Characterization of jet-in-hot-coflow flames using tangential stretching rate

Li, Zhiyi; Galassi, Riccardo Malpica; Ciottoli, Pietro Paolo; Parente, Alessandro; Valorani, Mauro

doi:10.1016/j.combustflame.2019.06.023

Cited by 19 publications

(23 citation statements)

References 63 publications

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“…It was used to study different coal flames (Tufano et al 2018;Wan et al 2019;Rieth et al 2019;, assess the stabilization mechanism of supersonic lifted flames (Bouheraoua et al 2017) and lifted hydrogen flames (Benim et al 2019), classify regions of industrial burners by the combustion regime , study auto-ignition of supercritical hydrothermal flames (Song et al 2019), analyze extinction and re-ignition events (Sripakagorn et al 2004) and gain insight into partially premixed DME flames . It was further applied to scram jets (Shen et al 2020;, Moderate or Intense Low oxygen Dilution (MILD) combustion (Amaduzzi et al 2020), compression ignition engines (An et al 2018), double-cone burners , coaxial diffusion flames , edge flames (Duboc et al 2019) and jet-in-hot-coflow flames in conjunction with tangential stretching rate analysis (Li et al 2019). In order to evaluate the flame index experimentally, Rosenberg et al (2013Rosenberg et al ( , 2015 introduced tracer gases.…”

Section: Introductionmentioning

confidence: 99%

Identification of Flame Regimes in Partially Premixed Combustion from a Quasi-DNS Dataset

Zirwes

Zhang

Habisreuther

et al. 2020

Flow Turbulence Combust

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Identifying combustion regimes in terms of premixed and non-premixed characteristics is an important task for understanding combustion phenomena and the structure of flames. A quasi-DNS database of the compositionally inhomogeneous partially premixed Sydney/Sandia flame in configuration FJ-5GP-Lr75-57 is used to directly compare different types of flame regime markers from literature. In the simulation of the flame, detailed chemistry and diffusion models are utilized and no turbulence and combustion models are used as the flame front and flow are fully resolved near the nozzle. This allows evaluating the regime markers as a post-processing step without modeling assumptions and directly comparing regime markers based on gradient alignment, drift term analysis and gradient free regime identification. The goal is not to find the correct regime marker, which might be impossible due to the different set of assumptions of every marker and the generally vague definition of the partially premixed regime itself, but to compare their behavior when applied to a resolved turbulent flame with partially premixed characteristics.

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Section: Introductionmentioning

confidence: 99%

Identification of Flame Regimes in Partially Premixed Combustion from a Quasi-DNS Dataset

Zirwes

Zhang

Habisreuther

et al. 2020

Flow Turbulence Combust

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“…Methane-air combustion chemistry is modelled using a skeletal mechanism [18], which was shown to be adequate for MILD conditions in [13] and in [8,19]. For the finite-rate based LES of a combustion with the current geometry, such mechanism is considered to be the best to balance between CPU hour requirement and accuracy.…”

Section: Combustion Modelsmentioning

confidence: 99%

“…The tangential stretching rate (TSR) denotes the level of stretching or contraction of the dynamics of interest along the direction of a vector field and is used here to characterize the most energy-containing time scales developing in the chemically reactive system of interest here [23,24]. This method was used for turbulent premixed flames [25] and MILD flames [19] in previous studies. The stretching rate of the reactor dynamics in the direction tangential to the vector field g(z) is ωτ( g) := N i=1 W i ( g) λ i , with λ i as the eigenvalue of i-th mode.…”

Section: Tsr Obtained From Csp Analysismentioning

confidence: 99%

Study of MILD combustion using LES and advanced analysis tools

Tomasch

Chen

et al. 2021

Proceedings of the Combustion Institute

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A cylindrical confined combustor operating under MILD condition is investigated using LES. The combustion and its interaction with turbulence are modeled using two reactor based models, PaSR and EDC. Results show that the Partially Stirred Reactor (PaSR) model yields improved estimation for mean temperature and species mole fractions compared to Eddy Dissipation Concept (EDC). LES data are analysed using advanced post-processing methods such as the chemical Tangential Stretching Rate (TSR), balance analysis and local Principle Component (PCA) analysis. TSR can identify chemical explosive (ignition-like) and contractive (burnt) regions. With the balance analysis of the convective, diffusive and reactive terms in temperature equation, regions with substantial heat release coming from ignition or flame are identified. The local PCA analysis classifies the whole domain into clusters (regions with specific features) and provides the leading species in each cluster. The three analyses correlate well with one another and it is observed that the most chemically active region locates upstream

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“…Hence, the e ects of transport on the chemical modes that will be discussed in the following sections are to be intended as both resolved and sub-grid parts. More details regarding the analysis can be found in the journal paper published by Li et al [29].…”

Section: Csp/tsr Analysis Of Jet-in-hot-coflow Burnersmentioning

confidence: 99%