Contribution
LCA-Driven Optimisation of Acoustic Materials Selection
* Presenting author
Abstract:
Ensuring good room acoustics is essential for well-being, yet it is also increasingly important to minimize environmental impacts of buildings. This project aims to develop a Python tool that optimizes the selection of room acoustic materials based on reverberation time (RT) performance and life cycle assessment (LCA) to minimize environmental impact. The tool takes as input the target RT values for multiple frequencies, the room dimensions, and the surfaces original material. A database has been created to compile absorption coefficients and environmental impacts of acoustic materials, collected from Danish Environmental Product Declarations (EPDs). Using this database, different combinations of acoustic materials and coverage levels across surfaces like walls, floor, and ceiling are generated. Sabine’s formula is then used to select the combinations that meet the RT requirements. Finally, the user selects an environmental impact category to minimize such as Climate Change, or an aggregated single score across all categories. In output, the tool provides what acoustic materials and what quantity to use on the different room surfaces to satisfy the RT requirement and to minimize the given criteria. It also provides an expected RT curve and LCA-related graphs, assisting users in making environmentally informed choices for sustainable acoustic design.