Archives of Acoustics, 42, 4, pp. 643–651, 2017

Prediction of Sound Insulation of Sandwich Partition Panels by Means of Artificial Neural Networks

Naveen GARG
CSIR-National Physical Laboratory

Siddharth DHRUW
National Institute of Technology, Hamirpur

National Institute of Technology, Kurukshetra

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 $R_w$ 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 $R_w$ 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%.
Keywords: weighted sound reduction index; Rw; Sound Transmission Class; STC
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AcouSYS software (2017), CSTB France, (accessed on 08.05.2017).

Antόnio J.M.P., Tadeu A., Godinho L. (2003), Analytical evaluation of the acoustic insulation provided by double infinite walls, Journal of Sound and Vibration, 263, 113–129.

ASTM E 90:1990, Standard Test Method for Laboratory Measurement of Airborne Sound Transmission Loss of Building Partitions and Elements, ASTM International, West Conshohocken.

ASTM-E413, Classification for Rating Sound Insulation, revised version in 2016, American Society for Testing and Materials, West Conshohocken.

Ballagh K.O. (2004), Accuracy of prediction methods for sound transmission loss, Inter-noise, (accessed on 08.05.2017).

Bradley J.S., Birta J.A. (2000), Laboratory measurements of the sound insulation of building facade elements, IRC Internal Report, IRC IR-818.

Bradley J.S., Birta J.A. (2001), On the sound insulation of wood stud exterior walls, Journal of Acoustical Society of America, 110, 3086–3096.

Bradley J.S., Gover B.N. (2011), Selecting walls for speech privacy, IRC report RR-314.

Buratti C., Barelli L., Moretti E. (2013), Wooden windows: Sound insulation evaluation by means of artificial neural networks, Applied Acoustics, 74, 740–745.

Cai M., Yin Y., Xie M. (2009), Prediction of hourly air pollutant concentrations near urban arterials using artificial neural network approach, Transportation Research Part D, 14, 32–41.

Craik R.J.M., Smith R.S. (2000), Sound transmission through double leaf lightweight partitions. Part I: airborne sound, Applied Acoustics, 61, 2, 223–245.

Crocker M., Price A.J. (1969), Sound transmission using statistical energy analysis, Journal of Sound and Vibration, 9, 3, 469-486.

Duch W., Jankowski N. (1999), Survey of neural network transfer functions, Neural Computing Surveys, 2, 163–212.

Garg N., Kumar A., Maji S. (2013a), Parametric sensitivity analysis of factors affecting sound insulation of double glazing using Taguchi method, Applied Acoustics, 74, 1406–1413.

Garg N., Kumar A., Maji S. (2013b), Practical concerns associated with single number ratings in measuring sound transmission loss properties of partition panels, Archives of Acoustics, 38, 1, 115–124.

Garg N., Kumar A., Maji S. (2013c), Significance and implications of airborne sound insulation criteria in building elements for traffic noise abatement, Applied Acoustics, 74, 1429-1435.

Garg N., Kumar A., Maji S. (2014a), Parametric sensitivity analysis of factors affecting the sound insulation of multi-layered building elements, Archives of Acoustics, 39, 2, 165–176.

Garg N., Maji S. (2015), On analyzing the correlations & implications of single-number quantities for rating airborne sound insulation in frequency range 50 Hz to 5 kHz, Journal of Building Acoustics, 22, 1, 121–136.

Garg N., Mangal S.K, Saini P.K., Dhiman P., Maji S. (2015), Comparison of ANN and analytical models in traffic noise modeling and predictions, Journal of Acoustic Australia, 43, 179–189.

Garg N., Saxena T.K., Kumar A. (2014b), Uncertainty Evaluation and Implications of spectrum adaptation terms in determining the airborne sound insulation in building elements, Noise Control Engineering Journal, 39, 2, 165–176.

Garg N., Sharma M.K., Parmar K.S., Soni K., Singh R.K., Maji S. (2016), Comparison of ARIMA and ANN approach in time-series predictions of traffic noise, Noise Control Engineering Journal, 64, 4, 522–531.

Ghaffari A., Abdollahi H., Khoshayand M.R., Bozchalooi I.S., Dadgar A., Rafiee-Tehrani M. (2006), Performance comparison of neural network training algorithms in modeling of bimodal drug delivery, International Journal of Pharmaceutics, 327, 126–138.

Givargis Sh., Karimi H. (2010), A basic neural traffic noise prediction model for Tehran’s road, Journal of Environmental Management, 91, 2529–2534.

Guillen I., Uris A., Estella H., Llinares J., Llopsis A. (2008), On the sound insulation of masonry wall facades, Building and Environment, 43, 523–529.

Halliwell R.E., Nightingale T.R.T., Warnock A.C.C., Birta J.A. (1998), Gypsum board walls: Transmission loss data, National Research Council, Canada, Report No. IRC-IR-761.

Hush D.R., Horne B.G. (1993), Progress in supervised neural networks, IEEE Signal Processing Magazine, 10, 8–39.

Insul Software Manual (2017), (accessed on 08.03.2017).

ISO 140/III 1978 (E) (revised as ISO 10140-2:2010), Acoustics – Measurement of sound insulation in buildings and of building elements, Part 3: Laboratory measurements of airborne sound insulation of building elements.

Kumar P., Nigam S.P., Kumar N. (2014), Vehicular traffic noise modelling using artificial neural network approach, Transportation Research Part C, 40, 111–122.

Kurra S. (2012), Comparison of the models predicting sound insulation values of multilayered building elements, Applied Acoustics, 73, 575–589.

