Dynamic mode decomposition analysis of flow characteristics of an airfoil with leading edge protuberances

Zhao, Ming; Zhao, Yijia; Liu, Zhengxian

doi:10.1016/j.ast.2020.105684

Cited by 41 publications

(7 citation statements)

References 34 publications

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“…Despite the great progress made using DMD in the fields of flow-field analysis, fluidsolid interaction and flow control, investigations into flow-field reconstruction and prediction remain in their early stages. One restraining factor is the rather strong HFF 33,10 requirement for flow data to be linearly assumed or statistically steady, but it is practical to illustrate the majority of flow characteristics with periodic fluctuations, such as cylinder flow (Jang et al, 2021) and airfoil flow (Zhao et al, 2020) without a dynamic stall, with the time-averaged flow and several low-order modes from DMD. In turbomachinery, the flows are unsteady but also periodic because of the interaction between the rotor and the stators, so with the exception of stalls caused by severe nonlinearities, it is possible to reproduce unsteady flow using DMD.…”

Section: Predicting Flow Fieldsmentioning

confidence: 99%

Multilevel method for predicting flow fields in radial turbines based on sparsity-promoting dynamic mode decomposition

Zheng

Yang

2023

HFF

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Purpose The purpose of this study is to propose a fast method for predicting flow fields with periodic behavior with verification in the context of a radial turbine to meet the urgent requirement to effectively capture the unsteady flow characteristics in turbomachinery. Aiming at meeting the urgent requirement to effectively capture the unsteady flow characteristics in turbomachinery, a fast method for predicting flow fields with periodic behavior is proposed here, with verification in the context of a radial turbine (RT). Design/methodology/approach Sparsity-promoting dynamic mode decomposition is used to determine the dominant coherent structures of the unsteady flow for mode selection, and for flow-field prediction, the characteristic parameters including amplitude and frequency are predicted using one-dimensional Gaussian fitting with flow rate and two-dimensional triangulation-based cubic interpolation with both flow rate and rotation speed. The flow field can be rebuilt using the predicted characteristic parameters and the chosen model. Findings Under single flow-rate variation conditions, the turbine flow field can be recovered using the first seven modes and fitted amplitude modulus and frequency with less than 5% error in the pressure field and less than 9.7% error in the velocity field. For the operating conditions with concurrent flow-rate and rotation-speed fluctuations, the relative error in the anticipated pressure field is likewise within an acceptable range. Compared to traditional numerical simulations, the method requires a lot less time while maintaining the accuracy of the prediction. Research limitations/implications It would be challenging and interesting work to extend the current method to nonlinear problems. Practical implications The method presented herein provides an effective solution for the fast prediction of unsteady flow fields in the design of turbomachinery. Originality/value A flow prediction method based on sparsity-promoting dynamic mode decomposition was proposed and applied into a RT to predict the flow field under various operating conditions (both rotation speed and flow rate change) with reasonable prediction accuracy. Compared with numerical calculations or experiments, the proposed method can greatly reduce time and resource consumption for flow field visualization at design stage. Most of the physics information of the unsteady flow was maintained by reconstructing the flow modes in the prediction method, which may contribute to a deeper understanding of physical mechanisms.

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Section: Predicting Flow Fieldsmentioning

confidence: 99%

Multilevel method for predicting flow fields in radial turbines based on sparsity-promoting dynamic mode decomposition

Zheng

Yang

2023

HFF

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“…So far in the literature, the tubercles airfoil aerodynamics are investigated by taking the baseline airfoil shape as NACA0020, 2,4,5,[12][13][14]18,23,24 NACA0021, 3,6,15,19,[25][26][27][28][29] and NACA63 4 -021 9,17,22,[30][31][32][33][34] with A ranging from 1.3% to 12% of c and k between 11% and 50% of c. Notice that the shape of the baseline NACA0020, NACA0021, and NACA63 4 -021 airfoils is more or less similar, as shown in Fig. 2(b), where the t/c % 21%.…”

