Reference-Cited by-同舟云学术

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Modeling and characteristic analysis of fouling in a wet cooling tower based on wavelet neural networks

Published:2019-04 Issue: Volume:152 Page:907-916
ISSN:1359-4311
Container-title:Applied Thermal Engineering
language:en
Short-container-title:Applied Thermal Engineering

Author:

Guo Qianjian,Qi Xiaoni,Wei Zheng,Yin Qiang,Sun Peng,Guo Pengjiang,Liu Jingcheng

Funder

National Natural Science Foundation of China

Shandong Provincial Natural Science Foundation of China

SDUT & Zhangdian District Integration Development Project of China

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Energy Engineering and Power Technology

Reference30 articles.

1. A novel approach for performance assessment of mechanical draft wet cooling towers;Naik;Appl. Therm. Eng.,2017

2. Optimization of mechanical draft counter flow wet-cooling tower using artificial bee colony algorithm;Rao;Energy Convers. Manage.,2011

3. Experimental analysis of the performance of new alternative materials for cooling tower fill;Tomás;Appl. Therm. Eng.,2018

4. Fouling of enhanced tubes for condensers used in cooling tower systems: a literature review;Chao;Appl. Therm. Eng.,2015

5. Film fill fouling in counter flow cooling towers: mechanism and design;Mortensen;Cool. Tower Inst. Ann. Meet.,1994

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