Including analytically reduced chemistry (ARC) in CFD applications

Abstract

Reacting numerical simulations today are often based on either fitted global reaction schemes, comprised of a few empirical reactions, or pre-tabulated laminar flame solutions computed with detailed chemistry. Although both methods can accurately predict global quantities such as laminar flame speed and burnt gas composition, they have significant limitations. In particular, neither are able to directly and adequately describe the complexity of pollutant chemistry. In the context of reducing harmful emissions of the next generation of aeronautical combustors, however, including these needed additional kinetic details in combustion simulations is becoming essential. Direct integration of detailed chemistry in accurate turbulent combustion models is not a viable option in the foreseeable future, because of excessive computational demands and numerical stiffness. In this context, Analytically Reduced Chemistry (ARC) represents an attractive compromise between accuracy and efficiency, and is already employed in relatively complex Direct Numerical Simulations (DNS) and Large Eddy Simulations (LES). ARCs are knowledge-based compact mechanisms retaining only the most relevant kinetic information as extracted directly, and without fitting, from detailed chemical models using specialized reduction techniques (important species identification through graph search, lumping of species with similar features, short-living species identification, etc.). In recent years, several multi-step efficient and automated reduction tools have been developed, enabling the easy generation of ARCs with minimum input and knowledge from the user. The main objective of this paper is to present a review of ARCs for fuels ranging from methane to aviation kerosene surrogates, recently derived with such a multi-step automated reduction tool: YARC. Information about the applicability and range of validity of each derived mechanism are given, along with further references. Each one was specifically derived to be convenient to use in CFD; in particular, the stiffness was regarded as a key factor and the final number of transported species never exceeds thirty. In a final section, the great potential of the methodology is illustrated in a multi-phase, reactive LES application where the fuel is a real multi-component transportation fuel. To that end, an ARC based on a Jet A described by the novel Hybrid Chemistry (HyChem) approach is coupled with the Dynamically Thickened Flame LES (DTFLES) model and directly integrated into the LES solver AVBP. A Lagrangian spray description is used. Results are compared to experimental data in terms of temperature and major species (CO2, H2O, CO, NO) mass fractions, leading to very satisfying results.