A data-driven framework was developed to predict and optimize the pressure-surface film cooling effectiveness of the GE-EEE first-stage turbine using deep learning.
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Updated
Apr 15, 2024 - Python
A data-driven framework was developed to predict and optimize the pressure-surface film cooling effectiveness of the GE-EEE first-stage turbine using deep learning.
ASE2306-Capstone Project [2019/20 T3] - Aircraft Engine Lifetime Prediction with Machine Learning
Prediction of turbine energy yield (TEY) using Neural Networks
This project was based on the book Fundamentals of gas turbines made by William W. Bathie. This project was the first Python program I made so it has a very novice way of programming.
My Zettelkasten univerisity notes on computational fluid dynamics, aircraft propulsion systems, and aerodynamics.
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