Acoustics Simulation using the Diffusion Equation
Project description
Diffusion Equation Software for Room Acoustics Modeling
acousticDE is an open-source software package developed for the simulation of room acoustics based on the diffusion equation method. The package provides two complementary numerical implementations of this method: the Finite Volume Method (FVM) and the Finite Difference Method (FDM). In addition, it includes a tool for auralization enabling users to listen to acoustic renderings generated from the results of the Finite Volume Method. The main strength of acousticDE is in its ability to predict the distribution of acoustic energy over space and time within a given room. With only a minimal set of input parameters, the software delivers accurate and computationally efficient estimates of both the energy propagation and room acoustics properties. This makes it a valuable tool for researchers and practitioners interested in architectural acoustics. The software is being developed as part of an ongoing research within the Building Acoustics Group at the Department of Built Environment, Eindhoven University of Technology. It is currently under active development and implemented in Python by Ilaria Fichera.
Release version
Version 0.1.0
Repository structure
The package acousticDE is formed by three subfolders:
- Auralization generates the auralization wav file for the room in question;
- FiniteDifferenceMethod computes the room acoustics based on the diffusion equation using the finite difference method (Navarro et al., 2012);
- FiniteVolumeMethod computes the room acoustics based on the diffusion equation using the finite volume method (Munoz, 2019);
Installation
Use pip to install acousticDE
pip install acousticDE
Once installed, in cmd window, use the following commands:
python
import acousticDE
To run FVM, continue with:
from acousticDE.FiniteVolumeMethod.FVM import run_fvm_sim
results = run_fvm_sim('C:\....\mesh.msh','C:\....\mesh_input_fvm.json','C:\....\absorption_coefficients.csv')
To run FDM, continue with:
from acousticDE.FiniteDifferenceMethod.FDM import run_fdm_sim
results = run_fdm_sim('C:\....\mesh_input_fdm.json')
To run Auralization, continue with:
from acousticDE.Auralization.Auralization import run_auralization_sim
results = run_auralization_sim('C:\....\anechoic_file.wav','C:\....\resultsFVM.pkl')
To run the codes/functions, check the documentation depending on the method you want to use, create the files needed for the specific function and check the Tutorial sections of the documentation.
Usage & Documentation
The documentation is created to help to use and develop acousticDE effectively. To use acousticDE, please refer to the Tutorial section of the documentation. In addition, the documentation gives an introduction of the package for both FDM and FVM.
Authors
Software is being developed by Ilaria Fichera at Eindhoven University of Technology (TU/e).
Funding
This research is founded by the Dutch Research Council (NWO), Applied and Engineering Sciences (AES) under grant agreement No. 19430, with project title "A new era of room acoustics simulation software: from academic advances to a sustainable open-source project and community".
License
Diffusion is under copyright of Building Acoustics Group at the Eindhoven University of Technology and is licensed under GNU General Public License v2.0. See LICENSE.md for more details.
References
J. M. Navarro, J. Escolano and J. J. Lopez, Implementation and evaluation of a diffusion equation model based on finite difference schemes for sound field prediction in rooms, Applied Acoustics 73 (2012).
R. P. Muñoz, Numerical modeling for urban sound propagation: developments in wave-based and energy based methods, PhD Thesis, Technische Universiteit Eindhoven, 2019.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file acousticde-0.1.0.tar.gz.
File metadata
- Download URL: acousticde-0.1.0.tar.gz
- Upload date:
- Size: 7.6 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4a883246ea3270cc56e8b6fe2abb7fa23e6352e13003cade6433be7337d5f9c8
|
|
| MD5 |
3639e879f840976b1e33f9075e03205d
|
|
| BLAKE2b-256 |
bfcbd0c504b63cb698232427b39adc7841efd6ce8aa9e41a59d958da55308e44
|
File details
Details for the file acousticde-0.1.0-py3-none-any.whl.
File metadata
- Download URL: acousticde-0.1.0-py3-none-any.whl
- Upload date:
- Size: 7.6 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9a7b4fb630b1424e2ab057f50b62ccaef9c5c3a9a10d13a06f5f68169259bcdd
|
|
| MD5 |
2506b29f83e5508eae7f71622bbc2082
|
|
| BLAKE2b-256 |
f8b7ea6a78a698bf278ce97452aea2f33dba68bfcb77a81f08f739a178981c97
|