Human-centered design optimization for noise control technologies in built environments

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Noise has a significant effect on the quality of space by influencing building occupant comfort and performance. Traditional approaches in the noise control area that attempt only to reduce physical noise levels have certain inherent limitations. These approaches tend to overlook occupant characteristics and behaviours. Without careful consideration of occupant patterns in spaces, efforts to quantify acoustic quality in unoccupied conditions can fail to meet the acoustic requirements for users. An optimized noise control product design incorporating occupant comfort is thus a significant piece of knowledge that has not yet been well-established. The long-term objective of the proposed research program is, therefore, to improve acoustic comfort in building spaces by providing a human-centered acoustic design optimization methodology. The short-term objectives are: (a) to develop an automatic activity noise level detection method in occupied classrooms, (b) to optimize a microperforated panel-embedded silencer for tonal HVAC noise, and (c) to optimize a sound masking system for occupied open-plan offices. To achieve the objectives outlined in the research proposal, a series of acoustic measurements, data analyses, numerical simulations, and subjective tests will be conducted. First, acoustic data in occupied spaces will be collected to obtain occupancy patterns for each space type. Accurate background noise spectra in building spaces will be made available for predicting acoustic activities. Unsupervised machine learning algorithms such as a Gaussian mixture model will be used to classify the background noise levels. The speech intelligibility for classrooms, sound masking system for open-plan offices, and a duct silencer for HVAC systems will be optimized by identifying crucial components. Finally, improved occupant comfort based on optimization of the noise reduction technologies will be validated in a virtual reality laboratory. The results of this research will provide an optimization methodology for designing noise-control technologies in occupied indoor spaces. The successful completion of the proposed research can be expected to improve the cost-effectiveness of the duct silencer and sound masking system design. The outcomes also can be used as an evidence-based design approach for sustainable buildings. The culmination of these efforts will be the achievement of optimal acoustic quality in building spaces, thereby improving occupant comfort and performance in the built environment.