Assessment of Tabulated Premixed Conditional Moment Closure Model Using Direct Numerical Simulation

• Published in: Combustion science and technology 2021-06, Vol.193 (8), p.1293-1312
• Main Authors: Bhide, Kedar G., Sreedhara, S
• Format: Article
• Language: English
• Subjects: Chemistry; Direct numerical simulation; DNS; ignition; Mathematical models; Model accuracy; Nonpremixed flames; premixed; Probability density functions; Simulation; Tabulation; TPCMC; Turbulence intensity
• ISSN: 0010-2202; 1563-521X
• DOI: 10.1080/00102202.2019.1688796

The Conditional Moment Closure (CMC) is a proven methodology to model non-premixed flames, but an emerging technique for analyzing turbulent premixed flames. However, solving a full set of CMC equations is a time-consuming process. The Tabulated Premixed CMC (TPCMC) model is a modification of the premixed CMC model that seeks to reduce the time consumed in solving equations by making the premixed CMC model amenable to the tabulation of chemistry. TPCMC model considers the effect of small scale mixing of reactants and products using the scalar dissipation rate and effect of large scale turbulence on the flame using the beta probability density function. The validation of TPCMC model using Direct Numerical Simulation (DNS) data has been attempted in this paper. DNS of growth of an ignition kernel in a turbulent medium was performed for this purpose. Two sets of simulations, namely 3D DNS with three-step reduced chemistry and 2D DNS with multi-step chemistry, have been carried out in this study using PENCIL code. The Favre averaging of this DNS data was performed on the surfaces of constant radius to assess the accuracy of TPCMC model. The variations in turbulence intensity and integral length scale were considered to generate DNS database. TPCMC model accurately predicted the variation of fuel mass fraction and temperature for all the cases considered in this study and captured the qualitative trends in the CO mass fraction where a negligible deviation from the actual values was observed. The influence of initial parameters related to turbulence considered in this study was negligible on the accuracy of predictions obtained from the model.