Turbofan Engine

Turbofan engine research centers on improving performance, reliability, and predictive maintenance. Current efforts heavily utilize machine learning, particularly deep learning architectures like convolutional and recurrent neural networks (including LSTMs and GRUs), often combined with techniques like physics-informed machine learning or modal decomposition to enhance accuracy and interpretability. These advancements aim to optimize engine efficiency, reduce maintenance costs, and improve safety through more accurate remaining useful life predictions and real-time fault detection, impacting both aviation and broader industrial applications.