Machine learning for Advanced Gas turbine Injection SysTems to Enhance combustoR performance

The project is funded under Marie Skłodowska-Curie Actions as an Innovative Training Network (ITN).

Air transport is expected to continue to grow in the coming decades. Clean combustion technology for aircraft engines is a key factor in reducing the impact of this growth on ecosystems and human health. The vision for European aviation is shaped by the goals of the Advisory Council for Aviation Research and Innovation in Europe in the Flight Path 2050, which defines strict regulations on pollutant emissions.

To meet these targets, major engine manufacturers are developing lean premixed combustors that operate at very high pressure. This development poses a major risk to the reliability and service life of engines: pressure fluctuations in the combustion chamber, known as thermoacoustics.

The aviation industry is currently experiencing the fourth industrial revolution: cyber-physical systems analyze and monitor technical systems and make automated decisions. This industrial revolution is referred to as "Industry 4.0" in Germany and the "Industrial Internet" in the USA. A key driver of the fourth industrial revolution is machine learning.

The ITN MAGISTER will use Machine Learning to predict and understand thermoacoustics in aircraft engine combustion chambers and lead combustion research towards a revolutionary new approach in this field.