OPPDIF: A Fortran program for computing opposed-flow diffusion flames

Lutz, Andrew E.; Kee, Robert J.; Grcar, Joseph F.; Rupley, F.M.

doi:10.2172/568983

Cited by 407 publications

(228 citation statements)

References 1 publication

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“…(11), using the same computer code LFLAM, developed at Ciemat. The fuel and In physical space, we solve the continuity, momentum, species and temperature equations as described in [43,44] for the planar geometry, here written in their unsteady form (in this formulation F = ρu and G = −ρv/y with u the axial and v the normal velocity components and y the perpendicular direction):…”

Section: Numerical Resolution Of 1d Flameletsmentioning

confidence: 99%

RANS modelling of a lifted H2/N2 flame using an unsteady flamelet progress variable approach with presumed PDF

Naud

Novella

Pastor

et al. 2015

Combustion and Flame

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Elsevier Naud, B.; Novella Rosa, R.; Pastor Enguídanos, JM.; Winklinger, JF. (2015). RANS modelling of a lifted H2/N2 flame using an unsteady flamelet progress variable approach with presumed PDF. Combustion and Flame. 162 (4) AbstractAn unsteady flamelet / progress variable (UFPV) approach is used to model a lifted H 2 /N 2 flame in a RANS framework together with presumed PDF. We solve the unsteady flamelets both in physical space and in mixture fraction space. We show that in the former case, the scalar dissipation rate profile strongly varies in time (while it is assumed to be fixed in time in the latter). However, this does not result in significant qualitative differences in the corresponding flamelet libraries. The progress variable is carefully defined, including both the main combustion product (H 2 O) and a key radical species in ignition process (HO 2 ). The presumed-PDF model is proposed in terms of the non-normalised progress variable, without assuming its statistical independence with mixture fraction. We introduce a modelled transport equation for the mean progress variable which is consistent with the basic underlying UFPV assumption, derived from the Lagrangian flamelet model. The influence of different model parameters on the results for the mean temperature and mean species mass fractions and their fluctuations is discussed. Good results are obtained for the conditions of the considered lifted flame where detailed experimental data is available. However, at low coflow temperature the modelled flame lift-off height is shorter than expected.

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Section: Numerical Resolution Of 1d Flameletsmentioning

confidence: 99%

RANS modelling of a lifted H2/N2 flame using an unsteady flamelet progress variable approach with presumed PDF

Naud

Novella

Pastor

et al. 2015

Combustion and Flame

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“…1 (left column). Because of the small size of the nozzles, their close placement relative to one another, and the parabolic outflow velocity boundary condition, the strained diffusion flame considered here, strictly speaking, cannot be accurately described by the commonly used one-dimensional model [29,30]. The flame structure found along the axis of symmetry is shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

Two-dimensional direct numerical simulation of opposed-jet hydrogen/air flames: Transition from a diffusion to an edge flame

Lee

Frouzakis

Boulouchos

2000

Proceedings of the Combustion Institute

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“…Details of the configuration can be found in (Arias et al 2011b;Lecoustre et al 2013). A steady-state solution for an opposed-flow steady laminar diffusion flame (Lutz et al 1996) with scalar dissipation rate of χ st = 7s −1 was mapped to the DNS domain based on the mixture fraction Z using the following relationship:…”

Section: Monotonicity Of Moments In Strongly Oxidizing Environmentsmentioning

confidence: 99%

“…The length of the most energetic scale is set to 1 mm, while the Kolmogorov length scale is set to 14 μm. The simulation was initialized with a flamelet obtained from a converged OPPDIF (Lutz et al 1996) solution with no nonrealizable points and a peak soot volume fraction of 0.27 ppm. Figure 6 shows the number of points where the solution is nonrealizable at t = 1ms.…”

Section: Realizability Of the Soot Psdfmentioning

confidence: 99%

Development of High Fidelity Soot Aerosol Dynamics Models using Method of Moments with Interpolative Closure

Roy

Arias

Lecoustre

et al. 2014

Aerosol Science and Technology

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The method of moments with interpolative closure (MOMIC) for soot formation and growth provides a detailed modeling framework maintaining a good balance in generality, accuracy, robustness, and computational efficiency. This study presents several computational issues in the development and implementation of the MOMIC-based soot modeling for direct numerical simulations (DNS). The issues of concern include a wide dynamic range of numbers, choice of normalization, high effective Schmidt number of soot particles, and realizability of the soot particle size distribution function (PSDF). These problems are not unique to DNS, but they are often exacerbated by the high-order numerical schemes used in DNS. Four specific issues are discussed in this article: the treatment of soot diffusion, choice of interpolation scheme for MOMIC, an approach to deal with strongly oxidizing environments, and realizability of the PSDF. General, robust, and stable approaches are sought to address these issues, minimizing the use of ad hoc treatments such as clipping. The solutions proposed and demonstrated here are being applied to generate new physical insight into complex turbulence-chemistry-soot-radiation interactions in turbulent reacting flows using DNS.

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OPPDIF: A Fortran program for computing opposed-flow diffusion flames

Cited by 407 publications

References 1 publication

RANS modelling of a lifted H2/N2 flame using an unsteady flamelet progress variable approach with presumed PDF

RANS modelling of a lifted H2/N2 flame using an unsteady flamelet progress variable approach with presumed PDF

Two-dimensional direct numerical simulation of opposed-jet hydrogen/air flames: Transition from a diffusion to an edge flame

Development of High Fidelity Soot Aerosol Dynamics Models using Method of Moments with Interpolative Closure

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