FAST Regressions

A FAST capability with applications beyond aircraft sizing.

Overview

FAST utilizes historical data driven regressions to make predicitions about aircraft parameters before and during the sizing process. The regressions used in FAST can also be called independently of aircraft sizing for anyone interested in analysis! The regression package is located in the github repository, and will be included when forking.

The regression package can be used to explore relationships between aircraft parameters, make predictions about new designs, or to learn about probabilistic regressions. Additionally, the package can be used with custom datasets as well, assuming they are organized the same way as the FAST database. The IDEAS Lab recommends checking out the documentation in the regression package or referring to the videos on YouTube for easy use!

Example regression output generated using FAST
Example regression output generated using FAST. This regression predicts fuselage length as a function of payload weight (which is used in the visualization package). It is the simplest of the regression package’s capabilities, predicting an output based on a single input.

For a detailed explanation on the Gaussian Process Regressions used in this package, refer to our recent study:

  • Provisional Citation: Arnson, M. and Aljaber, R. and Cinar, G., “Predicting Conceptual Aircraft Design Parameters Using Gaussian Process Regressions on Historical Data},” in press, AIAA SciTech Forum, 2025.

Accessing the FAST Database

All of the data used in the FAST regressions is available for free on the FAST Github, in the database package. The database is stored in three formats. The first is a large .xlsx workbook, with four different sheets. Each sheet stores information on: turbofan aircraft, turboprop aircraft, turbofan engines, or turboprop engines. The second format is two condensed .xlxs workbooks which can easily be imported into a statistical analysis tool such as JMP. The third format is a .mat file, which can be loaded into MATLAB. After loading, six variables will be present in the workspace: TurbofanAC, TurbopropAC, TurbofanEngines, TurbopropEngines, FanUnitsReference, and PropUnitsReference. These variables store the same information as the .xlxs formats, but in a set of nested structures. The UnitReference variables are identical to any specific aircraft in the AC variables, but store units instead of numerical values. Engine units are stored in Specs » Propulsion » Engine.

Websitescreenshot
Database files in the Database Package of the FAST Github repository. EAP_Databases_Offline.xlsx houses the entire database, as does IDEAS_DB.mat, while the database is split between turbofan and turboprop aircraft in the JMPInputSheet files (intented to be imported into statisitcal analysis software).

Get Started with FAST

FAST is open-source and freely available under an Apache 2.0 license. To start using FAST, visit the GitHub repository here. The repository contains detailed documentation, including a comprehensive user guide to help you get started with the software.

If you use FAST in your research or projects, please cite our work as follows:

FAST Video Tutorials Explore our comprehensive video tutorials to get the most out of the Future Aircraft Sizing Tool (FAST). Hosted by the IDEAS Lab researchers, these tutorials cover everything from installation to advanced features. Visit our YouTube channel for all videos.

Stay tuned for more tutorials and updates.

Watch the Playlist

Visit our YouTube channel for more tutorials.

Sign up for the FAST newsletter To stay informed about upcoming papers, new releases, and news about FAST, sign up for our newsletter here:

Funding and Acknowledgment: This work is sponsored by the NASA Aeronautics Research Mission Directorate and the Electrified Powertrain Flight Demonstration (EPFD) project, “Development of a Parametrically Driven Electrified Aircraft Design and Optimization Tool”. The IDEAS Lab would like to thank Ralph Jansen, Andrew Meade, Karin Bozak, Amy Chicatelli, Noah Listgarten, Dennis Rohn, and Gaudy Bezos-O’Connor from the NASA EPFD project for supporting this work and providing valuable technical input and feedback throughout the duration of the project.

Glenn Engineering and Research Support Contract (GEARS) Contract No. 80GRC020D0003

Maxfield Arnson
Maxfield Arnson
PhD Student and Graduate Research Assistant

Maxfield Arnson is a graduate student research assistant in the IDEAS Lab at the University of Michigan.

Rawan Aljaber
Rawan Aljaber
Undergraduate Research Assistant

Rawan is an undergraduate senior studying Aerospace Engineering at the University of Michigan. Rawan is working at the IDEAS Lab over the summer (2023) through the SURE (Summer Undergraduate Research in Engineering) program.

Paul Mokotoff
Paul Mokotoff
PhD Student and Graduate Research Assistant

Paul Mokotoff is a graduate student research assistant in the IDEAS Lab at the University of Michigan.

Gökçin Çınar
Gökçin Çınar
Assistant Professor of Aerospace Engineering