Optimal traffic noise reduction with Asphalt Rubber Concrete (ARC) and establishment of a quantitative traffic noise prediction model

A methodology for predicting traffic noise is established in this research on the basis of developing a traffic noise prediction model focused mainly on noise related key factors including the microstructure of a pavement surface, sound energy absorption capabilities, noise emission generated from the interaction between the road pavement and vehicle tires, average traffic speed, average traffic volume, geometry of the road and atmospheric conditions. A quiet road material, "Asphalt Rubber Concrete (ARC)", is investigated for its acoustic and physical properties in relating to traffic noise reduction. Numerical simulations have been carried out and verified with experimental measurements from several road sections in Saskatchewan. This traffic noise prediction methodology tends to provide reasonably accurate predictions to forecast environmental traffic noise from Canadian roads and will be useful for road management, service maintenance, noise and air pollution control and road design and planning.;This research develops a quantitative method for predicting the sound absorption coefficients of various porous highway pavement materials, with respect to their material properties classification. Existing models were studied and extended to predict the absorption coefficients of porous materials as a function of their permeability, porosity, tortuosity and pavement thickness. Experiments were performed on samples taken from the field and experimental results were compared with the model's predicted values. The effects of several control parameters on the determination of the absorption coefficients were investigated. The Close Proximity Method (CPX) was performed to experimentally evaluate the road and tire noise emission on various pavement materials by excluding power line and aerodynamic noise sources. A statistical estimation method was applied to estimate the noise emission generated at the actual source on the ground.;A new traffic noise prediction model modified from existing models is developed to better fit road conditions in Saskatchewan. This model is intended to be used indoors and on-the-road by focusing on portability, calculation speed, ease of use, cost and accuracy. A basic software package with a user friendly interface is constructed to exemplify the practical use of the developed model. Verification of the numerical model and its application to the experimental results is carried out with a statistical approach and analysis. This model can be used to determine the influence of pavement characteristics and a roadway's geometry on reducing highway noise as well as planning road maintenance, designing road construction and reducing environmental traffic noise for better and quieter living.;Four commonly recognized standards for measuring traffic noise were conducted on twelve different road segments and surface materials in Saskatchewan from 2005 to 2009; 1) A Statistical Pass-By method was used to collect 24 hour average traffic noise sound levels from the road segments, 2) Measurements of the influence of road surfaces on traffic noise were carried out with a newly designed and custom made trailer to collect noise emission from the interaction between road segments and rotating tires and 3) The acoustic determination of the sound absorption coefficients and impedance ratios were performed to identify the sound absorption capabilities of the pavement materials 4) Experimental porosity and permeability measurements were conducted to study the influence of pavement porosity and permeability on the noise energy absorption capabilities of the pavements.