Machine-learning and CFD based optimization and comprehensive experimental study on diagonal flow fan for energy conservation and efficiency enhancement-Reference-Cited by-同舟云学术

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Machine-learning and CFD based optimization and comprehensive experimental study on diagonal flow fan for energy conservation and efficiency enhancement

Published:2024-02-02 Issue:1 Volume:18 Page:
ISSN:1994-2060
Container-title:Engineering Applications of Computational Fluid Mechanics
language:en
Short-container-title:Engineering Applications of Computational Fluid Mechanics

Author:

Zhou Shuiqing¹²,Luo Yu¹²,Mao Zijian¹²,Lu Laifa¹²,Feng Weiping³

Affiliation:

1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, People’s Republic of China

2. Institue of Innovation Research of Shengzhou, Zhejiang University of Technology, Shengzhou, People’s Republic of China

3. Electrical Products Testing Laboratory, Zhejiang Fangyuan Test Group Co., LTD, Hangzhou, People’s Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/19942060.2024.2310608

Reference35 articles.

1. Industrial fan—Performance testing using standardized airways GB/T 1236-2017 C.F.R. (2017).

2. Methods of noise measurement for fans blowers compressors and roots blowers GB/T 2888-2008 C.F.R. (2008).

3. Effect of Different Guide Vane Configurations on Flow Field Investigation and Performances of an Axial Pump Based on CFD Analysis and Vibration Investigation

4. Optimisation of a mixed flow fan with NACA profiled blades using computational fluid dynamics

5. Evaluating the potential of offshore wind energy in the Gulf of Oman using the MENA-CORDEX wind speed data simulations

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