Effect of non-ambient pressure conditions and Lewis number variation on direct numerical simulation of turbulent Bunsen flames at low turbulence intensity

Rasool, Raheel; Chakraborty, Nilanjan; Klein, Markus

doi:10.1016/j.combustflame.2021.111500

Cited by 18 publications

(11 citation statements)

References 62 publications

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“…Recent analysis indicated that the pressure effects on hydrodynamic instability agree between simple and detailed chemistry simulations, provided the Arrhenius parameters are chosen in a physically consistent manner [29]. Finally, it was shown that the effect of pressure and Lewis number on hydrodynamic and thermodiffusive instability from simple chemistry is in qualitative agreement with experimental data [30]. Properties of both methodologies, together with the advantages and disadvantages of SC and DC, are summarized in Table 1.…”

Section: Introductionmentioning

confidence: 71%

“…The present work deals with stoichiometric methane-air flames and the investigation of nonunity Lewis number flames is beyond the scope of the present work. Although several analyses indicate that Lewis number effects can at least be qualitatively captured using SC DNS (e.g., [12,26,30]), a quantitative assessment, similar to this work, will be needed in future. It is also well known that flame geometry [15,31] has implications on flame propagation statistics, and quantitative confirmation regarding the accuracy of SC simulations will be needed in this respect as well.…”

Section: Discussionmentioning

confidence: 99%

“…For SC, the wellknown, fully compressible DNS code SENGA [41] was used. Here, the conservation equations of mass, momentum, energy, and species (presented in detail in [30]) are solved in nondimensional form, and the chemistry is represented using a single reaction progress variable. The reaction rate is calculated using an irreversible, simplified, Arrhenius-type mechanism.…”

Section: Direct Numerical Simulation Databasementioning

confidence: 99%

“…Properties of both methodologies, together with the advantages and disadvantages of SC and DC, are summarized in Table 1. Parametric variations Dozens possible [30,31] Typically, very few (e.g., 1-4) [32][33][34]; more limited in terms of nondimensional numbers, pressure, or size of domain Data analysis Straightforward, unambiguous results.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Flame Propagation Statistics Extracted from Direct Numerical Simulation Based on Simple and Detailed Chemistry—Part 1: Fundamental Flame Turbulence Interaction

et al. 2021

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In the present study, flame propagation statistics from turbulent statistically planar premixed flames obtained from simple and detailed chemistry, three-dimensional Direct Numerical Simulations, were evaluated and compared to each other. To this end, a new database was established encompassing five different conditions on the turbulent premixed combustion regime diagram, using nearly identical numerical methods and the same initial and boundary conditions. A detailed discussion of the advantages and limitations of both approaches is provided, including the difference in carbon footprint for establishing the database. It is shown that displacement speed statistics and their interrelation with curvature and tangential strain rate are in very good qualitative and reasonably good quantitative agreement between simple and detailed chemistry Direct Numerical Simulations. Hence, it is concluded that simple chemistry simulations should retain their importance for future combustion research, and the environmental impact of high-performance computing methods should be carefully chosen in relation to the goals to be achieved.

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Section: Introductionmentioning

confidence: 71%

Section: Discussionmentioning

confidence: 99%

Section: Direct Numerical Simulation Databasementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparison of Flame Propagation Statistics Extracted from Direct Numerical Simulation Based on Simple and Detailed Chemistry—Part 1: Fundamental Flame Turbulence Interaction

et al. 2021

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“…In these analyses, once more, statistically planar turbulent premixed flames have been considered and the same holds true for the analysis of the evolution of flame surface density [30] as well as surface density function [31] which are highly relevant quantities for modelling turbulent premixed combustion. While some effects of curvature might be annihilated in a mean sense for statistically planar flames, the mean curvature plays an important role for Lewis number effects on flame speed statistics, as demonstrated by Ozel Erol et al [32] for spherical flames and by Rasool et al [33] for Bunsen flames. Because of the Lewis number dependence, it might be expected that displacement speed statistics will be different for reaction progress variable definitions based on different species mass fractions.…”

