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

Abstract

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.

Design and Decomposition Analysis of Mixing Zone Structures on Flame Dynamics for a Swirl Burner

“…In case 5, the fluctuation level in PFR was 12 times larger than that in the temperature. Comparing the three types of flame in Table 3, the type-C flame cases (3,9,11,14, and 15) all showed higher temperature at the outlet and integral PFR compared with the arithmetic averaged values among the 16 cases. The type-B flame cases (1, 2, 4, 5, 7, 8, 12, and 16) all showed similar or lower values of temperature and PFR compared to the averaged levels.…”

“…Without explicitly comprehending the governing equation, DMD is an effective method that can reveal dynamic process through the operator matrix [13][14][15]. The algorithm of DMD contains two aspects: one is using the singular value decomposition (SVD) to reduce the computational cost of matrix decomposition.…”

“…However, limited information on how flow structures affect the flame frequency response can be extracted from the FTF. The dynamic mode decomposition (DMD) [14][15][16] method has been applied to explore the potential for the transient flow field data generated by the LES. It is based on the matrix decomposition of the represented coherent structures and can be employed to calculate the frequency band.…”

Data-driven analysis and prediction of dynamic postprandial metabolic response to multiple dietary challenges using dynamic mode decomposition

“…Model complexity in pDMDc for metabotyping, i.e., the choice of and (for simplicity we choose ), was assessed by identifying the inflection point in the scree plot of the singular values derived from the SVD = ( 28 , 29 ). Further, we classified the most dominant dynamical profile by clustering the covariance matrix of the measured data for each metabolite averaged over all individuals and diets ( Equations 23, 24 ).…”

Spectral analysis of OH-PLIF snapshots of a bluff body wake

“…In the field of combustion, (Kostka et al, 2012) provided an analysis of the bluff body wake using high-speed chemiluminescence images. Since then, several papers can be found in the literature that involve the utilization of the proper orthogonal decomposition on high-speed flow and flame imagery (Blanchard et al, 2014;Caswell et al, 2014;Emerson, 2013;Monfort, 2015;Morales et al, 2021;Roy et al, 2015;Shaw et al, 2019;Wickersham et al, 2014;Yang et al, 2020).…”