Work

Optimization of aerodynamic performance and aeroacoustic characteristics in axial flow fans for direct evaporative air conditioning systems

Year: 2025

Type: article

Abstract: Direct evaporative cooling (DEC) air conditioning has gained widespread adoption as a green and low-carbon cooling technology. However, large-airflow DEC units often suffer from elevated noise levels and reduced aerodynamic efficiency due to limitations in axial flow fan design. To address the trade-off between noise reduction and airflow performance, this study integrates aerodynamic and acoustic experiments with computational fluid dynamics (CFD) simulations to establish predictive models for flow field characteristics and aerodynamic noise in DEC systems. Six key structural parameters, including impeller tip clearance, blade count, blade camber angle, blade sweep angle, collector height, and heat exchanger core (paper-based packing) configuration, were systematically evaluated for their effects on airflow capacity and noise generation. Surrogate models were developed using response surface methodology (RSM) to predict air supply volume and total sound pressure level, followed by multi-objective optimization via a genetic algorithm to determine the optimal parameter set. Results show that blade count and sweep angle are the primary factors influencing airflow performance, while tip clearance and camber angle have the greatest impact on aerodynamic noise. Based on the design pareto frontier, the optimized configuration (5° camber angle, 10° sweep angle, 3 mm tip clearance) achieved an airflow rate of 26,615 m3/h at 71.56 dB(A) total sound pressure level, representing a 539 m3/h airflow increase and a 3.24 dB(A) acoustic reduction versus baseline design. This research establishes a generic and systematic framework for simultaneously optimizing aerodynamic and acoustic performance in high-capacity direct evaporative cooling systems.

Source: Engineering Applications of Computational Fluid Mechanics

DOI: 10.1080/19942060.2025.2569645

Authors: Yaming Fan, Linwei Yu, Jinchai Shen, Yiyu Li, Minfeng Zheng, Sherman C.P. Cheung

Institutions: Fujian University of Technology, Guangzhou Mechanical Engineering Research Institute (China), RMIT University

Language: English

Topic: Turbomachinery Performance and Optimization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action

Open Access status: gold

Estimated APC paid: $1,993