Parametric Turbofan Propulsion Model

During aircraft design, rough models are required to guide the conceptual design phase. Engine performance is particularly hard to predict due to complexity of engines and lack of available information. Our project aims to develop a tool to approximate engine behavior from easily accessible manufacturer data.

Our Team


JP O'Dell

Student researcher

Major: Aerospace Engineering
Hometown: Salinas, California
Interests: Flight Instructing, Wakeboarding, Line Dancing (rip)
Favorite Airplane: F/A-18 Hornet

Joey Hammond

Student researcher

Major: Aerospace Engineering
Hometown: Rota, Spain
Interests: Rock Climbing, Wakeboarding, Piano
Favorite Airplane: C-5 Galaxy


We would like to thank a couple of people for making this project possible:

  • Dr. Paulo Iscold for his persistent technical and personal support during our project
  • Pat LeBeau and Chris Smith from Lockheed Martin for their technical guidance and industry insight
  • Lockheed Martin Skunk Works for sponsoring the project

Project Video

Our Project's Digital Poster

Additional Information

Turbofan Engine Stations
GUI Screenshot
FAIR Algorithm


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