AMR simulation of developing flame surface, as turbulence flowing in from the lower boundary begins to impinge on the initially flat premixed hydrogen flame

Research Objectivex
The goal of this project is to develop a high-fidelity numerical simulation capability for turbulentcombustion processes such as those arising in furnaces and engines. The key issue in modeling turbulent combustion is the interplay between kinetics and the small-scale turbulent eddies in the flow. In practical, engineering combustion settings, the fuel typically consists of hydrocarbons whose chemical behavior is described by a complex reaction mechanism. Our objective is to develop and validate models for turbulent reacting flow that can accurately represent both the chemical and fluid-mechanical behavior of combusting hydrocarbons in a turbulent environment.

Computational Approach
The principal computational tool for this project is the low Mach number adaptive mesh refinement (AMR) algorithm developed by CCSE. This methodology provides an accurate and efficient approach for modeling reacting flows in the regime that is appropriate for engineering applications. The algorithm uses a fractional step discretization that easily facilitates the inclusion of complex kinetics mechanisms. The methodology uses a block-structured refinement approach that allows computational effort to be focused in regimes of the flow where it is required. The structured refinement approach provides a natural coarse-grained parallelism that has demonstrated excellent performance and scalability on distributed memory architectures.

Accomplishments
The focus of our research in the past year was on extending our low Mach number adaptive combustion algorithm to incorporate complex kinetics mechanisms and differential diffusion effects. We used the resulting methodology to address several open questions in combustion science. One area of study concerned the interaction of vortical structures with premixed hydrogen and methane flames. Here we focused the analysis on how the time-dependent flow fields associated with a counter-rotating vortex pair in two dimensions, and isotropic turbulence in three dimensions, modify the structure of the premixed flame. A second area of research focused on quantifying the production of nitrous oxides in a diffusion flame as a function of fuel composition (methane + additives). For both cases, the computations use 30—70 species and several hundred reactions to describe methane chemistry.

Significance
The modeling of turbulent fluid flow, even in the non-reacting case, remains one of the great scientific challenges. We still lack adequate predictive models for non-reacting turbulent flows in realistic engineering geometries. For realistic combustion scenarios, the picture becomes more complex because small-scale turbulent fluctuations modify the physical processes such as kinetics and multiphase behavior. These processes, in turn, couple the small scales back to the larger fluid-dynamical scales as chemical constituents react. As a result of this coupling, we must capture the structure of the subgrid fluctuations to make predictions. The use of average quantities as inputs to physical processes will generate large errors through interaction of these models. Developing techniques that accurately reflect the role of small-scale fluctuations on the overall macroscopic dynamics would represent a major scientific breakthrough.

Publications
M. S. Day and J. B. Bell, "Numerical simulation of laminar reacting flows with complex chemistry," Lawrence Berkeley National Laboratory report LBNL-44682 (1999).

J. B. Bell, N. J. Brown, M. S. Day, M. Frenklach, J. F. Grcar, and S. R. Tonse, "The effect of stoichiometry on vortex flame interactions," Lawrence Berkeley National Laboratory report LBNL-44730 (1999).

J. B. Bell, N. J. Brown, M. S. Day, M. Frenklach, J. F. Grcar, R. M. Propp, and S. R. Tonse, "Scaling and efficiency of PRISM in adaptive simulations of turbulent premixed flames," in Proceedings of the 28th International Combustion Symposium (2000); Lawrence Berkeley National Laboratory report LBNL-44732 (1999).

http://www.seesar.lbl.gov/ccse/