Optimization of Centrifugal Fan Volute Parameters

Researchers from Kunming University of Science and Technology in China have conducted a study to enhance the operational effectiveness of centrifugal fans under specific operating conditions. Using a combination of machine learning and genetic algorithms, the team optimized three structural parameters of the fan volute, resulting in improved performance indicators such as outlet flow rate and total pressure efficiency. The study demonstrated strong agreement between simulation and experimental data, with the optimized design yielding a 2.29% increase in outlet flow rate and a 2.96% improvement in total pressure efficiency.

Key Takeaways:

• Researchers from Kunming University of Science and Technology employed a Backpropagation (BP) neural network combined with a reference point-based Non-dominated Sorting Genetic Algorithm III (NSGA-III) for multi-objective optimization of centrifugal fan volute parameters.
• Three structural parameters of the fan volute, including volute height, minimum distance between the impeller and the volute tongue, and radius of the volute tongue corner, were selected as design variables.
• Two performance indicators, outlet flow rate and total pressure efficiency, were chosen as optimization objectives, with the optimized design yielding a 2.29% increase in outlet flow rate and a 2.96% improvement in total pressure efficiency.
• The BP neural network provided highly accurate fitting and predictions, yielding a reliable surrogate model for predicting volute performance.
• Structural improvements at the fan inlet enhanced the overall flow field, resulting in a 6.06% increase in outlet flow rate and a 4.04% increase in total pressure efficiency compared to the original design.
• The study demonstrated strong agreement between simulation and experimental data.

Statistics:

• 2.29% increase in outlet flow rate after optimization
• 2.96% improvement in total pressure efficiency after optimization
• 6.06% increase in outlet flow rate with structural improvements at the fan inlet
• 4.04% increase in total pressure efficiency with structural improvements at the fan inlet
• 10.44% improvement in overall performance of the centrifugal fan after optimization

Sources:

• Optimization Study of Centrifugal Fan Volute Parameters based on Non-dominated Sorting Genetic Algorithm III Algorithm. Journal of Applied Fluid Mechanics, 2025, 18(10): 2476-2487.
• Journal of Applied Fluid Mechanics: http://jafmonline.net
• The publisher for Journal of Applied Fluid Mechanics: Isfahan University of Technology