pyglenn — Worked Examples (Jupyter Notebooks)

📖 Documentation: profleao.github.io/pyglenn-notebooks

A collection of eleven elaborated, self-contained Jupyter notebooks demonstrating the pyglenn thermochemical properties calculator. pyglenn reconstructs the standard-state molar properties $C_p^\circ(T)$, $H^\circ(T)$ and $S^\circ(T)$ from NASA (Glenn) polynomial coefficients stored in a bundled SQLite database (~2030 species, 3772 temperature intervals).

The topics follow the applications outlined in the package's ideias.md (Dr. Reginaldo G. Leão Jr., GESESC / IFMG): combustion, biofuels, thermodynamic cycles, chemical equilibrium and CFD/kinetics property provision.

Requirements

# pip
pip install pyglenn
pip install numpy pandas matplotlib scipy   # used for plots, tables and solvers

# conda / mamba
conda install -c conda-forge pyglenn numpy pandas matplotlib scipy

Every notebook opens with the same short preamble that connects to the bundled database and defines a robust species_id(calc, name) helper for exact-name lookups.

The notebooks

#	Notebook	What it covers
01	Getting Started	Connecting, searching species, computing $C_p$/$H$/$S$, interpreting the returned values, error handling
02	NASA Polynomials Under the Hood	The 9-term polynomial math; reproducing the API from raw coefficients; piecewise intervals; meaning of $b_1, b_2$
03	Temperature-Dependent Properties & Plotting	$C_p(T)$, $S(T)$, $H(T)$ curves; equipartition and vibrational excitation; property tables with pandas
04	Enthalpy of Formation from NASA Polynomials	Recovering $\Delta_f H^\circ$ from the standardized enthalpy; validation against literature
05	Reaction Enthalpies & Heats of Combustion	$\Delta H_\mathrm{rxn}(T)$, LHV/HHV, Kirchhoff's law, Hess's law
06	Adiabatic Flame Temperature	Energy-balance solve for $T_\mathrm{ad}$; equivalence ratio, preheat, fuel comparison
07	Comparing Fuels & Biofuels	Ethanol / methanol / gasoline / jet-fuel: energy density, air-fuel ratio, CO₂ intensity (a GESESC use case)
08	Chemical Equilibrium & Gibbs Free Energy	$G^\circ = H^\circ - TS^\circ$; $K(T)$; water-gas shift; van't Hoff; high-T dissociation
09	Brayton Gas-Turbine Cycle	Air-standard Brayton with real $C_p(T)$; isentropic states via entropy; efficiency vs pressure ratio
10	Property Provider for CFD & Chemical Kinetics	Batch tables, a cached coefficient provider, a benchmark, and an ODE integration
11	Comparing Thermodynamic Data Sources	NASA polynomials vs NIST vs conventional tables for H₂O(g); side-by-side Cp/S/H comparison, benchmark and discrepancy analysis

A note on the data

• pyglenn's h_relative (calculate_properties(...)['h_relative']) is the standardized molar enthalpy on the NASA scale — it already includes the enthalpy of formation. Consequently reference-state elements read $H^\circ(298.15,\mathrm{K}) \approx 0$, compounds read their $\Delta_f H^\circ$, and reaction enthalpies are simple stoichiometric sums.
• In the bundled database the dedicated heat_of_formation_298K column is not populated, so calculate_formation_enthalpy() returns None. Notebook 04 shows how to obtain $\Delta_f H^\circ$ from h_relative at 298.15 K instead.

Reproducing

The notebooks are committed with their outputs already executed. To re-run:

jupyter nbconvert --to notebook --execute --inplace notebooks/en/*.ipynb

Citing

If you use this repository in your research or teaching, please cite it via Zenodo:

Gonçalves Leão Junior, R. (2026). pyglenn-notebooks. Zenodo. https://doi.org/10.5281/zenodo.21324685

BibTeX:

@software{goncalves_leao_junior_2026_21324685,
  author       = {Gonçalves Leão Junior, Reginaldo},
  title        = {pyglenn-notebooks},
  month        = jul,
  year         = 2026,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.21324685},
  url          = {https://doi.org/10.5281/zenodo.21324685},
}