scholarly journals Large eddy simulation of a lifted ethylene flame using a dynamic nonequilibrium model for subfilter scalar variance and dissipation rate

2013 ◽  
Vol 34 (1) ◽  
pp. 1289-1297 ◽  
Author(s):  
Colleen M. Kaul ◽  
Venkat Raman ◽  
Edward Knudsen ◽  
Edward S. Richardson ◽  
Jacqueline H. Chen
Keyword(s):  
Large Eddy Simulation ◽  
Dissipation Rate ◽  
Nonequilibrium Model ◽  
Ethylene Flame ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Scalar Variance

scholarly journals Modeling scalar dissipation and scalar variance in large eddy simulation: Algebraic and transport equation closures

2012 ◽  
Vol 24 (5) ◽  
pp. 055103 ◽  
Author(s):  
E. Knudsen ◽  
E. S. Richardson ◽  
E. M. Doran ◽  
H. Pitsch ◽  
J. H. Chen
Keyword(s):  
Large Eddy Simulation ◽  
Transport Equation ◽  
Scalar Dissipation ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Scalar Variance

scholarly journals Stochastic backscatter of turbulence energy and scalar variance by random subgrid-scale fluxes

1995 ◽  
Vol 451 (1941) ◽  
pp. 293-318 ◽  
Keyword(s):  
Large Eddy Simulation ◽  
Isotropic Turbulence ◽  
Pressure Fluctuations ◽  
Decay Rates ◽  
Temperature Fields ◽  
Turbulence Energy ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Scalar Variance ◽  
Energy Decay Rates

For large-eddy simulation with a finite-difference scheme, a simple stochastic subgridscale (SGS) model is introduced which describes the effects of random SGS motions on the resolved (filtered) scales of incompressible turbulent motions. The model extends the Smagorinsky-Lilly model by adding realizable random stresses and fluxes which are constructed as quadratic expressions of Gaussian random velocity and temperature fields. The random components reduce the correlations between stresses and strain rates to in between 0.16 and 0.5, in agreement with observations. The random stresses (fluxes) also induce random accelerations (temperature changes) with a k 4 power spectrum. Such random sources backscatter energy (variance) from SGS motions to resolved scale motions when temporally correlated with finite timescales. The timescales are different for momentum and heat flux. The analysis of the model provides an upper estimate of the magnitude of backscatter which is close to previous predictions. The analysis identifies the influence of the quasi-normal assumption and of numerical filters and determines the variance of the pressure fluctuations induced by the random accelerations at grid scales. Backscatter increases the SGS turbulent Prandtl number to a degree depending strongly on the numerical filter. Tests of the model in large-eddy simulation of isotropic turbulence show energy decay rates in close agreement with expected rates when the stochastic SGS model is included. Backscatter cannot be simulated with reduced diffusivities or filter widths.

An Application of LES for Gas Turbine Combustor

2002 ◽  
Author(s):  
Mitsuru Yaga ◽  
Kazutaka Suzuki ◽  
Hajime Endo ◽  
Tsuyoshi Yamamoto ◽  
Hideyuki Aoki ◽  
...  
Keyword(s):  
Large Eddy Simulation ◽  
Gas Turbine ◽  
Dissipation Rate ◽  
Characteristic Time ◽  
Gas Turbine Combustor ◽  
Turbulent Diffusion Flame ◽  
Eddy Simulation ◽  
Air Jet ◽  
Large Eddy ◽  
Combustion Simulation

A three-dimensional turbulence spray combustion simulation in a gas turbine combustor with Large Eddy Simulation is carried out. In this study, we construct a new eddy characteristic time model derived from a large-scale motion to estimate the combustion reaction rate with an eddy dissipation concept (EDC) model, and estimate combustion characteristics (temperature and chemical species distribution) in the gas turbine combustor for the purpose of validating this model. The essence of this model is that eddy characteristic time is estimated by considering Kolmogorov scale at first. From this assumption, eddy dissipation rate is apparent. However it is not solved directly in Large Eddy Simulation. So eddy dissipation rate is estimated by an assumption that turbulence energy generation and dissipation are locally equal (it is the same assumption as Smagorinsky model), and it is substituted in the eddy characteristic time formula. The overall reaction C12H24+18O2 → 12CO2+12H2O, is often used for turbulent combustion simulation for saving calculation time, but cannot consider CO and H2 formation in local fuel-rich region. To solve this problem, we use 3-step global mechanism (C12H24+6O2 → 12CO+12H2, CO+0.5O2 ↔ CO2, H2+0.5O2 ↔ H2O) to calculate turbulent non-premixed flame characteristics coupling with EDC. The calculated CO2 mole fraction distribution is in fairly good agreement with the experimental data. However, the calculated temperature distribution does not agree well with the measured result of temperature because of disturbing heat transport to downstream by dilution air jet. Though few problems are left, it is shown that the combustion simulation using LES with EDC model is effective method to calculate the characteristics of turbulent diffusion flame in furnace such as gas turbine combustor.

scholarly journals Improving Parameterization of Entrainment Rate for Shallow Convection with Aircraft Measurements and Large-Eddy Simulation

2016 ◽  
Vol 73 (2) ◽  
pp. 761-773 ◽  
Author(s):  
Chunsong Lu ◽  
Yangang Liu ◽  
Guang J. Zhang ◽  
Xianghua Wu ◽  
Satoshi Endo ◽  
...  
Keyword(s):  
Large Eddy Simulation ◽  
Vertical Velocity ◽  
Dissipation Rate ◽  
Principal Component ◽  
Entrainment Rate ◽  
Shallow Convection ◽  
Cumulus Clouds ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Multiple Variables

AbstractThis work examines the relationships of entrainment rate to vertical velocity, buoyancy, and turbulent dissipation rate by applying stepwise principal component regression to observational data from shallow cumulus clouds collected during the Routine Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign over the ARM Southern Great Plains (SGP) site near Lamont, Oklahoma. The cumulus clouds during the RACORO campaign simulated using a large-eddy simulation (LES) model are also examined with the same approach. The analysis shows that a combination of multiple variables can better represent entrainment rate in both the observations and LES than any single-variable fitting. Three commonly used parameterizations are also tested on the individual cloud scale. A new parameterization is thus presented that relates entrainment rate to vertical velocity, buoyancy, and dissipation rate; the effects of treating clouds as ensembles and humid shells surrounding cumulus clouds on the new parameterization are discussed. Physical mechanisms underlying the relationships of entrainment rate to vertical velocity, buoyancy, and dissipation rate are also explored.

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