Analysis of dynamic stall flow field of high bypass fan rotor based on airworthiness certification

2020 ◽  
Vol 234 (11) ◽  
pp. 1757-1769
Author(s):  
Kai Zhang ◽  
AJ Wang
Keyword(s):  
Flow Field ◽  
Unsteady Flow ◽  
Field Data ◽  
Decomposition Methods ◽  
Modal Identification ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Complex Flow ◽  
Mode Decomposition ◽  
Proper Orthogonal

In order to ensure flight safety, the stall test is one of the most important steps in the airworthiness certification phase of civil aircraft. The twisted-swept fan is one of the most important components of the high bypass ratio engine. The unsteady flow field of the fan rotor stall condition is obtained by numerical simulation. At the same time, the time series flow field data of the stall condition flow field is acquired. The modal analysis of the unsteady flow field at stall condition was performed using the dynamic mode decomposition and proper orthogonal decomposition methods. Through modal identification of a large number of unsteady flow field data, the eigenvalues and corresponding modal information about the unsteady flow field change process are obtained. Finally, the evolution process of the unsteady flow field of the fan rotor under stall condition is visually demonstrated, and the coherent structures of different scales in the complex flow field under stall condition are revealed.

Modeling the Turbulent Wake Behind a Wall-Mounted Square Cylinder

2020 ◽  
Author(s):  
Christian Amor ◽  
José M Pérez ◽  
Philipp Schlatter ◽  
Ricardo Vinuesa ◽  
Soledad Le Clainche
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Turbulent Wake ◽  
Orthogonal Decomposition ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Square Cylinder ◽  
Complex Flow ◽  
Reduced Order ◽  
Mode Decomposition ◽  
Proper Orthogonal

Abstract This article introduces some soft computing methods generally used for data analysis and flow pattern detection in fluid dynamics. These techniques decompose the original flow field as an expansion of modes, which can be either orthogonal in time (variants of dynamic mode decomposition), or in space (variants of proper orthogonal decomposition) or in time and space (spectral proper orthogonal decomposition), or they can simply be selected using some sophisticated statistical techniques (empirical mode decomposition). The performance of these methods is tested in the turbulent wake of a wall-mounted square cylinder. This highly complex flow is suitable to show the ability of the aforementioned methods to reduce the degrees of freedom of the original data by only retaining the large scales in the flow. The main result is a reduced-order model of the original flow case, based on a low number of modes. A deep discussion is carried out about how to choose the most computationally efficient method to obtain suitable reduced-order models of the flow. The techniques introduced in this article are data-driven methods that could be applied to model any type of non-linear dynamical system, including numerical and experimental databases.

scholarly journals Numerical Analysis of the Flow around Two Square Cylinders in a Tandem Arrangement with Different Spacing Ratios Based on POD and DMD Methods

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 903
Author(s):  
Feng Wang ◽  
Xiaodong Zheng ◽  
Jianming Hao ◽  
Hua Bai
Keyword(s):  
Flow Field ◽  
Flow Characteristics ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Square Cylinder ◽  
Main Mode ◽  
Square Cylinders ◽  
Mode Decomposition ◽  
The Difference ◽  
Proper Orthogonal

To more clearly understand the changes in flow characteristics around two square cylinders with different spacing ratios, the main mode of the flow field was extracted by using the Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) methods. The changes in the main mode of the flow field at different spacing ratios and the difference of the time series were analyzed and compared. This processing can separate the mixed information in the flow field and obtain the dominant modes in the flow field. These main modes can clearly reflect the dominant flow characteristics in the flow field. The analysis results show that when L/D = 2, the flow field structure is consistent with the flow field around a single square cylinder. When L/D = 2.5–3.5, the vortex shedding from upstream cylinders combines with the vortex near the downstream cylinders. This mutual coupling causes a significant change in the drag coefficient value of the downstream cylinder. When L/D = 4, the main vortex from the upstream cylinder can be completely shed, which means that the upstream and downstream square cylinder vortices start to become independent. The main focus of this paper is to use the advantages of POD and DMD to obtain several modes with higher energy in the flow field. Furthermore, it can be considered that these main modes can fully reflect the flow characteristics of the flow field.

scholarly journals Study on Flow Characteristics in Volute of Centrifugal Pump Based on Dynamic Mode Decomposition

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Yi-bin Li ◽  
Chang-hong He ◽  
Jian-zhong Li
Keyword(s):  
Flow Field ◽  
Unsteady Flow ◽  
Centrifugal Pump ◽  
Flow Characteristics ◽  
Internal Flow ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Rate Condition ◽  
Blade Passing Frequency ◽  
Mode Decomposition

To investigate the unsteady flow characteristics and their influence mechanism in the volute of centrifugal pump, the Reynolds time-averaged N-S equation, RNG k-ε turbulence model, and structured grid technique are used to numerically analyze the transient flow-field characteristics inside the centrifugal pump volute. Based on the quantified parameters of flow field in the volute of centrifugal pump, the velocity mode contours and oscillation characteristics of the mid-span section of the volute of centrifugal pump are obtained by dynamic mode decomposition (DMD) for the nominal and low flow-rate condition. The research shows that the first-order average flow mode extracted by DMD is the dominant flow structure in the flow field of the volute. The second-order and third-order modes are the most important oscillation modes causing unsteady flow in the volute, and the characteristic frequency of the two modes is consistent with the blade passing frequency and the 2x blade passing frequency obtained by the fast Fourier transform (FFT). By reconstructing the internal flow field of the volute with the blade passing frequency for the nominal flow-rate condition, the periodic variation of the unsteady flow structure in the volute under this frequency is visually reproduced, which provides some ideas for the study of the unsteady structure in the internal flow field of centrifugal pumps.

