This is our project of open source computational resources for students of Applied Thermodynamics. Our target audience are students that may not yet know what Python is, so we will present brief introductions and point to some tutorial material on that and other tools that we require.
The content you will see here is curated by members of UFRJ>ATOMS research group, and either developed by ourselves or adapted from cited sources. We are always accepting indirect suggestions as well as direct contributions. We are developing our material in the Python programming language, through the Jupyter notebook interface. If you are not familiar with these tools, Python is a programming language that can work with some useful libraries for numerical methods (numpy), symbolic algebra (sympy) and graphical plots (matplotlib) comparable to Matlab. Jupyter notebook, on the other hand, is a browser based interface for developing Python codes, with intercalating blocks of descriptive documentation and graphical results for easy exposition of the code and underlying ideas in an educational material. Finally, GitHub is the website that provides hosting of open source projects from developers (students, researchers, engineers) from all around the world, including ours.
We have divided our goals in three categories
This is our main goal
We are developing study material for beginners in applied thermodynamics with programming / scientific computing. These materials are suitable for either undergraduate or graduate level courses.
We are basing our project on scientific computing tools with focus on accessibility: We are developing lectures using pure python that can run on python tutor live on any computer with internet access, and lectures using the scipy stack on jupyter notebooks that can run on a variety of operational systems via the anaconda setup or on cloud computing supported by myBinder.
Scipy - “the Open Source Library of Scientific Tools”
jupyter notebooks - “The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text.”
Anaconda - “the leading open data science platform powered by Python, a high performance distribution with access to over 720 packages.””
myBinder - “With Binder, you can opens those notebooks in an executable environment, making your code immediately reproducible by anyone, anywhere. 100% free and open source.””
python tutor live - “Python Tutor, created by Philip Guo, helps people overcome a fundamental barrier to learning programming: understanding what happens as the computer executes each line of a program’s source code.”
we are hostoing the following kind of content in this section
this is our second goal
We intend to publish well documented and open source implementations of topics of interest in thermodynamics for intermediate level students in thermodynamics and in programming / scientific computing, with complete reference to original journal or textbook publications.
We will host a virtual laboratory for analysis, development and testing of models and algorithms.
We are hosting additional open source content not quite accessible from our jupyter notebook files, as c / fortran source code, that can be built using GNU compilers, however specific build instructions depend on the user’s environment, or matlab / mathematica / excel scripts / notebooks / spreadsheets, etc… that are themselves open source, but require a licensed matlab / mathematica / excel installation to run.
This our third goal, this section will feed from the results of our virtual laboratory.
Provide support for the development of research and engineering level packages to fill gaps in the scientific literature of the open source community.
a software incubator to develop research level packages for advanced level graduate students and researchers to fill gaps in the scientific literature of the open source community.
This will span independent projects that will most likely be hosted in independent GitHub repositories, nevertheless still being part of the PyTherm project. Or even additions to existing projects.
Expect usage of performance optimization tools and references to external available packages here rather than reinventions, when applicable.
- Classical thermodynamics fundamentals
- Mass balance, energy balance and the 1st law
- Entropy and the 2nd law
- Chemical reaction
- Combustion engines
- PxH diagrams
- Pure substance L-V saturation curve
- Critical points
- Molecular models
- Volumetric Equations of state
- Excess Gibbs energy models
- Pure solid and solid solution phases properties models
- Phase and reaction equilibria algorithms
- Stability analysis
- Bubble point and dew point calculations
- Flash calculations
We build our computations on top of the SciPy stack – a Python-based ecosystem of open-source software for mathematics, science, and engineering.
We build our content in the jupyter-notebook format, using the anaconda accessible distribution of the SciPy stack, fow windows, osx and linux.
We are able to launch our content in web readable format using jupyter’s nbviewer, GitHub’s gh-pages and compatible Jekyll theme.
We make our content available to the remote executable environments of Python Tutor and myBinder.
We host our whole project on GitHub