A soft-sensing approach for the evaluation of the acoustic comfort due to building envelope protection against external noise. (November 2019)

• Record Type: Journal Article
• Authors: Claudi, Livia; Arnesano, Marco; Chiariotti, Paolo; Battista, Gianmarco; Revel, Gian Marco
• Is Part Of: Measurement. Volume 146(2019)
• Page Start: 675
• Page End: 688
• Publication Date: 2019-11
• Subjects: Acoustic comfort -- Soft-sensing -- Acoustic measurements -- Building envelope -- Building retrofit -- External noise; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2019.07.003
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Soft-sensor for acoustic comfort measurements in buildings renovation. Application of the methodology to a real case study. Comparison between the KPI evaluated from measured and simulated data. Uncertainty and sensitivity analyses and impact on the decision-making process. Identification of the critical input variables to reduce the output uncertainty. Abstract: This research presents a methodology for measuring acoustic comfort using a soft-sensing approach to support decision-making for buildings renovation. The soft-sensor provides a measurement system for evaluating indoor acoustic quality of buildings (housing, schools, offices, etc.) in relation to the external noise level. The metric is represented by Key Performance Indicators ( KPIs ), which quantitatively express the acoustic comfort. Information regarding the current condition of the building ("As-is" KPI ) is provided as a normalised value for the simplified quantification of acoustic performance. The knowledge of the "As-is" KPI allows the design team to compare it with the new KPIs obtained from renovation scenarios ("What – if" KPI ). A case study is presented to demonstrate the exploitability of the methodology. Sensitivity and uncertainty analyses are performed to establish how the accuracy of the KPI measurement impacts on the decision-making process. The methodology shows promising results in the identification of the best retrofit strategy.