This conference paper considers how to use reaction path diagrams to better understand the output of reacting flow simulations. Briefly, these diagrams have long been used to depict the reactants and products in networks of chemical reactions. The diagrams can be generated in several ways from computer simulations of chemically reacting fluids to depict how the fluid moderates the chemistry by determining which species are brought into contact to react in quantity. The concept of a conditional diagram is introduced which depicts the reactions occurring in only a portion of the fluid domain, thus enabling comparisons between different regions of the fluid and the overall reaction network. Several examples are provided of the paths occurring in methane diffusion flames.

In this paper we study the behavior of a premixed turbulent methane flame in three dimensions using numerical simulation. The simulations are performed using an adaptive time-dependent low Mach number combustion algorithm based on a second-order projection formulation that conserves both species mass and total enthalpy. The species and enthalpy equations are treated using an operator-split approach that incorporates stiff integration techniques for modeling detailed chemical kinetics. The methodology also incorporates a mixture model for differential diffusion. For the simulations presented here, methane chemistry and transport are modeled using the DRM-19 (19-species, 84-reaction) mechanism derived from the GRIMech-1.2 mechanism along with its associated thermodynamics and transport databases. We consider a lean flame with equivalence ratio 0.8 for two different levels of turbulent intensity. For each case we examine the basic structure of the flame including turbulent flame speed and flame surface area. The results indicate that flame wrinkling is the dominant factor leading to the increased turbulent flame speed. Joint probability distributions are computed to establish a correlation between heat release and curvature. We also investigate the effect of turbulent flame interaction on the flame chemistry. We identify specific flame intermediates that are sensitive to turbulence and explore various correlations between these species and local flame curvature. We identify different mechanisms by which turbulence modulates the chemisry of the flame.

In this paper we discuss the application of a new diagnostic tool for analysis of flame simulations. This methodologogy is based on following specific chemical elements, e.g., carbon or nitrogen, as they move through the system. From this perspective an "atom" is a component of a molecule that is being transported through the simulation domain by advection and diffusion. Reactions cause the atom to shift from one species to another with the subsequent transport of the atom determined by the movement of the new species.

Many turbulent premixed flames of practical interest are statistically stationary. They occur in combustors that have anchoring mechanisms to prevent blow-off and flashback. The stabilization devices often introduce a level of geometric complexity that is prohibitive for detailed computational studies of turbulent flame dynamics. As a result, typical detailed simulations are performed in simplified model configurations such as decaying isotropic turbulence or inflowing turbulence. In these configurations, the turbulence seen by the flame either decays or, in the latter case, increases as the flame accelerates toward the turbulent inflow. This limits the duration of the eddy evolutions experienced by the flame at a given level of turbulent intensity, so that statistically valid observations cannot be made. In this paper, we apply a feedback control to computationally stabilize an otherwise unstable turbulent premixed flame in two dimensions. For the simulations, we specify turbulent inflow conditions and dynamically adjust the integrated fueling rate to control the mean location of the flame in the domain. We outline the numerical procedure, and illustrate the behavior of the control algorithm. We use the simulations to study the propagation and the local chemical variability of turbulent flame chemistry.