The integration of high-fidelity simulations in Multi-Disciplinary Optimisation (MDO) is a necessary evolution of the design process in order to meet short, medium and long-terms industrial objectives in terms of:
❖ Competitiveness: by reducing development time and cost but also the cost of manufacture;
❖ Environment: by designing more efficient engine and aircraft configurations with better multidisciplinary compromises and fostering the integration of greener technologies earlier in the design phase.
The adjoint method is a key enabling technology for efficient gradient-based optimisation with a large number of design variables. It can also contribute, outside of the optimisation loop, to identify crucial areas in a design which have the largest impact on performance. In this way, the adjoint approach enables the designer to focus on the most critical area for design optimisation, significantly shortening the design process. At the same time, the presence of excessively large sensitivities in candidate designs can be reduced, leading to more robust designs with smaller real-life performance degradations.
Within MADELEINE, rather than employing cheaper low-fidelity methodologies that have very limited potential to deliver enhanced designs, the consortium deployed efficiently the MDO optimisation process on next-generation HPC infrastructure in order to:
❖ design configuration with improved performance benefiting exploiting multidisciplinary trade-offs
❖ drastically reduce simulation times and make them compatible with industrial product development cycles.
In this context, MADELEINE achieved two particular goals:
❖ reduced the barriers to set-up an efficient MDO process by developing re-usable modules and standardising the interfaces between the disciplines;
❖ reduced the simulation run-time by exploiting heterogeneous HPC architectures through optimised libraries and efficient job orchestration.