Section: Introductionmentioning

confidence: 99%

On the investigation of the aerodynamics performance and associated flow physics of the optimized tubercle airfoil

Pinapatruni,

Duddupudi,

Dash

et al. 2024

Physics of Fluids

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In the present study, the evolutionary multi-objective optimization is employed to design the optimum amplitude and wavelength of sinusoidal leading-edge tubercles for the NACA0012 (National Advisory Committee for Aeronautics) airfoil to improve its aerodynamic performance at Reynolds number of 5.0 × 104 than that of the NACA0012 smooth leading-edge or baseline airfoil. Here, the optimum tubercle is found to have an amplitude of 11.71% and a wavelength of 25% of the baseline airfoil chord, respectively. Through a combination of in-house water tunnel experiments and numerical simulations, it is additionally established that the optimized tubercle airfoil exhibits superior lift and reduced drag characteristics compared to the baseline airfoil, particularly in the post-stall high angle of attack regime. Furthermore, it is noticed that the optimized tubercle design enhances the gap between large separation regions or stall cells along the tubercle airfoil span during the post-stall regime. Consequently, a more pronounced attached flow regime is developed between the consecutive stall cells, contributing to the tubercle airfoil's improved aerodynamic characteristics compared to the baseline airfoil. Our investigations also revealed that the formation and arrangement of the stall cells on the tubercle airfoil span are associated with a biased wake mechanism similar to the one observed in the wake of side-by-side arranged circular cylinders.

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“…Central to their exceptional maneuverability are the finely tuned mechanisms within their pectoral flippers [2], which serve as their primary means of controlling posture and direction. Among the distinctive features of humpback whale flippers are peculiar serrations along their leading edges, believed to be instrumental in optimizing their hydrodynamic performance [3][4][5]. In the context of advancing aerodynamic designs, this study delves into the application of tubercle leading edges, a concept inspired by the natural adaptations seen in humpback whale flippers.…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Investigating Mechanical Response and Structural Integrity of Tubercle Leading Edge under Static Loads

Esmaeili,

Jabbari,

Zehtabzadeh

et al. 2024

Modelling

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This investigation into the aerodynamic efficiency and structural integrity of tubercle leading edges, inspired by the agile maneuverability of humpback whales, employs a multifaceted experimental and computational approach. By utilizing static load extensometer testing complemented by computational simulations, this study quantitatively assesses the impacts of unique wing geometries on aerodynamic forces and structural behavior. The experimental setup, involving a Wheatstone full-bridge circuit, measures the strain responses of tubercle-configured leading edges under static loads. These measured strains are converted into stress values through Hooke’s law, revealing a consistent linear relationship between the applied loads and induced strains, thereby validating the structural robustness. The experimental results indicate a linear strain increase with load application, demonstrating strain values ranging from 65 με under a load of 584 g to 249 με under a load of 2122 g. These findings confirm the structural integrity of the designs across varying load conditions. Discrepancies noted between the experimental data and simulation outputs, however, underscore the effects of 3D printing imperfections on the structural analysis. Despite these manufacturing challenges, the results endorse the tubercle leading edges’ capacity to enhance aerodynamic performance and structural resilience. This study enriches the understanding of bio-inspired aerodynamic designs and supports their potential in practical fluid mechanics applications, suggesting directions for future research on manufacturing optimizations.

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Dynamic mode decomposition analysis of flow characteristics of an airfoil with leading edge protuberances

Cited by 41 publications

References 34 publications

Multilevel method for predicting flow fields in radial turbines based on sparsity-promoting dynamic mode decomposition

Multilevel method for predicting flow fields in radial turbines based on sparsity-promoting dynamic mode decomposition

On the investigation of the aerodynamics performance and associated flow physics of the optimized tubercle airfoil

Investigating Mechanical Response and Structural Integrity of Tubercle Leading Edge under Static Loads

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