Flame Induced Flow Features in the Presence of Darrieus-Landau Instability

Lamioni, Rachele; Lapenna, Pasquale Eduardo; Troiani, G.; Creta, Francesco

doi:10.1007/s10494-018-9936-0

Cited by 23 publications

(9 citation statements)

References 49 publications

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“…The one-step chemistry dataset has been presented in [2] and it has also been used for modelling purposes in [7]. It has been developed using a well-established numerical framework based on a one-step irreversible reaction controlled by the concentration of a deficient reactant [16][17][18][19]. This framework is implemented in a modified version [20][21][22][23] of the massively-parallel, spectral element [24], incompressible and low-Mach number code nek5000 [25].…”

Section: One-step Chemistry Datasetmentioning

confidence: 99%

“…The unfiltered deficient reactant system of governing equations is described in [17,19] and is comprised of two transport equations, respectively for the controlling reactant concentration Y, normalised with the unburned concentration Y u , and for the nondimensional temperature θ . A progress variable based on the controlling reactant is also readily defined as C = 1 − Y.…”

Section: Modelling Strategymentioning

confidence: 99%

“…where, as mentioned, the * superscript denotes the quantities directly established from a filtered dataset. Note that in the one-step chemistry DNS, the reaction rate can be directly expressed as a 2D table ω = ω(C, θ) with a simple analytical expression according to a one-step irreversible Arrhenius reaction [17,19]. Filtered laminar diffusion terms These terms for both temperature and reactant are usually neglected or simply approximated as…”

Section: Modelling Strategymentioning

confidence: 99%

“…Figure 6 displays the tables representing the values of the unclosed terms of Equations (18) and (19), obtained using the TD1 flame dataset and conditionally averaged on the filtered progress variable and temperature. Also shown are the loci, in the θ -C space, of both the filtered and unfiltered flamelet profiles obtained from a 1D unstretched laminar flame.…”

Section: Summary Of the Filtered Equationsmentioning

confidence: 99%

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Data-driven subfilter modelling of thermo-diffusively unstable hydrogen–air premixed flames

Lapenna

Berger

Attili

et al. 2021

Combustion Theory and Modelling

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This article is dedicated to Moshe Matalon on the occasion of his 70th birthday, for his numerous contributions to the field of combustion and, in particular, to the rich and varied topic of premixed flame stability. Here, we follow in his footsteps and propose a subfilter modelling framework for thermo-diffusively unstable premixed flames, such as lean hydrogen-air flames. Performing an optimal estimator analysis for the unfiltered and filtered heat release rate of the lean premixed hydrogen-air flames, the latter is found to require at least two scalars for an appropriate representation while for large filter sizes, the heat release appears to require only one scalar for parametrisation. As a result, we develop a modelling strategy based on the construction of thermochemical tables for each unclosed term as a function of two variables as well as the filter size. The framework is based on the filtered tabulated chemistry approach, where, in lieu of a one-dimensional unstretched flame, we adopt a data-driven paradigm and filter fully resolved two-dimensional simulations of variable size. Models originating from small-and medium-sized simulations are tested a-priori on a large-size simulation, thus highlighting the role of the lateral domain in the dataset used for tabulation. The concept of a minimum domain size is thus discussed, leading to a dataset exhibiting the minimal properties for sufficiently accurate thermochemical tables. The strategy is shown to be more accurate than a classical one-dimensional filtered tabulated chemistry approach and shows promise in future LES modelling of laboratory and industrial scale hydrogen flames.

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Section: One-step Chemistry Datasetmentioning

confidence: 99%

Section: Modelling Strategymentioning

confidence: 99%

Section: Modelling Strategymentioning

confidence: 99%

Section: Summary Of the Filtered Equationsmentioning

confidence: 99%

See 2 more Smart Citations

Data-driven subfilter modelling of thermo-diffusively unstable hydrogen–air premixed flames

Lapenna

Berger

Attili

et al. 2021

Combustion Theory and Modelling

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“…Recent investigations have revealed a substantial difference in the morphological and propagative properties of large-scale ( L > λ c ) compared to small scale flames. The characteristic flame wrinkling due to DL instability in large-scale flames was observed in both laminar and turbulent settings in multiple experimental [9][10][11][12] and numerical [13][14][15][16][17][18] studies. The DL induced morphology was found to be associated to an increase in flame area and to a consequent increase in laminar as well as turbulent propagation speed.…”

Section: Introductionmentioning

confidence: 96%

Large scale effects in weakly turbulent premixed flames

Lapenna

Lamioni

Troiani

et al. 2019

Proceedings of the Combustion Institute

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In this study we numerically investigate large scale premixed flames in weakly turbulent flow fields. A large scale flame is classified as such based on a reference hydrodynamic lengthscale being larger than a neutral (cutoff) lengthscale for which the hydrodynamic or Darrieus-Landau (DL) instability is balanced by stabilizing diffusive effects. As a result, DL instability can develop for large scale flames and is inhibited otherwise. Direct numerical simulations of both large scale and small scale three-dimensional, weakly turbulent flames are performed at constant Karlovitz and turbulent Reynolds number, using two paradigmatic configurations, namely a statistically planar flame and a slot Bunsen flame. As expected from linear stability analysis, DL instability induces its characteristic cusp-like corrugation only on large scale flames. We therefore observe significant morphological and topological differences as well as DL-enhanced turbulent flame speeds in large scale flames. Furthermore, we investigate issues related to reaction rate modeling in the context of flame surface density closure. Thicker flame brushes are observed for large scale flames resulting in smaller flame surface densities and overall larger wrinkling factors.

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