Comparison of Flow Mechanism of Blade Sweep between a Transonic Single Rotor and a Rotor in Stage Environment

Cao, Zeyuan; Gao, Xi; Liang, Yuyuan; Huang, Ping; Peng, Lei; Liu, Bo

doi:10.1007/s11630-022-1657-y

Cited by 8 publications

(2 citation statements)

References 31 publications

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“…Active control techniques include boundary-layer suction, end-wall air injection, and casing suction [ [5] , [6] , [7] ]. Passive flow-control methods include casing treatments, slotted blades, and curved/swept blades [ [8] , [9] , [10] , [11] ]. Notably, the aforementioned flow-control method in the tip-clearance area requires substantial modifications to the compressor structure and internal aerodynamic layout, resulting in higher costs.…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation on the influence of nonuniform tip clearance on rotor tip-clearance flow field structure

Zhang,

Li,

Cao

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Numerical investigation on the influence of nonuniform tip clearance on rotor tip-clearance flow field structure

Zhang,

Li,

Cao

et al. 2024

Heliyon

Self Cite

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“…For a fan, a poorly designed rotor hub region not only induces severe corner separations but also leads to flow losses in the downstream stator blades, which significantly decrease the fan performances (Gallimore, 1999; Joslyn and Dring, 1985; Cao et al , 2022). The full-annulus unsteady Reynolds-averaged Navier–Stokes (URANS) simulation approach has been demonstrated to be reliable in predicting fan performance under inlet distortion conditions (Zhang et al , 2020; Fidalgo et al , 2012).…”

Section: Introductionmentioning

confidence: 99%

A data-driven flow loss prediction model for the blade hub region of a boundary layer ingestion fan rotor

Shi,

Lu,

Song

et al. 2023

HFF

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Purpose In a boundary layer ingestion (BLI) propulsion system, the fan operates continuously under distorted inflow conditions, leading to an increment of aerodynamic loss and in turn impacting the potential fuel burn reduction of the aircraft. Usually, in the preliminary design stage of a BLI propulsion system, it is essential to assess the impact of fuselage boundary layer fluids on fan aerodynamic performances under various flight conditions. However, the hub region flow loss is one of the major loss sources in a fan and would greatly influence the fan performances. Moreover, the inflow distortion also results in a complex and highly nonlinear mapping relation between loss and local physical parameters. It will diminish the prediction accuracy of the commonly used low-fidelity computational approaches which often incorporate traditional physics-based loss models, reducing the reliability of these approaches in evaluating fan performances. Meanwhile, the high-fidelity full-annulus unsteady Reynolds-averaged Navier–Stokes (URANS) approach, even though it can give rather accurate loss predictions, is extremely time-consuming. This study aims to develop a fast and accurate hub loss prediction method for a BLI fan under distorted inflow conditions. Design/methodology/approach This paper develops a data-driven hub loss prediction method for a BLI fan under distorted inflows. To improve the prediction accuracy and applicability, physical understandings of hub flow features are integrated into the modeling process. Then, the key physical parameters related to flow loss are screened by conducting a sensitivity analysis of influencing parameters. Next, a quasi-steady assumption of flow is made to generate a training sample database, reducing the computational time by acquiring one single sample from the highly time-consuming full-annulus URANS approach to a cost-efficient single-blade-passage approach. Finally, a radial basis function neural network is used to establish a surrogate model that correlates the input parameters and the output loss. Findings The data-driven hub loss model shows higher prediction accuracy than the traditional physics-based loss models. It can accurately capture the circumferentially and radially nonuniform variation trends of the losses and the associated absolute magnitudes in a BLI fan under different blade load, inlet distortion intensity and rotating speed conditions. Compared with the high-fidelity full-annulus URANS results, the averaged relative prediction errors of the data-driven hub loss model are kept less than 10%. Originality/value The originality of this paper lies in developing a new method for predicting flow loss in a BLI fan rotor blade hub region. This method offers higher prediction accuracy than the traditional loss models and lower computational time cost than the full-annulus URANS approach, which could realize fast evaluations of fan aerodynamic performances and provide technical support for designing high-performance BLI fans.

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Pitchwise casing treatment for effects of grooves on dynamics of vortices and loss of blade tip region of a compressor cascade

Cao

Yang²,

Gao³

et al. 2022

Aerospace Science and Technology

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Comparison of Flow Mechanism of Blade Sweep between a Transonic Single Rotor and a Rotor in Stage Environment

Cited by 8 publications

References 31 publications

Numerical investigation on the influence of nonuniform tip clearance on rotor tip-clearance flow field structure

Numerical investigation on the influence of nonuniform tip clearance on rotor tip-clearance flow field structure

A data-driven flow loss prediction model for the blade hub region of a boundary layer ingestion fan rotor

Pitchwise casing treatment for effects of grooves on dynamics of vortices and loss of blade tip region of a compressor cascade

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