Toward the large-eddy simulation of compressible turbulent flows

Erlebacher, Gordon; Hussaini, M. Y.; Speziale, Charles G.; Zang, Thomas A.

doi:10.1017/s0022112092001678

Cited by 659 publications

(310 citation statements)

References 28 publications

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“…(10) (for the application of the Favre filter to the compressible Navier-Stokes equations see Garnier et al, 2009and Erlebacher et al, 1990, we obtain…”

Section: Les Formulationmentioning

confidence: 99%

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

2016

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Abstract.A new fluid-dynamic model is developed to numerically simulate the non-equilibrium dynamics of polydisperse gas-particle mixtures forming volcanic plumes. Starting from the three-dimensional N-phase Eulerian transport equations for a mixture of gases and solid dispersed particles, we adopt an asymptotic expansion strategy to derive a compressible version of the first-order non-equilibrium model, valid for low-concentration regimes (particle volume fraction less than 10 −3 ) and particle Stokes number (St -i.e., the ratio between relaxation time and flow characteristic time) not exceeding about 0.2. The new model, which is called ASHEE (ASH Equilibrium Eulerian), is significantly faster than the N-phase Eulerian model while retaining the capability to describe gas-particle non-equilibrium effects. Direct Numerical Simulation accurately reproduces the dynamics of isotropic, compressible turbulence in subsonic regimes. For gas-particle mixtures, it describes the main features of density fluctuations and the preferential concentration and clustering of particles by turbulence, thus verifying the model reliability and suitability for the numerical simulation of highReynolds number and high-temperature regimes in the presence of a dispersed phase. On the other hand, Large-Eddy Numerical Simulations of forced plumes are able to reproduce the averaged and instantaneous flow properties. In particular, the self-similar Gaussian radial profile and the development of large-scale coherent structures are reproduced, including the rate of turbulent mixing and entrainment of atmospheric air. Application to the Large-Eddy Simulation of the injection of the eruptive mixture in a stratified atmosphere describes some of the important features of turbulent volcanic plumes, including air entrainment, buoyancy reversal and maximum plume height. For very fine particles (St → 0, when non-equilibrium effects are negligible) the model reduces to the so-called dusty-gas model. However, coarse particles partially decouple from the gas phase within eddies (thus modifying the turbulent structure) and preferentially concentrate at the eddy periphery, eventually being lost from the plume margins due to the concurrent effect of gravity. By these mechanisms, gas-particle non-equilibrium processes are able to influence the large-scale behavior of volcanic plumes.

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“…(10) (for the application of the Favre filter to the compressible Navier-Stokes equations see Garnier et al, 2009and Erlebacher et al, 1990, we obtain…”

Section: Les Formulationmentioning

confidence: 99%

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

2016

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“…According to Erlebacher et al [14], τ kk can be neglected in flows where turbulent Mach number, M t = √ 3 urms a , is less than 0.4. The dynamic procedures have been developed to evaluate the parameters used in the subgrid models using the information provided by the resolved scales.…”

Section: Appendix a Subgrid Modelmentioning

confidence: 99%

LES of temporally evolving mixing layers by an eighth‐order filter scheme

Hadjadj

Yee

Sjögreen

2012

Numerical Methods in Fluids

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An eighth-order filter method for a wide range of compressible flow speeds (H.C. Yee and B. Sjogreen, Proceedings of ICOSAHOM09, June 22-26, 2009, Trondheim, Norway) are employed for large eddy simulations (LES) of temporally evolving mixing layers (TML) for different convective Mach numbers (M c ) and Reynolds numbers. The high order filter method is designed for accurate and efficient simulations of shock-free compressible turbulence, turbulence with shocklets and turbulence with strong shocks with minimum tuning of scheme parameters. The value of M c considered is for the TML range from the quasi-incompressible regime to the highly compressible supersonic regime. The three main characteristics of compressible TML (the self similarity property, compressibility effects and the presence of large-scale structure with shocklets for high M c ) are considered for the LES study. The LES results using the same scheme parameters for all studied cases agree well with experimental results of , and published direct numerical simulations (DNS) work of Rogers & Moser (1994) and Pantano & Sarkar (2002). Key words: DNS, LES, Homogeneous turbulence, Mixing layer, SWBLI Motivation and ObjectiveFor the last decade there has been an increase in the use of computational fluid dynamics (CFD) in engineering science, not only for fundamental understanding of complex compressible turbulent physics, but also for the development and design of industrial devices. Owing to the recent progress in petascale computing, in tandem with advances in algorithm development for accurate direct numerical simulations (DNS) and large eddy simulations (LES) of shock free compressible turbulence and turbulence with strong shocks, this type of DNS and LES computation has gradually been able to tackle more complex flows physics. Advances in flow visualization tools have paved the way to extracting valuable information from the computed results containing hundreds of terabytes of data. Examples include * This work was performed while the first author was a visiting scholar at the Center for Turbulence Research, Stanford University.

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“…For LES applications, the instantaneous conservation equations are filtered and models are applied to account for the subgrid-scale (SGS) mass, momentum and energy transport processes. The baseline SGS closure is obtained using the mixed dynamic Smagorinsky model by combining the models of Erlebacher et al [64] and Speziale [65] with the dynamic modeling procedure [66][67][68] and the Smagorinsky eddy viscosity model [69]. There are no tuned constants employed anywhere in the closure.…”

Section: Large Eddy Simulationsmentioning

confidence: 99%

Understanding and predicting soot generation in turbulent non-premixed jet flames.

Wang

Kook²,

Doom³

et al. 2010

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This report documents the results of a project funded by DoD's Strategic Environmental Research and Development Program (SERDP) on the science behind development of predictive models for soot emission from gas turbine engines. Measurements of soot formation were performed in laminar flat premixed flames and turbulent non-premixed jet flames at 1 atm pressure and in turbulent liquid spray flames under representative conditions for takeoff in a gas turbine engine. The laminar flames and open jet flames used both ethylene and a prevaporized JP-8 surrogate fuel composed of n-dodecane and m-xylene. The pressurized turbulent jet flame measurements used the JP-8 surrogate fuel and compared its combustion and sooting characteristics to a world-average JP-8 fuel sample. The pressurized jet flame measurements demonstrated that the surrogate was representative of JP-8, with a somewhat higher tendency to soot formation. The premixed flame measurements revealed that flame temperature has a strong impact on the rate of soot nucleation and particle coagulation, but little sensitivity in the overall trends was found with different fuels. An extensive array of non-intrusive optical and laser-based measurements was performed in turbulent non-premixed jet flames established on specially designed piloted burners. Soot concentration data was collected throughout the flames, together with instantaneous images showing the relationship between soot and the OH radical and soot and PAH. A detailed chemical kinetic mechanism for ethylene combustion, including fuel-rich chemistry and benzene formation steps, was compiled, validated, and reduced. The reduced ethylene mechanism was incorporated into a high-fidelity LES code, together with a momentbased soot model and models for thermal radiation, to evaluate the ability of the chemistry and soot models to predict soot formation in the jet diffusion flame. The LES results highlight the importance of including an optically-thick radiation model to accurately predict gas temperatures and thus soot formation rates. When including such a radiation model, the LES model predicts mean soot concentrations within 30% in the ethylene jet flame. 3This page left intentionally blank.

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Toward the large-eddy simulation of compressible turbulent flows

Cited by 659 publications

References 28 publications

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

LES of temporally evolving mixing layers by an eighth‐order filter scheme

Understanding and predicting soot generation in turbulent non-premixed jet flames.

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