SOURCE-LINKED INTELLIGENCE
Optimization of Gas Turbine Cooling Hole Ramp Configuration via Multi-Fidelity AI/ML Model
esigned. 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. Large eddy simulation, Gas turbine cooling hole, Upstream ramp, Machine learning, Pressure sensitive paint
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 209483.28
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T04:21:15.460Z. This is not the publication date.