Kurra S., Arditi D. (2001), Determination of sound transmission loss of multilayered elements. Part 1: predicted and measured results, Acta Acustica, 87, 5, 582–592.

LeCun Y.A., Bottou L., Orr G.B., Muller K.-R. (1998), Neural Networks: tricks of the trade, Lecture Notes in Computer Science, Springer, pp. 9–48.

Lin M., Tsai K., Su B. (2009), Estimating the sound absorption coefficients of perforated wooden panels by using artificial neural networks, Applied Acoustics, 70, 31–40.

Lyon R.H., DeJong R.G. (1995), Theory and application of statistical energy analysis, Butterworth-Heinemann, 2nd ed.

MathWorks, Train and Apply Multilayer Neural Networks, (accessed on 08.03.2017)

Montgomery D.C., Runger G.C. (2011), Applied Statistics and Probability for Engineers, 5th ed., Wiley, Ch. 10, pp. 351–394.

Mungiole M., Keith Wislon D. (2006), Prediction of outdoor sound transmission loss with an artificial neural network, Applied Acoustics, 67, 324–345.

Mustafa M.R., Rezaur I.R.B., Rahardjo H., Isa M.H., Arif A. (2015), Artificial Neural Network Modeling for Spatial and Temporal Variations of Pore-Water Pressure Responses to Rainfall, Advances in Meteorology, Article ID 273730, 1–12. (accessed on 08.03.2017).

Nannariello J., Fricke F.R. (1999), The prediction of reverberation time using neural network analysis, Applied Acoustics, 58, 305–325.

Nannariello J., Fricke F.R. (2001), A neural network analysis of effect of geometric variables on concert hall G values, Applied Acoustics, 62, 12, 1397–1410.

Nannariello J., Hodgon M., Fricke F.R. (2001), Neural network predictions of speech levels in university classrooms, Applied Acoustics, 62, 7, 749–767.

Nucara A., Pietrafesa M., Scaccianoce G., Staltari G. (2002), A comparison between analytical models and Artificial neural networks in the evaluation of traffic noise levels, Proceedings 17th International Congress on Acoustics, ICA Rome, pp. 208–209.

Pamanikabud P., Vivitjinda P. (2002), Noise prediction for highways in Thailand, Transportation Res. Part D, 7, 441–449.

Park H.K., Bradley J.S. (2009), Evaluating standard airborne sound insulation measures in terms of annoyance, loudness and audibility ratings, Journal of Acoustical Society of America, 126, 1, 208–219.

Pellicier A., Trompette N. (2007), A review of analytical methods, based on the wave approach, to compute partitions transmission loss, Applied Acoustics, 68, 10, 1192–1212.

Quirt J.D., Warnock A.C.C, Birta J.A. (1995), Sound transmission through Gypsum board walls: Sound transmission results, IRC-IR-693, National Research Council, Canada.

Roozen N.B., Muellner H., Labelle L., Rychtáriková M., Glorieux C. (2015), Influence of panel fastening on acoustic performance of light-weight building elements: Study by sound transmission and laser scanning vibrometry, Journal of Sound and Vibration, 346, 100–116.

Scholl W., Lang J., Wittstock V. (2011), Rating of Sound Insulation at Present and in Future. The Revision of ISO 717, Acta Acustica united with Acustica, 97, 686–698.

Sharp B.H. (1978), Prediction methods for the sound transmission of building elements, Noise Control Engineering Journal, 11, 53–63.

Uris A, Llopis A., Llinares J. (1999), Effect of the rockwool bulk density on the airborne sound insulation of lightweight double walls, Applied Acoustics, 58, 327–331.

Wang T., Li S., Rajaram S., Nutt S.R. (2010), Predicting the sound transmission loss of sandwich panels by statistical energy analysis approach, ASME Journal of Vibration Acoustics, 132, 1, 011004-011004-7, doi:10.1115/1.4000459.

Wang T., Sokolinsky V.S., Rajaram S., Nutt S.R. (2005), Assessment of sandwich models for the prediction of sound transmission loss in unidirectional sandwich panels, Applied Acoustics, 66, 245–262.

Warnock A.C.C. (1985), Factors affecting sound transmission loss, Canadian Building Science Insight, Canadian Building Science Insight, CBD 239.

Warnock A.C.C. (1990), Sound transmission loss measurement through 190 mm and 140 mm blocks with added dry wall and through cavity block walls, NRC Canada, Internal Report No. 586.

Warnock A.C.C. (1993), Sound transmission through slotted concrete blocks with attached gypsum board, National Research Council, Canada, Journal of the Acoustical Society of America, 94, 5, 2713–2720.

Warnock A.C.C. (1998), Controlling sound transmission through concrete block walls, Construction Technology Update No. 13, National Research Council of Canada.

Warnock A.C.C., Quirt J.D. (????), Sound transmission through gypsum board walls, Institute for Research in Construction, National Research Council of Canada, NRCC-38990, (accessed on 08.03.2017).

Warnock A.C.C., Quirt J.D. (1997), Control of sound transmission through gypsum board walls, Construction Technology Updated No. 1, Institute for Research in Construction, National Research Council of Canada. (accessed on 08.03.2017).

Zhang G., Patuwo B.E., Hu M.Y. (1998), Forecasting with artificial neural networks: The state of art, International Journal of Forecasting, 14, 35–62.

Zhou J., Bhaskar A., Zhang X. (2013), Optimization for sound transmission through a double-wall panel, Applied Acoustics, 74, 12, 1422–1428.

DOI: 10.1515/aoa-2017-0068

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