Joint Scalar versus Joint Velocity-Scalar PDF Simulations of Bluff-Body Stabilized Flames with REDIM

Abstract

Two transported PDF strategies, joint velocity-scalar PDF (JVSPDF) and joint scalar PDF (JSPDF), are investigated for bluff-body stabilized jet-type turbulent diffusion flames with a variable degree of turbulence-chemistry interaction. Chemistry is modeled by means of the novel reaction-diffusion manifold (REDIM) technique. A detailed chemistry mechanism is reduced, including diffusion effects, with N 2 and CO 2 mass fractions as reduced coordinates. The second-moment closure RANS turbulence model and the modified Curl's micro-mixing model are not varied. Radiative heat loss effects are ignored. The results for mean velocity and velocity fluctuations in physical space are very similar for both PDF methods. They agree well with experimental data up to the neck zone. Each of the two PDF approaches implies a different closure for the velocity-scalar correlation. This leads to differences in the radial profiles in physical space of mean scalars and mixture fraction variance, due to different scalar flux modeling. Differences are visible in mean mixture fraction and mean temperature, as well as in mixture fraction variance. In principle, the JVSPDF simulations can be closer to physical reality, as a differential model is implied for the scalar fluxes, whereas the gradient diffusion hypothesis is implied in JSPDF simulations. Yet, in JSPDF simulations, turbulent diffusion can be tuned by means of the turbulent Schmidt number. In the neck zone, where the turbulent flow field results deteriorate, the joint scalar PDF results are in somewhat better agreement with experimental data, for the test cases considered. In composition space, where results are reported as scatter plots, differences between the two PDF strategies are small in the calculations at hand, with a little more local extinction in the joint scalar PDF results.

Transported scalar PDF calculations of a swirling bluff body flame (‘SM1’) with a reaction diffusion manifold

“…In general, agreement with experimental data is quite good, comparable to what was obtained with LES in [20]. As already observed in similar simulations of the non-swirling Sydney bluff-body flames [27,28], the differences in mean density between the three different calculations do not strongly affect the mean flow field. In Figure 7 the mean mixture fraction and mixture fraction rms profiles are shown.…”

“…It is quite remarkable that, whereas the mean velocity results are similar for the three calculations, the mean mixture fraction results differ quite strongly, especially at x/D = 1.5. Such differences are not observed when using the standard value Sc T = 0.7 (not shown), and neither were they observed in the non-swirling bluff-body flame calculations [27,28] where a standard constant value for Sc T was used. In these cases, the REDIM calculations do not correctly reproduce the mixing between pure air and hot products in the recirculation zone (no 'mixing line') and mainly lead to a burning solution similar to a single diffusion flamelet.…”

“…All calculations are steady axisymmetric and are performed with the same code PDFD [32], which has already successfully been applied to non-swirling Sydney bluff-body burner cases [27,28]. In transported PDF calculations, the equations are solved using a consistent hybrid finite-volume/particle method [32].…”

“…We adopt the Reaction Diffusion Manifold (REDIM) [26] approach, as it has already been used for calculations of non-swirling bluff-body flames [27,28]. In the latter, the combination of REDIM with EMST mixing model [29] led to reasonable results, but scatter in Y CO 2 space was clearly under-estimated.…”

Turbulent scalar fluxes from a generalized Langevin model: Implications on mean scalar mixing and tracer particle dispersion

“…The computer program PDFD originally developed at TU Delft is used, where the implemented hybrid Finite-Volume / particle method has already been applied to different singlephase and two-phase turbulent non-reacting and reacting flows [35][36][37][38][39][40][41] . The second-order accuracy of the method, the use of iteration averages in order to reduce statistical errors in the evaluation of expected values, and the reduction of bias error in this consistent hybrid method are detailed in Naud et al 22 .…”