Recent progress in simulation methodologies and high-performance parallel computers have made it is possible to perform detailed simulations of multidimensional reacting flow phenomena using comprehensive kinetics mechanisms. As simulations become larger and more complex, it becomes increasingly difficult to extract useful information from the numerical solution, particularly regarding the interactions of the chemical reaction and diffusion processes. In this paper we present a new diagnostic tool for analysis of numerical simulations of reacting flow. Our approach is based on recasting an Eulerian flow solution in a Lagrangian frame. Unlike a conventional Lagrangian view point that follows the evolution of a volume of the fluid, we instead follow specific chemical elements, e.g., carbon, nitrogen, etc., as they move through the system . From this perspective an "atom" is part of some molecule of a species that is transported through the domain by advection and diffusion. Reactions cause the atom to shift from one chemical host species to another and the subsequent transport of the atom is given by the movement of the new species. We represent these processes using a stochastic particle formulation that treats advection deterministically and models diffusion and chemistry as stochastic processes. In this paper, we discuss the numerical issues in detail and demonstrate that an ensemble of stochastic trajectories can accurately capture key features of the continuum solution. The capabilities of this diagnostic are then demonstrated by applications to study the modulation of carbon chemistry during a vortex-flame interaction, and the role of cyano chemistry in rm NO_x production for a steady diffusion flame.

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.

Recent progress in simulation methodologies and new, high-performance parallel architectures have made it is possible to perform detailed simulations of multidimensional combustion phenomena using comprehensive kinetics mechanisms. However, as simulation complexity increases, it becomes increasingly difficult to extract detailed quantitative information about the flame from the numerical solution, particularly regarding the details of chemical processes. In this paper we present a new diagnostic tool for analysis of numerical simulations of combustion phenomena. Our approach is based on recasting an Eulerian flow solution in a Lagrangian frame. Unlike a conventional Lagrangian viewpoint in which we follow the evolution of a volume of the fluid, we instead follow specific chemical elements, e.g., carbon, nitrogen, etc., as they move through the system. From this perspective an "atom" is part of some molecule that is transported through the domain by advection and diffusion. Reactions cause the atom to shift from one species to another with the subsequent transport given by the movement of the new species. We represent these processes using a stochastic particle formulation that treats advection deterministically and models diffusion as a suitable random-walk process. Within this probabilistic framework, reactions can be viewed as a Markov process transforming molecule to molecule with given probabilities. In this paper, we discuss the numerical issues in more detail and demonstrate that an ensemble of stochastic trajectories can accurately capture key features of the continuum solution. We also illustrate how the method can be applied to studying the role of cyanochemistry on NOx production in a diffusion 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.

Using examples from active research areas in combustion and astrophysics, we demonstrate a computationally efficient numerical approach for simulating multiscale low Mach number reacting flows. The method enables simulations that incorporate an unprecedented range of temporal and spatial scales, while at the same time, allows an extremely high degree of reaction fidelity. Sample applications demonstrate the efficiency of the approach with respect to a traditional time-explicit integration method, and the utility of the methodology for studying the interaction of turbulence with terrestrial and astrophysical flame structures.

The theory of turbulent premixed flames is based on a characterization of the flame as a discontinuous surface propagating through the fluid. The displacement speed, defined as the local speed of the flame front normal to itself, relative to the unburned fluid, provides one characterization of the burning velocity. In this paper, we introduce a geometric approach to computing displacement speed and discuss the efficacy of the displacement speed for characterizing a turbulent flame.

We present three-dimensional, time-dependent simulations of the flowfield of a laboratory-scale slot burner. 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 methodology incorporates detailed chemical kinetics and a mixture model for differential species diffusion. Methane chemistry and transport are modeled using the DRM-19 mechanism along with its associated thermodynamics and transport databases. Adaptive mesh refinementdynamically resolves the flame and turbulent structures. Detailedcomparisons with experimental measurements show that the computational results provide a good prediction of the flame height, the shape of the time-averaged parabolic flame surface area, and the global consumption speed (the volume per second of reactants consumed divided by the area of the time-averaged flame). The thickness of the computed flamebrush increases in the streamwise direction, and the flamesurface density profiles display the same general shapes as the experiment. The structure of the simulated flame also matches the experiment; reaction layers are thin (typically thinner than 1 mm) and the wavelengths of large wrinkles are 5--10 mm. Wrinkles amplify to become long fingers of reactants which burn through at a neck region, forming isolated pockets of reactants. Thus both the simulated flame and the experiment are in the "corrugated flamelet regime."