Airbreathing Engine Combustors. Part 2: Modeling and Numerical Simulation

The main aims of this article are to show how numerical simulation can meet the major challenges of designing an aeronautical combustion chamber (hereinafter referred to as CCA) and to provide key information to guide the choices of numerical engineers, both in terms of models and methods.

In order for this article to stand on its own, it should be noted here that aircraft combustion chambers have to meet numerous performance and safety requirements, but are also central to the challenge of reducing the environmental footprint of air transport. To keep pace with technological developments, digital simulation is playing an increasingly important role and can draw on ever more powerful computing infrastructure, as well as continuous advances in software engineering and physical modeling. While the characterization of systems from an experimental point of view remains essential for direct access to the physical mechanisms at play, numerical simulation provides access to all the variables of interest to engineers (pressure, speed, temperature, mass fractions of different species, etc.) as well as the entire volume of the calculation domain (including areas of space that would be difficult or impossible to access using a probe or laser).

In order to ensure that the result obtained is that of a simulation and not a simulacrum (a result that could be considered a numerical aberration, disconnected from any physical reality), it is essential to have reliable models for the various phenomena involved (turbulence, chemical reactions, kerosene atomization, etc.), which must be combined with appropriate numerical and practical calculation methods. Controlling the cost of simulations is also a key issue in order to be able to address the complex issues associated with aircraft combustion chambers. We will see that, very often, the most general models for describing the various physical phenomena involved are too costly to be used in practice and that it is necessary to replace them (or supplement them) with simplified approaches based on stronger assumptions.