Multifidelity Aeromechanical Design Framework for High Flow Speed Multistage Axial Compressors

The development of novel engine architectures is vital in achieving the aviation sector’s net-zero carbon emission target by 2050. With today’s digital decade providing support for an accelerated technology maturation, the challenge for turbomachinery design remains to significantly push the limits of current performance within an ambitious development lead time. In this context, it is essential to adopt a design framework where the predictive models or simulations employed target a sufficiently reliable performance assessment. These models must be tailored to the dynamics of an evolving industrial design process and therefore continuously balance required design flexibility, robust evaluation, appropriate fidelity (i.e., the level of detail and accuracy they provide), and resulting evaluation time. This article discusses a framework for designing axial compressors and its application to the aeromechanical optimization of a high-speed compressor rotor. The design environment integrates geometry parametrization, a modular evaluation with different levels of fidelity for the aerodynamic and structural models, and surrogate-based optimization (SBO) capabilities. It is shown how the combination of a modular sequencing of the different models and the acceleration enabled by high-performance computing (HPC) and machine learning allows for a more advanced preliminary design. A significant gain in isentropic efficiency is attained while satisfying all structural constraints. At the same time, it is demonstrated that the framework is compatible with the characteristics of the preliminary design phase: both in its ability to adapt to cycle and design changes as well as regarding the turnaround time of the optimization itself.