Linear eddy modeling of reactant conversion and selectivity in turbulent flows

Frankel, Steven; McMurtry, Patrick; Givi, Peyman

doi:10.1002/aic.690410208

Cited by 15 publications

(17 citation statements)

References 29 publications

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“…However, the majority of these studies only considered larger, micron-sized particles. In a recent work, Wu and Menon (2001) studied the evolution of nanoscale particles in the near field of an engine exhaust plume using a moment method (Frenklach & Harris, 1987) in conjunction with a linear eddy method (LEM) (Kerstein, 1989(Kerstein, , 1991(Kerstein, , 1992McMurtry, Menon, & Kerstein, 1993;Frankel, McMurtry, & Givi, 1995). However, the accuracy of the combined moment/LEM methodology was not established via comparison with results obtained experimentally or via direct numerical simulation (DNS).…”

Section: Introductionmentioning

confidence: 99%

Nanoparticle coagulation via a Navier–Stokes/nodal methodology: Evolution of the particle field

Garrick

Lehtinen

Zachariah

2006

Journal of Aerosol Science

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Section: Introductionmentioning

confidence: 99%

Nanoparticle coagulation via a Navier–Stokes/nodal methodology: Evolution of the particle field

Garrick

Lehtinen

Zachariah

2006

Journal of Aerosol Science

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“…This is achieved by formulating the model in one spatial dimension. The reactiondiffusion equation for the species concentration is (Frankel et al, 1995):…”

Section: /17mentioning

confidence: 99%

“…Also, a particular rearrangement mapping must be chosen and Kerstein (1991) has shown the triplet map to capture features for high Reynolds number turbulence. As reviewed by Frankel et al (1995), based on high Reynolds number scaling laws, it can be shown that the following relations must be satisfied (Kerstein, 1991):…”

Section: /17mentioning

confidence: 99%

Les Software for the Design of Low Emission Combustion Systems for Vision 21 Plants

Smith¹,

Cannon²,

Adumitroaie³

et al. 2005

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In this project, an advanced computational software tool was developed for the design of low emission combustion systems required for Vision 21 clean energy plants. Vision 21 combustion systems, such as combustors for gas turbines, combustors for indirect fired cycles, furnaces and sequestrian-ready combustion systems, will require innovative low emission designs and low development costs if Vision 21 goals are to be realized. The simulation tool will greatly reduce the number of experimental tests; this is especially desirable for gas turbine combustor design since the cost of the high pressure testing is extremely costly. In addition, the software will stimulate new ideas, will provide the capability of assessing and adapting low-emission combustors to alternate fuels, and will greatly reduce the development time cycle of combustion systems.The revolutionary combustion simulation software is able to accurately simulate the highly transient nature of gaseous-fueled (e.g. natural gas, low BTU syngas, hydrogen, biogas etc.) turbulent combustion and assess innovative concepts needed for Vision 21 plants. In addition, the software is capable of analyzing liquid-fueled combustion systems since that capability was developed under a concurrent Air Force Small Business Innovative Research (SBIR) program. The complex physics of the reacting flow field are captured using 3D Large Eddy Simulation (LES) methods, in which large scale transient motion is resolved by time-accurate numerics, while the small scale motion is modeled using advanced subgrid turbulence and chemistry closures. In this way, LES combustion simulations can model many physical aspects that, until now, were impossible to predict with 3D steady-state Reynolds Averaged Navier-Stokes (RANS) analysis, i.e. very low NO x emissions, combustion instability (coupling of unsteady heat and acoustics), lean blowout, flashback, autoignition, etc. LES methods are becoming more and more practical by linking together tens to hundreds of PCs and performing parallel computations with fine grids (millions of cells). Such simulations, performed in a few weeks or less, provide a very cost-effective complement to experimental testing. In 5 years, these same calculations can be performed in 24 hours or less due to the expected increase of computing power and improved numerical techniques.This project was a four-year program. During the first year, the project included the development and implementation of improved chemistry (reduced GRI mechanism), subgrid turbulence (localized dynamic), and subgrid combustion-turbulence interaction (Linear Eddy) models into the CFD-ACE+ code. University expertise (Georgia Tech and University of California, Berkeley) was utilized to help develop and implement these advanced submodels into the unstructured, parallel CFD flow solver, CFD-ACE+. Efficient numerical algorithms that rely on in situ look-up tables or artificial neural networks were implemented for chemistry calculations. In the second year, the combustion LES software was ev...

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“…2 shows results of stand-alone HiPS simulations of an isothermal series-parallel reaction scheme with two parallel competitive reactions and four species: A + B → R, A + R → P . 1, the governing equations for the investigated series-parallel reaction scheme are shown, whereby the Damköhler number Da = τ /τ reaction stands for the ratio of the prevailing turbulent time scale to the prevailing chemical time scale as in [6]. A selectivity S can be formulated based on the ratio between mass fraction of species P and the sum of the mass fractions of species R and P: S = 2Y P /(Y R + 2Y P ) [6].…”

Section: Introduction and Hips Modelmentioning

confidence: 99%

“…A selectivity S can be formulated based on the ratio between mass fraction of species P and the sum of the mass fractions of species R and P: S = 2Y P /(Y R + 2Y P ) [6]. For a fixed value of Da 2 , the selectivity is not significantly affected by a change of the value of Da 1 as in [6]. 1, the governing equations for the investigated series-parallel reaction scheme are shown, whereby the Damköhler number Da = τ /τ reaction stands for the ratio of the prevailing turbulent time scale to the prevailing chemical time scale as in [6].…”

Section: Introduction and Hips Modelmentioning

confidence: 99%

Hierarchical Parcel‐Swapping: An efficient mixing model for turbulent reactive flows

Starick

Schmidt

2019

Proc Appl Math and Mech

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Hierarchical Parcel-Swapping (HiPS) developed by A.R. Kerstein [J. Stat. Phys. 153, 142-161 (2013)] is a computationally efficient and novel model for the effects of turbulence on time-evolving, diffusive scalar fields. The characteristic feature of HiPS is the interpretation of the one-dimensional flow domain or a state space as a binary tree structure. Every tree level corresponds to a specific length and time scale, which is based on a turbulence inertial range scaling. The state variables reside at the base of the tree and are interpreted as fluid parcels. The effects of turbulent advection are represented by stochastic swaps of sub-trees at rates determined by turbulent time scales associated with the sub-trees. The mixing of adjacent fluid parcels is done at rates consistent with the prevailing diffusion time scales. In this work, we investigate the influence of turbulent time scale variations on an isothermal series-parallel reaction scheme. The production of a desired chemical species is evaluated by means of a defined selectivity and is strongly affected by the underlying mixing time scales.

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Linear eddy modeling of reactant conversion and selectivity in turbulent flows

Cited by 15 publications

References 29 publications

Nanoparticle coagulation via a Navier–Stokes/nodal methodology: Evolution of the particle field

Nanoparticle coagulation via a Navier–Stokes/nodal methodology: Evolution of the particle field

Les Software for the Design of Low Emission Combustion Systems for Vision 21 Plants

Hierarchical Parcel‐Swapping: An efficient mixing model for turbulent reactive flows

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