The combination of cutting-edge HPC platforms, pioneering Artificial Intelligence (AI) methodologies, and High-Performance Data Analytics (HPDA) techniques are expanding horizons for aeronautical engine design and optimisation. This integration will facilitate novel investigation approaches and furnish unprecedented levels of accuracy and physical insight.
In the present proposal HPC, AI, and HPDA techniques will be combined for case study focused on the design of aeronautical low-pressure turbines in the framework of joint research project between Avio Aero Spa (AVIO), Morfo Design Srl (MORFO) and the University of Genoa (UNIGE). The analysis will be based on complex CFD simulations and entails CPU-intensive and time-consuming computations.
The main goal will be to leverage on the possibilities offered by state-of-the-art computing systems and to establish an efficient management system for numerical results to move to a higher level of accuracy current design standards and tools, while relevantly reducing time-to-design.
The present proposal directly supports the ongoing European project ACROSS (HPC BIG DATA ARTIFICIAL INTELLIGENCE CROSS STACK PLATFORM TOWARDS EXASCALE, https://www.acrossproject.eu/), which is framed in the collaborative research EUROHPC programme. More exactly, the current project will be focused on a wide and detailed applications of high-fidelity calculations (i.e. Large Eddy Simulation, LES) to map loss, and loss mechanism over the whole design space of interest of the future aeronautical engine.