Many people are affected by noise coming from traffic, industrial activities or the neighborhood. The European Commission estimates that more than 30% of the European population may be exposed to excessive environmental noise levels and the related health risks, and the WHO estimates that at least one million healthy life years are lost every year from traffic-related noise alone in the western part of Europe. One way of protecting people from noise is by increasing the overall sound insulation of houses and housing units. However, the prediction of sound insulation levels in buildings is a complex problem as the sound insulation between two rooms is not a mere property of the separating wall or floor. It also depends on the properties of the adjacent rooms and on flanking transmission through other parts of the building. Uncertainties in geometry and material properties generally play an important role; and small connections between building parts can affect the overall sound insulation to a significant extent.

The development of a new generation of prediction tools that enable to understand, assess, and optimize the sound insulation performance of complex building structures, is therefore of crucial importance. This PhD project will aid in the development of such tools by focusing on modelling the complex building components of interest and their connections in a sufficiently detailed but computationally efficient way, and on dealing with the many uncertainties that are encountered in practice, in order to ensure robust sound insulation predictions. A hybrid finite element-statistical energy analysis approach, which has been validated for sound insulation prediction of single and double walls at the Structural Mechanics Section of KU Leuven in collaboration with the University of Cambridge, will serve as a starting point for these developments. This approach enables the rigorous coupling of detailed long-wavelength component models to very efficient, short-wavelength component models within a single probabilistic framework. Targeted applications include the acoustic analysis and optimization of walls and floors containing discrete connections and poroelastic layers, and of flanking transmission through connected building elements. Due attention will be paid to experimental validation; for this purpose, there will be a close cooperation with the Department of Physics and Astronomy, where building acoustics infrastructure is available (anechoic chamber, sound transmission suite, reverberation room).