scholarly journals Dynamic Mode Decomposition Analysis of Spatially Agglomerated Flow Databases

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2134
Author(s):  
Binghua Li ◽  
Jesús Garicano-Mena ◽  
Yao Zheng ◽  
Eusebio Valero
Keyword(s):  
Flow Field ◽  
Clustering Algorithms ◽  
Decomposition Analysis ◽  
Turbulent Channel Flow ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Complex Flow ◽  
Computational Performance ◽  
Mode Decomposition ◽  
Multiple Variables

Dynamic Mode Decomposition (DMD) techniques have risen as prominent feature identification methods in the field of fluid dynamics. Any of the multiple variables of the DMD method allows to identify meaningful features from either experimental or numerical flow data on a data-driven manner. Performing a DMD analysis requires handling matrices V ∈ R n p × N , where n p and N are indicative of the spatial and temporal resolutions. The DMD analysis of a complex flow field requires long temporal sequences of well resolved data, and thus the memory footprint may become prohibitively large. In this contribution, the effect that principled spatial agglomeration (i.e., reduction in n p via clustering) has on the results derived from the DMD analysis is investigated. We compare twelve different clustering algorithms on three testcases, encompassing different flow regimes: a synthetic flow field, a R e D = 60 flow around a cylinder cross section, and a R e τ ≈ 200 turbulent channel flow. The performance of the clustering techniques is thoroughly assessed concerning both the accuracy of the results retrieved and the computational performance. From this assessment, we identify DBSCAN/HDBSCAN as the methods to be used if only relatively high agglomeration levels are affordable. On the contrary, Mini-batch K-means arises as the method of choice whenever high agglomeration n p ˜ / n p ≪ 1 is possible.

scholarly journals Analysis of transonic buffet using dynamic mode decomposition

2021 ◽  
Vol 62 (4) ◽  
Author(s):  
Antje Feldhusen-Hoffmann ◽  
Christian Lagemann ◽  
Simon Loosen ◽  
Pascal Meysonnat ◽  
Michael Klaas ◽  
...  
Keyword(s):  
Shock Wave ◽  
Flow Field ◽  
Acoustic Waves ◽  
Feedback Loop ◽  
Measurement Data ◽  
Dynamic Mode Decomposition ◽  
Recirculation Region ◽  
Dynamic Mode ◽  
Mode Decomposition ◽  
Transonic Buffet

AbstractThe buffet flow field around supercritical airfoils is dominated by self-sustained shock wave oscillations on the suction side of the wing. Theories assume that this unsteadiness is driven by a feedback loop of disturbances in the flow field downstream of the shock wave whose upstream propagating part is generated by acoustic waves. High-speed particle-image velocimetry measurements are performed to investigate this feedback loop in transonic buffet flow over a supercritical DRA 2303 airfoil. The freestream Mach number is $$M_{\infty } = 0.73$$ M ∞ = 0.73 , the angle of attack is $$\alpha = 3.5^{\circ }$$ α = 3 . 5 ∘ , and the chord-based Reynolds number is $${\mathrm{Re}}_{c} = 1.9\times 10^6$$ Re c = 1.9 × 10 6 . The obtained velocity fields are processed by sparsity-promoting dynamic mode decomposition to identify the dominant dynamic features contributing strongest to the buffet flow field. Two pronounced dynamic modes are found which confirm the presence of two main features of the proposed feedback loop. One mode is related to the shock wave oscillation frequency and its shape includes the movement of the shock wave and the coupled pulsation of the recirculation region downstream of the shock wave. The other pronounced mode represents the disturbances which form the downstream propagating part of the proposed feedback loop. The frequency of this mode corresponds to the frequency of the acoustic waves which are generated by these downstream traveling disturbances and which form the upstream propagating part of the proposed feedback loop. In this study, the post-processing, i.e., the DMD, is highlighted to substantiate the existence of this vortex mode. It is this vortex mode that via the Lamb vector excites the shock oscillations. The measurement data based DMD results confirm numerical findings, i.e., the dominant buffet and vortex modes are in good agreement with the feedback loop suggested by Lee. Graphic abstract

scholarly journals Analysis of V-Gutter Reacting Flow Dynamics Using Proper Orthogonal and Dynamic Mode Decompositions

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4886 ◽  
Author(s):  
Yang Yang ◽  
Xiao Liu ◽  
Zhihao Zhang
Keyword(s):  
Shear Layer ◽  
Large Scale ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Reacting Flow ◽  
Eddy Simulation ◽  
Mode Decomposition ◽  
Wake Instability ◽  
Shedding Frequency ◽  
Proper Orthogonal

The current work is focused on investigating the potential of data-driven post-processing techniques, including proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) for flame dynamics. Large-eddy simulation (LES) of a V-gutter premixed flame was performed with two Reynolds numbers. The flame transfer function (FTF) was calculated. The POD and DMD were used for the analysis of the flame structures, wake shedding frequency, etc. The results acquired by different methods were also compared. The FTF results indicate that the flames have proportional, inertial, and delay components. The POD method could capture the shedding wake motion and shear layer motion. The excited DMD modes corresponded to the shear layer flames’ swing and convect motions in certain directions. Both POD and DMD could help to identify the wake shedding frequency. However, this large-scale flame oscillation is not presented in the FTF results. The negative growth rates of the decomposed mode confirm that the shear layer stabilized flame was more stable than the flame possessing a wake instability. The corresponding combustor design could be guided by the above results.

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