Objective
Gas turbines play several important roles in Europe, contributing to various sectors of the economy. According to the Polaris Market report, the global gas turbine market was valued at 22.25 billion USD in 2021 and is expected to grow at a CAGR of 6.3% till 2030. At this huge global market size, since fossil fuels are burned in gas turbines, they release greenhouse gases, including CO2. Based on the 2030 EU Climate Target Plan, sets Europe on a responsible path to becoming climate neutral by 2050, greenhouse gas emissions should be cut by at least 55% by 2030. Hydrogen gas turbines offer several advantages over fossil fuels, making them an attractive option for clean and sustainable energy generation (zero emissions), helping to face climate change, and reducing air pollution. However, hydrogen burns at a higher temperature compared to other fuels, which poses challenges for turbine blade cooling and requires an efficient cooling technique to maintain blade integrity. Film cooling, by injecting cold air at discrete locations over the exposed surfaces through holes and slots, is one of the available technologies. Additive structures, such as ramps, near the exit of the cooling hole geometry can be used to improve the film-cooling effectiveness, thus increasing the gas turbine efficiency. The geometrical configuration of the upstream ramp can significantly affect the cooling effectiveness on the surface and the mixing between coolant and mainstream. Therefore, the ramp configuration should be carefully designed. In this project, this goal will be achieved through a multidisciplinary optimization approach, based on the combination of experiments and high-fidelity Large Eddy Simulations, making use of Artificial Intelligence and Machine Learning approaches. The outcome of the project will be an optimization tool and an optimized ramp to be applied on the cooling hole and expected to result in better thermal efficiency in the gas turbines and lower fuel consumption.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencesmathematicspure mathematicsgeometry
- engineering and technologyenvironmental engineeringenergy and fuels
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
24129 Bergamo
Italy