Being the second largest environmental pollutant in Europe, noise has a high societal and economic impact. An important way of protecting people from noise is by ensuring a sufficient level of sound insulation in buildings and building units, so laws and building codes of practice have established minimum sound insulation requirements in almost every country worldwide. Unfortunately, meeting these requirements is becoming increasingly challenging, not only because of urban densification but especially also because the construction industry is facing continuous pressure to reduce its carbon footprint. This latter trend results in a shift towards building systems that are lightweight and therefore more prone to problematic sound transmission than conventional heavyweight buildings.
Acoustic requirements do not naturally align with a building’s structural and thermal requirements, so sound insulation cannot be an afterthought, it must be a central part of the building’s design. Nevertheless, engineering consultants, architects and manufacturers of building products and systems lack efficient and reliable tools for predicting and optimizing the sound insulation of their designs or products. As a result, substantial design margins are taken, and the acoustic development and optimization of new building products and systems typically relies on extensive experimental protype testing, which is costly and time-consuming.
In the ERC Starting Grant VirBAcous, new, dedicated numerical methods for sound insulation prediction have been developed that possess the required combination of a high prediction accuracy and a high computational efficiency. The aim of the ERC Proof of Concept Grant Soprano was to bridge the gap between the fundamental numerical methods from VirBAcous and the construction sector.
