DEFINITION:

Computational methods for propulsion consist in the development, validation, and use of software tools for the numerical simulation of physical phenomen taking place in propulsion devices, such as turbine engines, jet engines, rocket motors (liquid and solid propellants), missiles, ramjets, launchers. The numerical codes must provide capabilities for treating multi-physics situations implying multi-species, multi-phases, turbulent, chemically reacting flows with heat transfers from convective and radiative processes and strong fluid-structure couplings. This necessitates the knowledge of applied mathematics, numerical methods, computer sciences and physical modellings. Physical models and the codes where they are made available have to be validated and calibrated by comparison with experimental data. In particular physical, thermodynamic and chemical properties are of major importance, as well as input data for the models used in numerical simulations and may require dedicated experiments to be acquired. Unsteady flows are of major concern as instabilities, transient flows and noise generation are often critical aspects of propulsion devices. Emissions (pollutants, noise, radiation, …) are often to be controlled and must receive special attention. Computations often include complex, hostile conditions and stiff mechanisms which require high computational power, robustness and efficiency. Grid tailoring and grid adaptation is often mandatory, as well as parallel computing and code coupling. The computer codes are run along the following steps: After the grid generation (or adaptation), the solver are run and data are eventually exchanged between solvers before post-processing and analysis of the results. Numerical simulations are used for understanding physics of complex situations for performance prediction and for flow control or system design studies.

(Source: ACARE Domain 313)

SUBDOMAINS:

1. Physical modelling (turbulent, heat transfer, reactive flows, two-phase flows, radiative medium…)
2. Unsteady flows, vortex flows, aeroacoustics
3. Development of numerical schemes and algorithms
4. Code coupling, multi-physics, multi-scale simulations
5. Development and production of software
6. Validation of software, model characterisation
7. Grid generation and adaptation
8. High Performance computing (vector and parallel processing)
9. Complex applications, system analysis, control