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Technical Paper

Reducing the Acoustic Surface Power of a Cooling Fan Using the Mesh Morpher Optimizer

2017-03-28
2017-01-1610
Cooling fans have many applications in industrial and electronic fields that remove heat away from the system. The process of designing a new cooling fan with optimal performance and reduced acoustic sources can be fairly lengthy and expensive. The use of CFD with support of mesh morphing, along with the development of optimization techniques, can improve the acoustic’s performance of the fan model. This paper presents a new promising method which will support the design process of a new cooling fan with improved performance and less acoustic surface power generation. The CFD analysis is focused on reducing the acoustic surface power of a given cooling fan’s blade using the surface dipole acoustic power as the objective function, which leads to an optimized prototype design for a better performance. The Mesh Morpher Optimizer (MMO) in ANSYS Fluent is used in combination with a Simplex model of the broadband acoustic modeling.
Technical Paper

Investigation of the Acoustic Surface Power on a Cooling Fan Using the Mesh Morpher Optimizer

2019-04-02
2019-01-0833
A cooling fan is an essential device of the engine cooling system which is used to remove the heat generated inside the engine from the system. An essential element for successful fan designs is to evaluate the pressure over the fan blade since it can generate annoying noices, which have a negative impact on the fan’s performance and on the environment. Reducing the acoustic surface power will assist in building improved designs that comply with standards and regulations in achieving a more quiet environment. The usage of computational fluid dynamics (CFD), with support of mesh morphing, can provide simulation study for optimizing the shape of a fan blade to reduce the aeroacoustic effects. The investigation process will assist in examining and analyzing the acoustic performance of the prototype, impact of different parameters, and make a solid judgement about the model performance for improvement and optimization.
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