Check out the Aviary documentation here.
This repository is an OpenMDAO-based aircraft modeling tool that incorporates aircraft sizing and weight equations from its predecessors GASP (General Aviation Synthesis Program) and FLOPS (Flight Optimization System). It also incorporates aerodynamic calculations from GASP and FLOPS and has the capability to use an aerodynamics deck as well as an aircraft engine deck. There are two options for the mission analysis portion of this code, a 2 degrees-of-freedom (2DOF) approach, and a height energy (HtEn) approach. The user can select which type of mission analysis to use, as well as whether to use the FLOPS-based code or the GASP-based code for the weight, sizing, and aerodynamic relations.
The simplest installation method for development is an "editable mode" install with pip in your terminal:
pip install -e .
This installs the package in the current environment such that changes to the Python code don't require re-installation.This command should be performed while in the folder containing setup.py.
The Aviary documentation is located here.
Otherwise you can build the docs locally:
- Install jupyter-book using instructions located here
- Go to Aviary/aviary/docs
- Run the command
sh build_book.shfrom your command prompt of choice - Navigate to the built html:
/Aviary/aviary/docs/\_build/html/intro.html
To visualize XDSMs and successfully pass spec tests, all the XDSM files must be run. This can be done using the run_all.py utility script within the aviary/xdsm directory. This is a necessary step before unit testing, otherwise unit tests will fail.
This code has been validated using output and data from the GASP and FLOPS codes themselves. The GASP-based weight calculations in this code include in their comments which versions of the GASP standalone weights module were used in validation. The aero and EOM subsystem validations were based on runs of the entire GASP and FLOPS code as they stood in the summer of 2021 and the summer of 2022 respectively.
The repository installation can be tested using the command testflo . at the top-level Aviary folder. Assuming you have both SNOPT and IPOPT installed, the output should look something like this:
OK
Passed: 706
Failed: 0
Skipped: 3
Ran 709 tests using 16 processes
Wall clock time: 00:00:16.97
In addition to all of the quicker tests, we include multiple integration tests within Aviary.
These have also been known as "benchmarks".
Due to their length, these tests are not run when using the above command.
Instead, you can use the run_all_benchmarks.py file in the Aviary/aviary folder, which is just a light wrapper around the testflo call.
This will run all of the longer tests in parallel using all of your available CPU cores.
Information on the versions of the packages required for Aviary can be found in the most recent GitHub Actions runs.
We have also provided a static version of the environment.yml at the top level of the Aviary repo.
Aviary is in active development. We plan to expand its capabilities and add features as detailed in this doc page.