Abstracts Submitted: 250
Number of Users: 297
View Abstracts Submitted
Back to home Page
Conventional acoustic barriers used for noise abatement, backed by their effectiveness and design simplicity, have been well known since decades. This work demonstrates the three dimensional simulation of an array of rectangular reflecting barriers, and realizes their application in noise control. Application of multiple barriers or an array of barriers may not prove to be cost-effective, but the significant reduction in insertion loss that can be achieved by their usage, can justify the financial factor. The array, basically exploits the presence of a complex acoustic field, created due to multiple reflections from the group of barriers. The interference field created due to the acoustic source and multiple reflections from the barriers has shown better attenuation characteristics than that achieved by a single barrier. The three-dimensional numerical analysis helped us significantly to visualize, manipulate and map the sound field efficiently. The first part of this work focuses on developing a high-accuracy Dispersion-Relation-Preserving numerical scheme for spatial discretization, Optimized Coupled Compact Difference Scheme (OCCS), along with an optimized second-order, five stage Runge-Kutta scheme (ORK5) for temporal integration. This in-house development of these numerical schemes has been explained considering the characteristics of the schemes, which has been reported here to support the sufficiency for the chosen problem. In the second part, a comparison has been made, demonstrating the superiority of multiple barriers on the sound field over a single barrier. This study has been extended to the use of an array of barriers, which is simply a confined pattern of multiple barriers. The dimensional entities characterizing the barriers has been varied to analyze their effect on the sound field. This will further endow a corrective measure to remodel the dimensional parameters of the barriers, to realize enhanced effectiveness.
© Copyright 2017 All Rights Reserved