Effect of a casing fence on the tip-leakage flow of an axial flow fan

Park, Keuntae; Choi, Haecheon; Choi, Seokho; Sa, Yongcheol

doi:10.1016/j.ijheatfluidflow.2019.04.005

Cited by 18 publications

(7 citation statements)

References 54 publications

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“…It is a rotating flow structure that forms caused by the pressure disparity between the upper and lower surfaces of the object, causing fluid to flow around the tip and form a vortex [3,4]. Tip vortex is an important aspect of fluid dynamics in many engineering applications, as it can have significant effects on the performance and efficiency of the object [5,6]. For example, in aircraft design, tip vortex can cause increased drag and reduced lift, which can have a negative impact on the aircraft's performance.…”

Section: Introductionmentioning

confidence: 99%

Influence of different turbulence models on tip vortex prediction

Fang,

Li,

Tao

et al. 2024

J. Phys.: Conf. Ser.

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Tip vortex cavitation usually occurs in marine propellers and axial-flow turbines, the cavitation in the tip vortex could potentially result in blade erosion, at the same time, it will cause the pump vibration and noise emission. The tip vortex mainly occurs in rotating machinery with complex three-dimensional flow, but the prediction of the hydrofoil tip vortex can provide a basis for the study of the blade tip vortex in rotating machinery by simplifying the blade model. Hence, in this paper, we use the commercial software CFX to investigate the impact of distinct turbulence models on the configuration of tip vortex distribution in the NACA 16-020 hydrofoil, including SST (Shear Stress Transport), DES (Detached Eddy Simulation), LES (Large Eddy Simulation) turbulence models which are widely used in the field of rotating machinery. At the same time, the axial and radial velocity distributions at different locations downstream of the tip of the hydrofoil are compared to analyse the effects on the velocity distribution near the vortex core line stemming from various turbulence models. By comparing with the experimental data, the most accurate turbulence model for tip vortex prediction is obtained, which will provide guidance for the next step tip vortex prediction and the control of tip vortex flow.

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Section: Introductionmentioning

confidence: 99%

Influence of different turbulence models on tip vortex prediction

Fang,

Li,

Tao

et al. 2024

J. Phys.: Conf. Ser.

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“…Deep learning [13]- [20] can play a significant role in enhancing the monitoring and maintenance system for axial flow fans. The deep neural networks (DNNs) [13] or convolutional neural networks (CNNs) [14] can be trained on historical data from the axial flow fan's operation. These models can learn to recognize normal operating patterns and detect anomalies in real-time.…”

Section: Introductionmentioning

confidence: 99%

Hybrid optimal deep learning with IoT based smart based monitoring and maintenance system for axial flow fan using feature optimization

Andreica,

Offenberg

2023

J. Adv. Zool.

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Axial flow fan is a mechanical fan that generates airflow in the same direction as its rotational axis. These fans find widespread use in various applications, including ventilation, cooling, and air circulation across industrial, commercial, and residential settings. However, designing these fans can be challenging in the fan manufacturing industry due to the need to accommodate diverse operating conditions. This complexity arises from the fact that multiple design parameters significantly influence fan performance, requiring careful consideration and optimization to ensure efficient operation across various scenarios. In this paper, we present a technique for monitoring and maintenance of axial flow fans using hybrid optimal deep learning with IoT system. Our method leverages the pre-trained U-Net architecture to extract hidden features effectively from the dataset. Furthermore, we introduce an improved triple tree-seed optimization (IT2SO) algorithm for feature optimization, which identifies the most optimal features among the extracted ones. To make informed decisions about axial flow fan process monitoring, we propose the deep boosted hybrid learning (DBHL) technique as the decision model to maintain the proper operation. To validate the effectiveness of proposed IT2SO+DBHL technique, we have conducted experiments using the air movement and control association international (AMCA) dataset. The results demonstrate the superior performance of our monitoring approach compared to existing techniques across various evaluation measures.

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“…In the meantime, the rotor and stator interaction (RSI) was the reason for the pressure fluctuation, and the TLF had less effect on the impeller inlet and middle region within a certain range. In addition, some other scholars applied numerical simulation methods to investigate the TLF in turbomachinery such as centrifugal pumps [27,28], compressors [29,30], fans [31,32].…”

Section: Introductionmentioning

confidence: 99%

Phase Distribution in the Tip Clearance of a Multiphase Pump at Multiple Operating Points and Its Effect on the Pressure Fluctuation Intensity

Shi

Liu

et al. 2021

Processes

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Tip clearance has a great effect on the flow and pressure fluctuation characteristics in a multiphase pump, especially at multiple operating points. The phase distribution and pressure fluctuation in tip clearance in a multiphase pump are revealed using the CFD (computational fluid dynamics) technology and high-speed photography methods. In this paper, the phase distribution, the gas-liquid two-phase velocity slip, and the pressure fluctuation intensity are comprehensively analyzed. Results show with the increase of the tip clearance, the multiphase pump pressurization performance is obviously deteriorated. In the meantime, the gas accumulation mainly occurs at the hub, the blade suction side (SS), and the tip clearance, and the maximum gas-liquid two-phase velocity difference is near the impeller streamwise of 0.4. In addition, the tip clearance improves the gas-liquid two-phase distribution in the pump, that is, the larger the tip clearance is, the more uniform the gas-liquid distribution becomes. Furthermore, the gas leads to the maximum pressure fluctuation intensity in the tip clearance which is closer to the tip leakage flow (TLF) outlet, and has a greater effect on the degree of flow separation in the tip clearance.

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Effect of a casing fence on the tip-leakage flow of an axial flow fan

Cited by 18 publications

References 54 publications

Influence of different turbulence models on tip vortex prediction

Influence of different turbulence models on tip vortex prediction

Hybrid optimal deep learning with IoT based smart based monitoring and maintenance system for axial flow fan using feature optimization

Phase Distribution in the Tip Clearance of a Multiphase Pump at Multiple Operating Points and Its Effect on the Pressure Fluctuation Intensity

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