Chemical kinetic uncertainty quantification for Large Eddy Simulation of turbulent nonpremixed combustion

2013 ◽  
Vol 34 (1) ◽  
pp. 1299-1306 ◽  
Author(s):  
Michael E. Mueller ◽  
Gianluca Iaccarino ◽  
Heinz Pitsch
Keyword(s):  
Large Eddy Simulation ◽  
Uncertainty Quantification ◽  
Chemical Kinetic ◽  
Nonpremixed Combustion ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Turbulent Nonpremixed

Simulating Flame Lift-Off Characteristics of Diesel and Biodiesel Fuels Using Detailed Chemical-Kinetic Mechanisms and Large Eddy Simulation Turbulence Model

2012 ◽  
Vol 134 (3) ◽  
Author(s):  
Sibendu Som ◽  
Douglas E. Longman ◽  
Zhaoyu Luo ◽  
Max Plomer ◽  
Tianfeng Lu ◽  
...  
Keyword(s):  
Large Eddy Simulation ◽  
Turbulence Model ◽  
Turbulence Models ◽  
Chemical Kinetic ◽  
Spray Combustion ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Kinetic Mechanisms ◽  
Lift Off ◽  
Biodiesel Fuels

Combustion in direct-injection diesel engines occurs in a lifted, turbulent diffusion flame mode. Numerous studies indicate that the combustion and emissions in such engines are strongly influenced by the lifted flame characteristics, which are in turn determined by fuel and air mixing in the upstream region of the lifted flame, and consequently by the liquid breakup and spray development processes. From a numerical standpoint, these spray combustion processes depend heavily on the choice of underlying spray, combustion, and turbulence models. The present numerical study investigates the influence of different chemical kinetic mechanisms for diesel and biodiesel fuels, as well as Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) turbulence models on predicting flame lift-off lengths (LOLs) and ignition delays. Specifically, two chemical kinetic mechanisms for n-heptane (NHPT) and three for biodiesel surrogates are investigated. In addition, the renormalization group (RNG) k-ε (RANS) model is compared to the Smagorinsky based LES turbulence model. Using adaptive grid resolution, minimum grid sizes of 250 μm and 125 μm were obtained for the RANS and LES cases, respectively. Validations of these models were performed against experimental data from Sandia National Laboratories in a constant volume combustion chamber. Ignition delay and flame lift-off validations were performed at different ambient temperature conditions. The LES model predicts lower ignition delays and qualitatively better flame structures compared to the RNG k-ε model. The use of realistic chemistry and a ternary surrogate mixture, which consists of methyl decanoate, methyl nine-decenoate, and NHPT, results in better predicted LOLs and ignition delays. For diesel fuel though, only marginal improvements are observed by using larger size mechanisms. However, these improved predictions come at a significant increase in computational cost.

scholarly journals Large-eddy simulation of transcritical liquid oxygen/methane jet flames

2019 ◽  
Author(s):  
H. Müller ◽  
M. Pfitzner
Keyword(s):  
Computational Cost ◽  
Liquid Oxygen ◽  
Test Case ◽  
Rocket Engines ◽  
Flamelet Model ◽  
Nonpremixed Combustion ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Flow Features ◽  
Turbulent Nonpremixed

A numerical method to perform large-eddy simulations (LES) of nonpremixed liquid oxygen/methane (LOx/CH4) combustion at supercritical pressures is presented and the computational results are compared with available experimental data. The injection conditions of the considered test case resemble those in typical liquid-propellant rocket engines (LRE). Thermodynamic nonidealities are modeled using the Peng–Robinson (PR) equation of state (EoS) in conjunction with a novel volume-translation method to correct deficiencies in the transcritical regime. The resulting formulation is more accurate than the standard cubic EoS's without deteriorating their good computational efficiency. The real-gas thermodynamics model is coupled with the steady laminar flamelet model (SLFM) for turbulent nonpremixed combustion to incorporate chemical reactions at reasonable computational cost in the LES. A reduced reaction mechanism, which is validated with respect to the full mechanism, is used to generate a flamelet library. A comparison of the LES result with available OH* measurements shows that important flow features are well predicted.

Large eddy simulation of a turbulent nonpremixed piloted methane jet flame (Sandia Flame D)

2005 ◽  
Vol 30 (1) ◽  
pp. 549-556 ◽  
Author(s):  
M.R.H. Sheikhi ◽  
T.G. Drozda ◽  
P. Givi ◽  
F.A. Jaberi ◽  
S.B. Pope
Keyword(s):  
Large Eddy Simulation ◽  
Jet Flame ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Turbulent Nonpremixed

scholarly journals Large Eddy Simulation on the Effects of Pressure on Syngas/Air Turbulent Nonpremixed Jet Flames

2019 ◽  
Vol 192 (10) ◽  
pp. 1963-1996 ◽  
Author(s):  
Pietro P. Ciottoli ◽  
Bok Jik Lee ◽  
Pasquale E. Lapenna ◽  
Riccardo Malpica Galassi ◽  
Francisco E. Hernández-Pérez ◽  
...  
Keyword(s):  
Large Eddy Simulation ◽  
Jet Flames ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Turbulent Nonpremixed

Uncertainty Quantification: A Stochastic Method for Heat Transfer Prediction Using LES

2012 ◽  
Author(s):  
M. Carnevale ◽  
F. Montomoli ◽  
A. D’Ammaro ◽  
S. Salvadori
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Large Eddy Simulation ◽  
Uncertainty Quantification ◽  
Epistemic Uncertainty ◽  
Stochastic Approach ◽  
Operating Conditions ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Turbulence Closures

In Computational Fluid Dynamics (CFD) is possible to identify namely two uncertainties: epistemic, related to the turbulence model, and aleatoric, representing the random-unknown conditions such as the boundary values and or geometrical variations. In the field of epistemic uncertainty, Large Eddy Simulation (LES and DES) is the state of the art in terms of turbulence closures to predict the heat transfer in internal channels. The problem concerning the stochastic variations and how to include these effects in the LES studies is still open. In this paper, for the first time in literature, a stochastic approach is proposed to include these variations in LES. By using a classical Uncertainty Quantification approach, the Probabilistic Collocation Method is coupled to Numerical Large Eddy Simulation (NLES) in a duct with pin fins. The Reynolds number has been chosen as a stochastic variable with a normal distribution. It is representative of the uncertainties associated to the operating conditions, i.e. velocity and density, and geometrical variations such as the pin fin diameter. This work shows that by assuming a Gaussian distribution for the value of Reynolds number of +/−25%, is possible to define the probability to achieve a specified heat loading under stochastic conditions, which can affect the component life by more than 100%. The same method, applied to a steady RANS, generates a different level of uncertainty. This procedure proves that the uncertainties related to the unknown conditions, aleatoric, and those related to the physical model, epistemic, are strongly interconnected. This result has directed consequences in the Uncertainty Quantification science and not only in the gas turbine world.

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