High Fidelity Simulations of High-Pressure Turbines Cascades for Data-Driven Model Development

Gas turbines (GT) are, and will continue to be, the backbone of aircraft propulsion, as well as power generation and mechanical drive. A small GT performance improvement is expected to have a fuel-spend advantage of the billion-dollar order, together with a significant CO2 emission benefit. Part of the possible performance improvements can be enabled by continuously advancing the understanding of the GT flow physics and thus further reducing the inaccuracy of current design tools based on computational fluid dynamics (CFD). By exploiting the capability of our high-fidelity CFD solver on leadership GPU-accelerated supercomputers, we have been able to perform state-of-the-art high fidelity simulations of turbomachinery flows. The generated data, therefore, can shed light on the detailed fundamental flow physics, in particularly the behavior of transitional and turbulent boundary layers affected by large-scale violent freestream turbulence, under strong pressure gradient and curvature. Furthermore, machine learning methods are applied to the high-fidelity data to develop low order models readily applicable to GT designs.