Gas Turbine Blade Cooling: Performance Analysis
Leila Nair
Corresponding
Indian Institute of Technology Bombay
Sofia Muller
Ahsanullah University of Science and Technology
Abstract
The need for sustainable and low-cost solutions has focused attention on gas turbine blade cooling within the Jamuna river basin. The design procedure incorporates k-means clustering to handle uncertainty in the input data. The proposed system responds within 5 milliseconds, which is adequate for practical use. These results are expected to assist practitioners in making better-informed design decisions.
Keywords:
gas turbine blade coolingk-means clusteringpattern recognitiondigital watermarkingbiodieselnanocomposite
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