Blade Structure Design Based on Multi-objective Optimization of Automotive Fan

Zhong, Yinhui; Li, Yinong; Li, Peiran; Chen, Jingchang; Xia, Tiequan; Kuang, Xiaohong

doi:10.1088/1742-6596/1952/3/032022

Cited by 3 publications

(2 citation statements)

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“…A very limited number of fan blade shape optimizations for noise reduction are available in the literature. One of them is [7], in which BEM and the Ffowcs Williams-Hawkings analogy [8] are used to compute the fan acoustics, and the geometry optimization of the blade is carried out by a genetic algorithm.…”

Section: Introductionmentioning

confidence: 99%

Low-Noise Airfoils for Turbomachinery Applications: Two Examples of Optimization

Casari,

Fadiga,

Oliani

et al. 2024

IJTPP

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Automotive fans, small wind turbines, and manned and unmanned aerial vehicles (MAVs/UAVs) are just a few examples in which noise generated by the flow’s interaction with aerodynamic surfaces is a major concern. The current work shows the potential of a new airfoil shape to minimize noise generation, maintaining a high lift-to-drag ratio in a prescribed Reynolds regime. This investigation uses a multifidelity approach: a low-fidelity semiempirical model is exploited to evaluate the sound pressure level (SPL). Fast evaluation of a low-cost function enables the computation of a large range of possible profiles, and accuracy is added to the low-fidelity response surface with high-fidelity CFD data. The constraint of maintaining a predefined range of the lift coefficient and lift-to-drag ratio ensures the possibility of using this profile in usual design procedures.

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Section: Introductionmentioning

confidence: 99%

Low-Noise Airfoils for Turbomachinery Applications: Two Examples of Optimization

Casari,

Fadiga,

Oliani

et al. 2024

IJTPP

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show abstract

“…For instance, [8] and [9] use parametrized RANS and metamodels to mitigate the high computational cost of the complex numerical simulations and perform the optimization process using multi-objective genetic algorithms while [10] relies on RANS simulations and a Kriging metamodel, using Latin Hypercube Sampling to reduce the number of simulations required. Still few design optimization attempts have been made that include fan acoustic performances, such as [11], in which BEM and Ffowcs William-Hawkings analogy (FWH) [12] are used to compute the fan acoustics and a genetic algorithm performs the blades geometry optimization.…”

Section: Introductionmentioning

confidence: 99%

Towards a low-noise axial fan for automotive applications

Casari

Oliani

Pinelli

et al. 2022

J. Phys.: Conf. Ser.

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The demand for quieter vehicles is pushing manufacturers of components for the automotive industry to seek for solutions to reduce the overall noise emissions. The cooling fan makes no exception: the aerodynamic interaction of the blades with the incoming flow generates turbulence and pressure fluctuations which ultimately translate into noise generation. A variety of expedients have been introduced to limit the produced noise, but no univocal solution has been found. In modern research, Computational Fluid Dynamics (CFD) has been successfully applied to blades and fans for both the flow and acoustic field derivation. By including the acoustic field, researchers have been able to predict the effect of changes in the blade geometry on the overall sound emission. This work reports a conjugate numerical-experimental study of a reference profile in different flow conditions, in order to validate the CFD acoustic prediction and to lay the basis for improved candidates able to lower the fan-generated noise.

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Study on Noise Model of an Automotive Axial Fan Based on Aerodynamic Load Force

Zhong

2022

Applied Sciences

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Due to the fact that the noise caused by axial fan blades of vehicles is large, which seriously affects ride comfort, and there is no effective mathematical model to quantitatively study the contribution of the various parameters of the blades to the noise, a new method for calculating the load force of the blades is proposed. This method obtains the constant load force of the blade according to the blade element momentum theory and the characteristics of the blade structure of the axial fan for a vehicle. At the same time, this method obtains the non-constant load force of the blade by combining the non-constant thin-wing theory and experimental data and then vectors the constant load force and the non-constant load force to obtain the total load force of the blade to build a mathematical model of the relationship between the noise of the fan and the parameters of the blade. According to the model, the total sound pressure level of a fan is calculated numerically and further compared with the FLUENT software simulation and experimental results. The results show that the error of the total sound pressure level calculated by the numerical value is within 3 dB(A). This method provides an important basis for the study of a high-accuracy noise mathematical model and the optimization of blade parameters of low Mach-number fans.

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Blade Structure Design Based on Multi-objective Optimization of Automotive Fan

Cited by 3 publications

References 0 publications

Low-Noise Airfoils for Turbomachinery Applications: Two Examples of Optimization

Low-Noise Airfoils for Turbomachinery Applications: Two Examples of Optimization

Towards a low-noise axial fan for automotive applications

Study on Noise Model of an Automotive Axial Fan Based on Aerodynamic Load Force

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