Fast compressible flow tables for aerodynamic calculations in Python.

21f6f979
—
James Brind
2 years ago

Incorporate averaging

d81fb2ff
—
James Brind
2 years ago

Change frame functions, tests in submodule, reformat

ebd69123
—
James Brind
2 years ago

Polynomial initial guesses for flow function

- read-only
- https://git.sr.ht/~jb753/compflow
- read/write
- git@git.sr.ht:~jb753/compflow

The compflow library contains functions to convert back and forth between Mach number and other non-dimensional groups in compressible flows. By using a NumPy--Fortran interface, the code is vectorised and lightning-fast, yielding a speed-up of up to two orders of magnitude.

Full documentation is available online.

- Evaluation of ten non-dimensional flow quantities as explicit functions of Mach number;
- Iteration with Newton's method to invert explicit relations and solve for Mach number;
- Creation and caching of lookup tables to speed up inversions;
- Fortran-accelerated, fully-vectorised in both directions.

compflow is available on the Python Package Index, so installation is as simple as,

```
pip install compflow
```

**Note:** as the library uses the NumPy--Fortran interface, you will
need both Numpy and a working Fortran compiler for the installation to complete
successfully.

Optionally, run the tests using `pytest`

to verify the installation,

```
pytest --pyargs compflow
```

We can now start doing some calculations. First, an explicit evaluation of stagnation pressure ratio given a Mach number,

```
>>> import compflow
>>> ga = 1.4
>>> compflow.Po_P_from_Ma(0.3, ga)
1.0644302861529382
```

Second, an inversion of flow function where iterative solution for Mach number is required,

```
>>> compflow.Ma_from_mcpTo_APo(0.8, ga)
0.39659360325173604
```

The names and symbols of non-dimensional quantities are fairly self-explanatory, but a full list is given in the Nomenclature. All functions and the equations used for the calculations are documented in the API.

Numpy arrays are also accepted as inputs,

```
>>> import numpy
>>> Ma1 = numpy.array([0., 0.5, 1., 2.])
>>> compflow.To_T_from_Ma(Ma1, ga)
array([1. , 1.05, 1.2 , 1.8 ])
>>> Ma2 = numpy.array([[0.1, 0.2], [0.3, 0.4], [0.5, 0.6]])
>>> compflow.To_T_from_Ma(Ma2, ga)
array([[1.002, 1.008],
[1.018, 1.032],
[1.05 , 1.072]])
```

When solving for Mach number at a given normalised mass flow, it is assumed
that we are on the subsonic branch of the curve unless a flag is specified.
Where no solution is possible, i.e. if the flow would choke, `NaN`

is
returned,

```
>>> capacity = [0.6, 2.]
>>> compflow.Ma_from_mcpTo_APo(capacity, ga)
array([0.28442265, nan])
>>> compflow.Ma_from_mcpTo_APo(capacity, ga, sup=True)
array([2.27028708, nan])
```

- Sort out packaging so that NumPy gets installed automatically (distutils due to be deprecated?).

James Brind Mar 2022