Modern architecture promotes a high demand for transparent building envelopes. Typically, glass façades are designed under a variety of objectives, one of which is to meet sound insulation requirements. Reliable and fairly accurate estimation of the sound insulation properties of different glass assemblies becomes time-consuming and difficult due to the complexity of experimental testing or numerical simulations. Therefore, this paper presents a Machine Learning approach for predicting the acoustic properties (weighted sound insulation value RW, STC, OITC) of different glazing systems. For this purpose,
SOUNDLAB AI Tool-Machine learning for sound insulation value predictions
Date
Authors
Ing Michael Anton Kraus, M&M Network-Ing UG, Henrik Riedel, Rafael Bischof, Leon Schmeiser, Ingo Stelzer
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