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Proceedings Papers

Application of Machine Learning Based Surrogate Model for Prediction of Sectional Temperature of Radially Cooled Gas Turbine Blades

Rishabh Shrivastava, Nisha Tamar, Amit Grover, Debdulal Das
Proc. ASME. GTINDIA2021, ASME 2021 Gas Turbine India Conference, V001T02A003, December 2–3, 2021
Paper No: GTINDIA2021-76053
DOI: https://doi.org/10.1115/GTINDIA2021-76053
... Abstract Accurate thermal prediction of gas turbine blades is essential to ensure successful operation throughout the design life. Large Gas turbines operate in different conditions based on customer requirements, due to which turbine blades are subjected to variations in thermal loading...
View Paper titled, Application of Machine Learning Based Surrogate Model for Prediction of Sectional Temperature of Radially Cooled Gas <span class="search-highlight">Turbine</span> <span class="search-highlight">Blades</span>
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Topics: Blades, Finite element analysis, Gas turbines, Machine learning, Temperature, Turbine blades