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Thermodynamic cycle modeling library, built on top of OpenMDAO

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pyCycle


This is a thermodynamic cycle modeling library, designed primarily to model jet engine performance. It is built on top of the OpenMDAO framework and the design is heavily inspired by NASA's NPSS software. You need to be at least familiar with either OpenMDAO or NPSS in order to be successful in using this library.

Disclosure: The docs are nearly non-existent. We're hoping to improve this, but for the moment this is what you get. We suggest you look in the examples folder for some indications of how to run this code. Also, you can read the paper on pyCycle which goes into a lot of detail that is very relevant.

OpenMDAO Version Compatibility


pyCycle is built on top of OpenMDAO, and thus depends on it. Here is the OpenMDAO version you need for the specific versions of pyCycle

pyCycle version OpenMDAO version
3.0.0 2.8.0 thru 3.1.1
3.2.0 3.2.0 thru 3.5.0
3.4.0 3.3.0 thru 3.5.0
3.5.0 3.5.0 thru 3.7.0
4.0.0 3.7.0 or greater
4.1.x 3.10.0 or greater
4.2.0 3.10.0 or greater

Version 4.2 --- PyPI release

No significant code changes, but minor adjustments to the package name in setup.py to enable publishing to PyPI.

Citation

If you use pyCycle, please cite this paper:

E. S. Hendricks and J. S. Gray, “Pycycle: a tool for efficient optimization of gas turbine engine cycles,” Aerospace, vol. 6, iss. 87, 2019.

@article{Hendricks2019,
author="Eric S. Hendricks and Justin S. Gray" ,
title = "pyCycle: A Tool for Efficient Optimization of Gas Turbine Engine Cycles",
journal = "Aerospace",
year = "2019",
day = "8",
month = "August",
volume = {6},
number = {87},
doi = {10.3390/aerospace6080087},
}

Installation

PyPI

If you want to install from PyPI then do the following:

pip install om-pycycle

or, if you want to install the (optional) additional testing tools

pip install 'om-pycycle[all]'

Why is it om-pycycle on PyPI? Because another package already claimed pyCycle! Note that the import does not change though. You still use import pycycle regardless.

Clone

clone this repo, and checkout the specific version you want to run:

git clone https://github.com/OpenMDAO/pyCycle
cd pyCycle

You can see a list of all versions in the repo via:

git tag

Select one of those tags (e.g. 3.0.0)

git checkout 3.0.0

or for pyCycle V3.2.0:

git checkout 3.2.0

or for pyCycle V4.0.0:

git checkout 4.0.0

Use pip to install:

pip install -e .

Testing

After installation if you wat to run the unit test suite you can do so via the testflo command:

testflo pycycle

This will run all the unit tests within the pycycle repository, but note that it will NOT run the longer regression tests from the example_cycles folder. If you want to run the regression tests, then you need to clone the repository, CD into the example_cycles folder and call

testflo .

Version 4.0 Announcements

Version 4.0 officially supports multiple thermodynamic packages. Currently there are two: CEA (the original thermo solver) and the new TABULAR option. Although these are the only two current thermo packages, the code has been setup so that it is expandable to more later.

The tabular thermodynamic is much simpler to use, and much faster to run. The downside is that it is tied to a specific pre-computed thermodynamic data set that is valid for a specific fuel type, and within a specific temperature range. We have included an example script that shows how to generate your own tabular data set, which you would need to do for anything other than Jet-A fuel. Additionally the default tabular thermo data only support fuel (no water injection). If you want to use tabular thermo for a water injection case, you'll need to generate a new thermo data table.

Different thermos will give different answers!

Please note that when you switch thermodynamics packages, you will get slightly different answers. Depending on how finely you sample your thermo data for the tabular package, the differences could be small to modest. If you see changes greater than 1% on any critical values then you should consider refining your thermodynamic data tables.

V4 is modestly backwards incompatible

In order to modular thermodynamic happens, some modest changes to the API were needed.

  • The Cycle, introduced in V3.5.0, is now mandatory. You must build your cycle in this, instead of a basic OpenMDAO Group.
  • The pyc_add_element method has been deprecated (to be removed in version 4.1). Improvements to the cycle class made it possible to stick with standard add_subsystem calls instead.
  • The arguments needed to be passed into Elements during instantiation have been changed (and for the most part significantly simplified). The biggest change is that you no longer need to pass element lists to each Element any more. All of the thermodynamic arguments have now been moved up to the Cycle group.
  • There is a new Element class which must be the base class (or at least an ancestor class) for any component that contain flow-ports (anything you would point to in a call to connect_flow is an element). This new base class has one additional method, pyc_setup_output_ports that is required for initialization of the fluid port data. If you have developed any of your own custom Elements beyond the standard library, then note that you'll need to update them and define the new method in them.

Over all the, changes are pretty minor, but their impact is significant. The changes to the Element initialization not only make models simpler, they also make them thermo-agnostic.

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Thermodynamic cycle modeling library, built on top of OpenMDAO

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