Gas models, combustion and gas turbine solver.

This project uses Transformer-based RNN model to predict the remaining useful life (RUL) of turbo fan jet engines using NASA's C-MAPSS simulated sensor data.

Course notes for ME 3276 Propulsion taught at UConn

• Predicted Remaining Useful Life (RUL) for turbofan jet engines using a Random Forest Classifier Model. • Performed Exploratory Data Analysis on NASA’s Dataset and analyzed feature correlation using Seaborn. • Applied hyperparameter optimization using Randomized Search CV and increased F1-Score to an overall 91.2%.

ImportWP Jet Engine Importer allows you to import into Custom Post Types, Taxonomies and Custom Fields generated with Jet Engine WordPress plugin.

Predicting Jet Engine Failures with NASA’s C-MAPSS Dataset and LSTM: A Practical Guide to Predictive Maintenance

Jet Engine Health Monitoring System using ML for Predictive Maintenance — a university group project.

Summary of work from the DoE's USTR Gas Turbine Industrial Fellowship Program @swri

HackAI 2026 | Unsupervised LSTM Autoencoders for Jet Engine Fault Detection