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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A method to predict reverberation time in concert hall preliminary design stage

Zhang, Yan 04 October 2005 (has links)
A historical review is performed to study the impact of acoustical knowledge on concert hall developments. It shows that although acoustics developed from myth to real science, there is still a gap between its fast growing knowledge and relatively slow applications to improve designs. Architectural acoustics research and education shall help populating the tacit knowledge and experience of acousticians to reduce the gap between design and knowledge. The established paradigm in this field is to identify the performance goals of concert halls, recognize the available design information in different stages, and establish models to link them together. Placed in this general picture, this thesis focuses on providing design support for preliminary stage. It develops a model to link accessible design features with the most important acoustics performance index, reverberation time. A literature review on exiting reverberation time prediction methods shows that they are based on either too demanding or over-simplified for this stage. This study intends to develop a model that makes maximum use of available information and improves prediction accuracy in comparison with existing simplified methods. Through literature survey and data analysis, three factors (geometrical shape, non-uniform material distribution and scattering effect) are recognized as significant for reverberation time prediction. This thesis developed a simplified model taking these factors into consideration and calibrated this model with empirical data through Bayesian statistical method.

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