| Issue |
Acta Acust.
Volume 9, 2025
|
|
|---|---|---|
| Article Number | 61 | |
| Number of page(s) | 16 | |
| Section | Building Acoustics | |
| DOI | https://doi.org/10.1051/aacus/2025050 | |
| Published online | 17 October 2025 | |
Scientific Article
An outdoor-to-indoor sound propagation modelling framework for evaluating noise exposure applications
Building Acoustics Group, Department of the Built Environment, Eindhoven University of Technology, Het Kranenveld 8, Eindhoven, 5612 AZ, The Netherlands
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
5
June
2025
Accepted:
11
September
2025
Abstract
Environmental noise exposure has shown to have significant negative effects on people’s lives. In noise exposure studies, outdoor noise levels are usually preferred over indoor levels for investigating exposure-response relationships, introducing a systematic risk of bias. Hence, an outdoor-to-indoor sound propagation modelling framework is defined for estimating indoor noise levels based on outdoor levels. Particularly, by expressing outdoor and indoor sound propagation via energetic models and façade (multi-component and multi-layered) structures via computational sound insulation models (Transfer Matrix Method), outdoor-based indoor impulse responses can be generated. To validate the framework, a case study was conducted, showing that measured and simulated sound insulation were in good agreement. Finally, this framework was applied to generate datasets of outdoor and indoor noise levels (noise indicators) based on scenarios of outdoor environment, indoor environment, and façade structures. This allows the training of statistical learning approaches for estimating indoor noise levels and identifying important predictors. Results show that a random-forest approach outperforms a stepwise and a neural network approach across all the employed noise indicators (RMSE < 2 dB). These models enable the estimation of indoor sound exposure levels based on outdoor levels as well as the exploration of exposure-response relationships in locations with known built environment characteristics.
Key words: Sound insulation / Sound propagation / Impulse response synthesis / Noise exposure / Statistical learning
© The Author(s), Published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.
