Prediction of Sound Insulation Using Artificial Neural Networks—Part II: Lightweight Wooden Façade Structures
Source abstract
Abstract
A prediction model based on artificial neural networks is adapted to forecast the acoustic performance of airborne sound insulation of various lightweight wooden façade walls. A total of 100 insulation curves were used to develop the prediction model. The data are laboratory measurements of façade walls in one-third-octave bands (50 Hz–5 kHz). For each façade wall, geometric and physical information (material type, dimensions, thicknesses, densities, and more) are used as input parameters. The model shows a satisfactory predictive capability for airborne sound reduction. A higher accuracy is obtained at middle frequencies (250 Hz–1 kHz), while lower and higher frequency ranges often show higher deviations. The weighted airborne sound reduction index (Rw) of façades can be estimated with a maximum difference of 3 dB. Sometimes, the model shows high variations within fundamental and critical frequencies that influence the predictive precision. A sensitivity analysis is implemented to investigate the significance of parameters in insulation estimations. The material density (i.e., cross-laminated timber panel, gypsum board), thickness of the insulation materials, thickness and spacing between interior studs and the total density of façades are factors of significant weight on predictions. The results also emphasize the importance of façade thickness and the total density of the clustered exterior layers.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Acoustic Wave Phenomena Research · Noise Effects and Management · Wind and Air Flow Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Applied Sciences, University of Quebec at Chicoutimi, Saguenay, QC G7H2B1, Canada
Engineering Acoustics, Lund University, John Ericssons väg 1, 223 63 Lund, Sweden
Technological Institute FCBA, All. de Boutaut, 33000 Bordeaux, France
Funding
Natural Sciences and Engineering Research Council (NSERC) of Canada · Region Nouvelle-Aquitaine · industrial partners of the NSERC industrial chair on eco-responsible wood construction (CIRCERB)
References (70)
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