Micromixing effects in a reacting plume by the Stochastic Fields method

Garmory, Andrew; Richardson, E.S.; Mastorakos, Epaminondas

doi:10.1016/j.atmosenv.2005.11.002

Cited by 42 publications

(32 citation statements)

References 24 publications

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“…The Stochastic Fields method has to date been used to model combustion (Sabel'nikov and Soulard, 2005a;Mustata et al, 2006). We have previously used the method to simulate a NO x /O 3 reacting plume in laboratory conditions (Garmory et al, 2006) and found excellent agreement with experimental data for mean and rms values. The method was also extended to the simulation of a jet engine exhaust plume in Garmory et al (2008).…”

Section: The Stochastic Fields Methodsmentioning

confidence: 60%

“…This is characterised by the Damköhler number, Da, defined as the ratio of mixing timescale to chemical timescale Da = T phys /T chem . For further discussion of this see Garmory et al (2006). The above comments apply equally to RANS and LES calculations, the difference being that in the latter case the sub-grid segregation is expected to be smaller, but still not negligible in principle.…”

Section: Introductionmentioning

confidence: 99%

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Simulations of the dispersion of reactive pollutants in a street canyon, considering different chemical mechanisms and micromixing

Garmory

Kim

Britter

et al. 2009

Atmospheric Environment

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Section: The Stochastic Fields Methodsmentioning

confidence: 60%

Section: Introductionmentioning

confidence: 99%

Simulations of the dispersion of reactive pollutants in a street canyon, considering different chemical mechanisms and micromixing

Garmory

Kim

Britter

et al. 2009

Atmospheric Environment

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“…For temperature and gas phase concentration the turbulent mixing timescale is made equal to the turbulent velocity timescale in line with previous studies using the IEM model (Jones and Kakhi, 1998;Garmory et al, 2006 one is to assume that the mixing timescale is the same as for temperature and gas phase concentration, the second is to neglect any micromixing effect on the particles. By doing the latter the timescale T eddy for M 0 , M 1 and M 2 is made effectively infinite and the micromixing term is dropped for these three.…”

Section: Methodsmentioning

confidence: 96%

“…(25) we ensure that it is independent of ∆W f k and that the Ito integral is obtained correctly (Gardiner, 2004). A limit is placed on the maximum size of the Wiener step to prevent unbounded scalars; this technique has been employed in previous work (Garmory et al, 2006 where it produced stable accurate solutions.…”

Section: Methodsmentioning

confidence: 99%

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Aerosol nucleation and growth in a turbulent jet using the Stochastic Fields method

Garmory

Mastorakos

2008

Chemical Engineering Science

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The Stochastic Fields transported PDF method for turbulent reacting flows has been used to model the nucleation and growth of Dibutyl Phthalate particles in a hot, turbulent jet in a colder background for which experimental data is available.The aerosol population is modelled using an assumed log-normal size distribution.It has been found that neglecting the effect of turbulent fluctuations leads to the peak particle concentration being predicted too close to the jet and the concentration downstream underpredicted. However, this effect was small compared to that of adjusting modelled surface tension. Only by adjusting this was it possible to reproduce correctly the downstream evolution of particle number found in experiment.Particle mass mean diameter was significantly underpredicted at the centre of the jet, which may be due to the inability of log-normal size distribution to capture the distribution in detail. Taking account of turbulent fluctuations leads to increased mean particle size at the edge of the plume. The extent of this increase is strongly dependent on the choice of micromixing timescale.

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Eulerian (Field) Monte Carlo Methods for Solving PDF Transport Equations in Turbulent Reacting Flows

Sabelnikov

Soulard

2010

Handbook of Combustion

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This chapter reviews some recent progress made in the field of Eulerian (field) Monte Carlo (EMC) methods, used for solving probability density function (PDF) transport equations in turbulent reacting flows. The framework of this review includes both Reynolds‐averaged Navier–Stokes (RANS) and large eddy simulation (LES) approaches, and both composition and velocity–composition PDFs. Instead of stochastic particles, as in Lagrangian Monte Carlo (LMC) methods, stochastic Eulerian fields are used to represent the PDF in EMC methods. These fields evolve according to stochastic partial differential equations (SPDEs), stochastically equivalent to the PDF equation. These SPDEs are derived from Lagrangian stochastic ordinary differential equations (SODEs), in the same way as in classical hydrodynamics one transforms the Navier–Stokes equations written in Lagrangian variables into Eulerian coordinates. Boundary conditions for the stochastic fields are discussed. From a numerical point of view, recent publications give evidence that EMC methods converge more rapidly than LMC methods. Further, EMC methods offer an additional advantage over LMC methods: they allow typical Eulerian transport solvers to be employed, thus facilitating the coupling in hybrid EMC–RANS or EMC–LES algorithms. The novel hybrid EMC–RANS is developed and then applied to a premixed methane–air flame stabilized by a backward‐facing step. Other examples of recent applications are reviewed, including the simulation of the auto‐ignition of a hydrogen jet issuing into a co‐flow of vitiated hot air with a scalar EMC–LES method and the simulation of an NO plume in the atmosphere with a scalar EMC–RANS method. Finally, potential future developments and areas of EMC methods are highlighted.

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Micromixing effects in a reacting plume by the Stochastic Fields method

Cited by 42 publications

References 24 publications

Simulations of the dispersion of reactive pollutants in a street canyon, considering different chemical mechanisms and micromixing

Simulations of the dispersion of reactive pollutants in a street canyon, considering different chemical mechanisms and micromixing

Aerosol nucleation and growth in a turbulent jet using the Stochastic Fields method

Eulerian (Field) Monte Carlo Methods for Solving PDF Transport Equations in Turbulent Reacting Flows

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