Section: Introductionmentioning

confidence: 97%

Comparison of Flame Propagation Statistics Based on Direct Numerical Simulation of Simple and Detailed Chemistry. Part 2: Influence of Choice of Reaction Progress Variable

et al. 2021

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Flame propagation statistics for turbulent, statistically planar premixed flames obtained from 3D Direct Numerical Simulations using both simple and detailed chemistry have been evaluated and compared to each other. To achieve this, a new database has been established encompassing five different conditions on the turbulent combustion regime diagram, using nearly identical numerical methods and the same initial and boundary conditions. The discussion includes interdependencies of displacement speed and its individual components as well as surface density function (i.e., magnitude of the reaction progress variable) with tangential strain rate and curvature. For the analysis of detailed chemistry Direct Numerical Simulation data, three different definitions of reaction progress variable, based on and mass fractions will be used. While the displacement speed statistics remain qualitatively and to a large extent quantitatively similar for simple chemistry and detailed chemistry, there are pronounced differences for its individual contributions which to a large extent depend on the definition of reaction progress variable as well as on the chosen isosurface level. It is concluded that, while detailed chemistry simulations provide more detailed information about the flame structure, the choice of the reaction progress variable definition and the choice of the resulting isosurface give rise to considerable uncertainty in the interpretation of displacement speed statistics, sometimes even showing opposing trends. Simple chemistry simulations are shown to provide (a) the global flame propagation statistics which are qualitatively similar to the corresponding results from detailed chemistry simulations, (b) remove the uncertainties with respect to the choice of reaction progress variable, and (c) are more straightforward to compare with theoretical analysis or model assumptions that are mostly based on simple chemistry assumptions.

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A Comparison of Evaluation Methodologies of the Fractal Dimension of Premixed Turbulent Flames in 2D and 3D Using Direct Numerical Simulation Data

Herbert,

Chakraborty,

Klein

2024

Flow Turbulence Combust

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A Direct Numerical Simulation (DNS) database of statistically planar flames ranging from the wrinkled flamelets to the thin reaction zones regime and DNS data for a Bunsen premixed flame representing the wrinkled flamelets regime have been utilised to evaluate the fractal dimensions of flame surfaces using the filtering dimension method, the box-counting algorithm and the correlation dimension approach. The fractal dimension evaluated based on the fully resolved three-dimensional data has been found to be reasonably approximated by adding unity to the equivalent fractal dimension evaluated based on two-dimensional projections irrespective of the methodology of extracting fractal dimension. This indicates that the flame surface can be approximated as a self-similar fractal surface for the range of Karlovitz and Damköhler numbers considered here. While all methods, provide results identical to each other for benchmark problems, it has been found that the fractal dimension evaluation based on box-counting method provides almost identical results as that obtained using the filtering dimension method for both three and two dimensions, while the fractal dimensions based on the correlation dimension tend to be slightly smaller. The findings of the current analysis have the potential to be used to reliably estimate the actual fractal dimension in 3D based on experimentally obtained 2D binarised reaction progress variable field. The inner cut-off scales estimated based on all three methodologies yield comparable results in terms of order of magnitude with the box-counting method predicting a smaller value of inner cut-off scale in comparison to other methods. The execution times for fractal dimension extraction based on filtering dimension and box-counting methodologies are found to be comparable but the correlation dimension method is found to be considerably faster than the two alternative approaches and provides results consistent with theoretical bounds in all cases.

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Effect of non-ambient pressure conditions and Lewis number variation on direct numerical simulation of turbulent Bunsen flames at low turbulence intensity

Cited by 18 publications

References 62 publications

Comparison of Flame Propagation Statistics Extracted from Direct Numerical Simulation Based on Simple and Detailed Chemistry—Part 1: Fundamental Flame Turbulence Interaction

Comparison of Flame Propagation Statistics Extracted from Direct Numerical Simulation Based on Simple and Detailed Chemistry—Part 1: Fundamental Flame Turbulence Interaction

Comparison of Flame Propagation Statistics Based on Direct Numerical Simulation of Simple and Detailed Chemistry. Part 2: Influence of Choice of Reaction Progress Variable

A Comparison of Evaluation Methodologies of the Fractal Dimension of Premixed Turbulent Flames in 2D and 3D Using Direct Numerical Simulation Data

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