Toolbox for design and prediction of multilayered acoustic treatments. Also contains a material model based on the GRAS database.
- numpy
- scipy
- mpmath
- matplotlib
- pandas
- xlsxwriter
- h5py
pip install numpy scipy mpmath matplotlib pandas xlsxwriter
pip install git+https://github.com/rinaldipp/tmm.git
from tmm.tmm import TMM
# Define the frequency range, resolution and sound incidence
treatment = TMM(fmin=20, fmax=5000, df=1, incidence="diffuse", incidence_angle=[0, 78, 1],
filename="example_perforated_resonator")
# Define the layers - from top to bottom
treatment.perforated_panel_layer(t=19, d=8, s=24, method="barrier")
treatment.porous_layer(model="mac", t=50, sigma=27)
treatment.air_layer(t=50)
# Compute, plot and export data
treatment.compute(rigid_backing=True, show_layers=True)
treatment.plot(plots=["alpha"], save_fig=True)
treatment.save2sheet(n_oct=3)
treatment.save()
bands, filtered_alpha = treatment.filter_alpha(view=True, n_oct=3)
For more examples see the example files.
[1] R. Petrolli, A. Zorzo and P. D'Antonio, " Comparison of measurement and prediction for acoustical treatments designed with Transfer Matrix Models ", in Euronoise, October 2021.
For questions about usage, bugs, licensing and/or contributions contact me at [email protected].