Evaluation of the Uniform Conditional State Method for Turbulence-Chemistry Interaction Modelling of Swirl-Stabilized Flames

2021 ◽  
Author(s):  
Stefanie De Graaf ◽  
Ludovic De Guillebon ◽  
Marco Konle ◽  
W. Kendal Bushe
Author(s):  
Stefanie De Graaf ◽  
Ludovic de Guillebon ◽  
Marco Konle ◽  
W. Kendal Bushe

Abstract This paper considers a variation on Conditional Moment Closure (CMC) modelling for turbulence-chemistry interaction called the Uniform Conditional State (UCS) model and its application to the prediction of swirl-stabilized flames. UCS is essentially a zero-spatial dimensional, multi-condition CMC method. Unlike conventional CMC methods, for flames that are in (statistically) steady flows, the chemistry can be solved a priori in conditional space only. The reactive scalars are then mapped into real space by taking the inner product of the resulting conditional averages with the joint probability density function of the conditioning variables, here taken to have a presumed form that is a function of the mean and variance of the conditioning variables. Two conditioning variables are used, mixture fraction and progress variable. The combination of these allows for the resulting chemistry table to be applicable to both premixed and non-premixed combustion but also in the partially-premixed regime. In doing so, this new approach is promising to be highly suitable for simulating industrial applications and complex geometries. Another promising aspect is the universal applicability to different fuels and kinetic mechanisms providing great flexibility to the user of this method. Ultimately it is intended to aid the development of industrial burners by providing detailed information about the local composition and emission production, while keeping computational costs significantly low. Not only does this provide additional insight into global emissions and fuel consumption of a new design, but it allows for variability between different stages of mixedness as well as the testing of, for example, alternative fuels in established burner configurations. In this present study a comparison of different fuels and initial conditions is being conducted to analyze their effect on the resulting UCS solution — meaning the chemical source-terms, composition and thermodynamic state in conditional space. Furthermore the use of the UCS solutions as a predictive method in a RANS simulation is being presented here. The paper illustrates the UCS predictions and compares them to experimental data, as well as previously published simulation results of more established modelling approaches. The experimental test case chosen is a model combustor with a swirl-stabilized flame and high technical relevance which demonstrates the applicability of the UCS method to industrial designs for aero engines. Further investigations have begun including the application of this new tool to a real industrial combustor within the framework of this collaboration with MTU Aero Engines AG.


2021 ◽  
Author(s):  
Stefanie De Graaf ◽  
Sonia R. Taylor ◽  
Ludovic de Guillebon ◽  
Marco Konle ◽  
W. K. Bushe

1985 ◽  
Vol 17 (2-3) ◽  
pp. 303-311
Author(s):  
Kees de Korte ◽  
Peter Smits

The usual method for OC measurement is the non-steady state method (reaeration) in tapwater or, sometimes, in activated sludge. Both methods are more or less difficult and expensive. The steady state method with activated sludge is presented. Fundamentals are discussed. For complete mixed aeration tanks, plug flow systems with diffused air aeration and carousels the method is described more in detail and the results of measurements are presented. The results of the steady state measurements of the diffused air system are compared with those of the reaeration method in tapwater. The accuracy of the measurements in the 3 systems is discussed. Measurements in other aeration systems are described briefly. It is concluded that the steady state OC measurement offers advantages in comparison with the non-steady state method and is useful for most purposes.


AIP Advances ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 035304
Author(s):  
You Shan ◽  
Guojun Zhou ◽  
Kairen Chen ◽  
Changchun Zhao ◽  
Kun Shen ◽  
...  

2021 ◽  
Vol 154 (1) ◽  
pp. 014110
Author(s):  
Pablo Ramos ◽  
Michele Pavanello
Keyword(s):  

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