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Naveen Garg, Siddharth Dhruw and Laghu Gandhi

Abstract

The paper presents the application of Artificial Neural Networks (ANN) in predicting sound insulation through multi-layered sandwich gypsum partition panels. The objective of the work is to develop an Artificial Neural Network (ANN) model to estimate the Rw and STC value of sandwich gypsum constructions. The experimental results reported by National Research Council, Canada for Gypsum board walls (Halliwell et al., 1998) were utilized to develop the model. A multilayer feed-forward approach comprising of 13 input parameters was developed for predicting the Rw and STC value of sandwich gypsum constructions. The Levenberg-Marquardt optimization technique has been used to update the weights in back-propagation algorithm. The presented approach could be very useful for design and optimization of acoustic performance of new sandwich partition panels providing higher sound insulation. The developed ANN model shows a prediction error of ±3 dB or points with a confidence level higher than 95%.

Open access

Naveen Garg, Anil Kumar and Sagar Maji

Abstract

The paper presents an extensive review investigating the practical aspects related to the use of single- number ratings used in describing the sound insulation performance of partition wall panels and practical complications encountered in precise measurements in extensive frequency range from 50 Hz to 5 kHz. SWOT analysis of various single number ratings is described. A laboratory investigation on a double wall partition panel combination revealed the significant dependence of STC rating on transmission loss at 125 Hz attributed to 8 dB rule. An investigation conducted on devising alternative spectrums of aircraft noise, traffic noise, vehicular horn noise and elevated metro train noise as an extension to ISO 717-1 Ctr for ascertaining the sound insulation properties of materials exclusively towards these noise sources revealed that the single-number rating Rw + Ctr calculated using ISO 717-1 Ctr gives the minimum sound insulation, when compared with Rw + Cx calculated using the alternative spectrums of aircraft noise, traffic noise, etc., which means that material provides a higher sound insulation to the other noise sources. It is also observed that spectrum adaptation term Cx calculated using the spectrum of noise sources having high sound pressure levels in lower frequencies decreases as compared to ISO 717-1 Ctr owing to significant dependence of Ctr at lower frequencies.

Open access

Naveen Garg, Vishesh and Sagar Maji

Abstract

The paper presents a retrospective study for selection of noise barrier for road traffic noise abatement. The work proposes the application of Fuzzy TOPSIS (Technique for order preference by similarity to an ideal solution) approach is selection of optimal road traffic noise barrier. The present work utilizes the fuzzy TOPSIS model proposed by Mahdavi et al. (2008) in determination of ranking order of various types of noise barriers with respect to the various criteria considered. It is suggested that application of this approach can be very helpful in selection and application of optimal noise barrier for road traffic noise abatement.

Open access

Naveen Garg, Anil Kumar and Sagar Maji

Abstract

The paper presents application of Taguchi method in optimizing the sound transmission loss through sandwich gypsum constructions and those comprising of masonry concrete blocks and gypsum boards in order to investigate the relative influence of the various parameters affecting the sound transmission loss. The application of Taguchi method for optimizing sound transmission loss has been rarely reported. The present work uses the results analytically predicted on “Insul” software for various sandwich material configurations as desired by each experimental run in an L8 orthogonal array. The relative importance of the parameters on single-number rating, Rw (C, Ctr) is evaluated in terms of percentage contribution using Analysis of Variance (ANOVA). The ANOVA method reveals that type of studs, steel stud frame and number of gypsum layers attached are the key factors controlling the sound transmission loss characteristics of sandwich multi-layered constructions.

Open access

Naveen Garg, A. K. Sinha, M. Dahiya, V. Gandhi, R. M. Bhardwaj and A. B. Akolkar

Abstract

The paper describes the noise monitoring data acquired from the pilot project on the establishment of National Ambient Noise Monitoring Network (NANMN) across seven major cities in India for continuous noise monitoring throughout the year. The annual average Lday (06-22 h) and Lnight (22-06 h) values observed in year 2011-2014 for the 35 locations under study in which 14 locations are in commercial zone,5 in Industrial, 7 in residential and 9 in silence zones are described. The long-term noise monitoring shows that ambient noise levels have marginally increased for 29 sites (82.9%) since past four years. The present study is focused on evaluation and analysis of environmental noise pollution at 35 noise monitoring sites in seven major cities of India and shall be instrumental in planning for the noise abatement measures for controlling the noise pollution in these sites.