Meteoroid Ablation Models

metablate provides meteoroid ablation and atmospheric-entry models, MSIS atmospheres, material presets, and plasma-density calculations.

Install

Install the latest published release:

pip install metablate

The bleeding-edge version is available with:

pip install git+https://github.com/danielk333/ablate.git

or trough cloning this repo.

Minimal ablation example

Run the Kero–Szasz (2008) model with a cometary meteoroid and the default AtmPymsis atmosphere:

import numpy as np
from spacecoords import frames

import metablate.material as mat
import metablate.models.kero_szasz_2008 as ks

lat, lon = 67.0, 20.0
position = frames.geodetic_wgs84_to_ecef(lat, lon, 100e3, degrees=True)
direction = frames.azel_to_ecef(lat, lon, az=10, el=-45, degrees=True)

model = ks.KeroSzasz2008(
    options=ks.KeroSzaszOptions(
        material=mat.cometary,
        atmosphere_kwargs=dict(as_dataset=False),
    ),
)
result = model.run(
    parameters=ks.KeroSzaszInitialState(
        epoch=np.datetime64("2018-06-28T12:45:33"),
        position_ecef=position,
        velocity_ecef=direction * 60e3,
        mass=1e-6,
    ),
)
print(f"Runtime: {result.runtime:.3f} s")

Positions and velocities use ECEF coordinates in metres and metres per second; mass is in kilograms. Results include time, mass, velocity, temperature and position.

Atmospheres and computation

AtmPymsis calls the Fortran extensions supplied by pymsis, with MSIS 2.1 by default. ODE models use atmosphere.total_density(...), which returns a NumPy array of total mass density in kg/m^3. density(...) also provides species data and temperature; e.g. sputtering calculation uses this full output. Historical solar and geomagnetic indices are downloaded when needed and cached within their three-hour interval. Custom atmospheres can override total_density for speed; its default implementation extracts "Total" from density.

AtmMSISE00 is optional and requires the separate msise00 package and a Fortran compiler; see its installation instructions.

Some functions use Numba to speed up subsequent calls. The first call compiles the kernels, which are cached for subsequent runs. Set NUMBA_DISABLE_JIT=1 to run the same formulas in Python for debugging.

Examples

See docs/examples for e.g. ablation, fireball, alpha–beta and plasma examples. For example, after a repository checkout, generate an ablation sweep with:

python docs/examples/ablation_sweep.py --output ablation_sweep.png

Which produces this plot:

Development

From a repository checkout:

pip install -e .[tests]
# or pip install -e .[develop] for all dev packages
pytest