WARNING: This code contains significant known errors. As development of this fork is suspended for the time being, consider it a starting point/reference for your own work and not a fully operational plugin.

Files updated for OpenMDAO 1.0

• flowstation.py (burn() and functions dealing with reactants still need to be implemented)
• cycle_component.py
• compressor.py
• duct.py
• heat_exchanger.py
• inlet.py
• splitter.py
• start.py
• test/test_compressor.py
• test/test_duct.py
• test/test_flowstation.py (some functions still need to be implemented)
• test/test_heat_exchanger.py
• test/test_inlet.py
• test/test_splitter.py
• test/test_start.py
• test/test_util.py (new in this fork)

Files not ready for OpenMDAO 1.0

• nozzle.py - do all regimes take Tt and Pt from throat conditions?
• test/test_nozzle.py

Changes

OpenMDAO no longer treats variable trees as distinct classes, so flow_station.py has been restructured as a library of stateless functions that calculate thermodynamics values directly from parameters. Passing known parameters to solve() will be sufficient for nearly all applications. FlowStation variable trees must be stored manually by components.

The CycleComponent class has been given new helper functions for initializing, reseting, and solving FlowStation variable trees. The easiest way to use FlowStations is to subclass CycleComponent and use self._add_flowstation() and self._solve_flow_vars(). Variables are stored as params['FLOWSTATION NAME:in:VARIABLE'] and unknowns['FLOWSTATION NAME:out:VARIABLE']. When a variable is set in both params and unknowns, self._solve_flow_vars() uses the value stored in unknowns. Thus, it is important to call self._clear_unknowns() for each FlowStation at the beginning of self.solve_nonlinear(), lest outputs from a previous run interfere with calculations.

The HeatExchanger component no longer includes state variables resid_Qmax and resid_e_balance. Instead, T_cold_out and T_hot_out have been made outputs and are solved by a newton solver within the component's solve_nonlinear() method.

pycyle.api has been renamed pycycle.components to agree with OpenMDAO 1.0 naming convention. pycycle.flowstation is not a component, so it must be imported separately.

This plugin provides basic thermodynamic cycle modeling tools for OpenMDAO. It's main feature is the inclusion of a FlowStation variable that provides access to isentropic flow relationships.

This is an OpenMDAO plugin, so we assume you have already installed a version of OpenMDAO.

On OS-X it is strongly suggested that you setup Python, and other OpenMDAO pre-reqs with homebrew. You can follow these detailed instructions but once you have homebrew installed and setup, here is the short version:

brew install git
brew install python
brew install gfortran
pip install numpy
pip install scipy
brew install freetype
pip install matplotlib

In addition, this plugin requires Cantera and the python wrapper for it. You can compile cantera from scratch, or follow the instructions below for a bit easier route.

Cantera provides pre-compiled binaries that are by far the easiest choice for windows. You should follow their instructions for the best way to install it and make sure it works.

But note that you need to install version 2.0.2 and NOT the 2.1 beta version. Get only the official release version of it!

https://code.google.com/p/cantera/wiki/WindowsInstallation

Assuming you've used homebrew to get OpenMDAO setup, then just use it to install Cantera too!

brew install cantera

You're best bet is to follow the official instructions.

Make sure you're in an activated OpenMDAO environment. Then you have two options:

This will install the plugin, but you won't have access to the source in order to mess around with it.

plugin install --github pycycle

If you want to have access to the source and make changes to it while you're working then you should do an install from source. Don't be scared by the cantera source install though, compared to that this is pretty easy! It's only two steps.

1. Clone the repository to your local machine. If you want to clone ours:

   git clone https://github.com/OpenMDAO-Plugins/pyCycle.git

Or you can fork it and clone that to your local machine. Either way...

2. cd into the pyCycle directory

   python setup.py develop