Development of Experimental and Modelling Approaches to Characterize Noise Reduction Capability of Porous Materials

Abstract

Porous materials have been recognized as effective materials for noise reduction and noise control. It is also recognized that numerous inherent and external factors may affect the noise reduction properties of porous materials. The research of this dissertation aims to develop innovative experimental and modelling approaches to analyze the noise reduction capability of porous materials under different conditions and to study the main factors affecting the noise reduction capability of porous materials. The impact of material age on noise reduction properties of porous materials is first studied, and a Nested Ensemble Filtering (NEF) approach is proposed for parameter estimation and uncertainty quantification in traffic noise emission from porous pavements. The proposed NEF method improves upon the ensemble Kalman filter (EnKF) method by incorporating sample importance resampling (SIR) procedures into the EnKF update process. Applying the proposed NEF method to traffic noise prediction on the Trans-Canada Highway in the City of Regina, the results indicate: (a) the NEF method provides accurate parameter estimation in the traffic noise prediction model; (b) the uncertainty in the traffic noise model can be significantly reduced and quantified through the proposed NEF approach; and (c) the unit noise emission for new porous pavement is significantly decreased in comparison with that of old pavement considered, regardless of the impacts of uncertainties. In addition to porous material age, air density within pore structures also impacts acoustic properties of porous materials. Consequently, a series of experimental investigations are conducted to investigate the effects of different levels of vacuum on the sound reduction and acoustic properties of porous materials. An innovative experiment would be designed to measure acoustic responses, such as sound intensities and corresponding frequencies, for various porous materials under different vacuum levels. The results indicate that applying even relatively low vacuum levels to porous materials has a significant effect on sound reduction. The sound absorption coefficients for various porous materials under different vacuum levels are further characterized through the statistical energy analysis (SEA) approach. It is anticipated that the research findings in this research may lead to the construction of effective sound reducing products for attenuating noise, increasing insertion loss or improving sound insulation. In order to comprehensively evaluate the applicability of porous-structured noise control (PSNC) measures, a systematic evaluation framework is to be proposed to identify the most appropriate PSNC options under consideration of both internal and external factors. Such a framework is based on an inexact fuzzy integer chance constraint programming (IFICCP) approach to integrate the acoustic properties of each measure (i.e. reduction rate), unit cost, installation location and environmental tolerance into a general framework. Also, the IFICCP method can handle uncertainties expressed as fuzzy and interval numbers in the noise control system established with various porous materials. A number of decision alternatives have been obtained for each acceptable noise level and analyzed under various fuzzy confidence levels. They can potentially reflect complex tradeoffs among cost and properties of porous materials, location, and environmental considerations, and further provide decision support to find the most desirable porous materials for noise reduction.