Development of sound insulation prediction tool by integration of life cycle assessment

Abstract

This research aims to develop an acoustic design methodology for CLT floor assemblies using artificial neural networks approach by integration of life cycle assessment (LCA). 72 Lab-based measurements are used to develop the acoustic prediction tool. They are related to 29 different CLT-based floor assemblies. The weighted sound reduction index (Rw), and the weighted normalized impact sound pressure level (Ln,w) are estimated with an accuracy of 2 dB. Then a LCA study is conducted on wooden assemblies. The acoustic performance and their environmental impacts are compared to highlight trends that may guide decision-makers in the design phase. This paper initially found that CLT-based floor assemblies generally increase the environmental impacts to achieve better acoustic insulation. However, a good sound attenuation can be reached by selecting suitable acoustic solutions.