Applied sciences

Archives of Acoustics

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Archives of Acoustics | 2021 | vol. 46 | No 4 |

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Abstract

Electric guitar manufacturers have used tropical woods in guitar production for decades claiming it as beneficiary to the quality of the instruments. These claims have often been questioned by guitarists but now, with many voices raising concerns regarding the ecological sustainability of such practices, the topic becomes even more important. Efforts to find alternatives must begin with a greater understanding of how tonewood affects the timbre of an electric guitar. The presented study examined how the sound of a simplified electric guitar changes with the use of various wood species. Multiple sounds were recorded using a specially designed test setup and their analysis showed differences in both spectral envelope and the generated signal level. The differences between the acoustic characteristics of tones produced by the tonewood samples explored in the study were larger than the just noticeable differences reported for the respective characteristics in the literature. To verify these findings an informal listening test was conducted which showed that sounds produced with different tonewoods were distinguishable to the average listener.
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Bibliography

1. Ahvenainen P. (2018), Anatomy and mechanical properties of woods used in electric guitars, IAWA Journal, 40(1): 106–S6, doi: 10.1163/22941932-40190218.
2. Ahmed S.A., Adamopoulos S. (2018), Acoustic properties of modified wood under different humid conditions and their relevance for musical instruments, Applied Acoustics, 140: 92–99, doi: 10.1016/j.apacoust.2018.05.017.
3. Bennett B. (2016), The sound of trees: wood selection in guitars and other chordophones, Economic Botany, 70(1): 49–63, doi: 10.1007/s12231-016-9336-0.
4. Carral S. (2011), Determining the just noticeable difference in timbre through spectral morphing: a trombone example, Acta Acustica united with Acustica, 97(3): 466–476, doi: 10.3813/AAA.918427.
5. Fleischer H., Zwicker T. (1998), Mechanical vibrations of electric guitars, Acta Acustica united with Acustica, 84(4): 758–765.
6. Fletcher N., Rossing T. (1998), The Physics of Musical Instruments, doi: 10.1007/978-0-387-21603-4.
7. Green D.M. (1993), Auditory Intensity Discrimination, Springer Handbook of Auditory Research, Vol. 3, Springer, New York, doi: 10.1007/978-1-4612-2728-1_2.
8. Jansson E.V. (1983), Acoustics for the Guitar Maker, Function, Construction and Quality of the Guitar, Publication No. 38 of the Royal Swedish Academy of Music, Stockholm.
9. Koch M. (2001), Building Electric Guitars: How to Make Solid-Body, Hollow-Body and Semi-Acoustic Electric Guitars and Bass Guitars, Koch Verlag, Gleisdorf.
10. Martinez-Reyes J. (2015), Mahogany intertwined: Enviromateriality between Mexico, Fiji, and the Gibson Les Paul, Journal of Material Culture, 20(3): 313– 329, doi: 10.1177/1359183515594644.
11. Ozimek E. (2002), Sound and its Perception. Physical and Psychoacoustic Aspects [in Polish: Dzwiek i jego percepcja. Aspekty fizyczne i psychoakustyczne], Polish Scientific Publishers PWN, Warsaw.
12. Paté A., Le Carrou J., Fabre B. (2013), Ebony vs. Rosewood: experimental investigation about the influence of the fingerboard on the sound of a solid body electric guitar, [in:] Proceedings of the Stockholm Musical Acoustics Conference (SMAC), Stockholm (Sweden), pp. 182–187.
13. Paté A., Le Carrou J., Navarret B., Dubois D., Fabre B. (2015), Influence of the electric guitar’s fingerboard wood on guitarists’ perception, Acta Acustica united with Acustica, 101(2): 347–359, doi: 10.3813/AAA.918831.
14. Puszynski J. (2014), String-wood feedback in electrics string instruments, Annals of Warsaw University of Life Sciences – SGGW Land Reclamation, 2014(85): 196–199.
15. Puszynski J., Molinski W., Preis A. (2015), The effect of wood on the sound quality of electric string instruments, Acta Physica Polonica, 127(1): 114–116, doi: 10.12693/APhysPolA.127.114.
16. Schubert E., Wolfe J. (2006), Does timbral brightness scale with frequency and spectral centroid?, Acta Acoustica United with Acustica, 92(5): 820–825.
17. Torres J., Boullosa R. (2009), Influence of the bridge on the vibrations of the top plate of a classical guitar, Applied Acoustics, 70(11–12): 1371–1377, doi: 10.1016/j.apacoust.2009.07.002.
18. Torres J., Boullosa R. (2011), Radiation efficiency of a guitar top plate linked with edge or corner modes and intercell cancellation, The Journal of the Acoustical Society of America, 130(1): 546–556, doi: 10.1121/1.3592235.
19. Tzanetakis G., Cook P. (2002), Musical genre classification of audio signals, 2002 IEEE Transactions on Speech and Audio Processing, 10(5): 293–302, doi: 10.1109/TSA.2002.800560.
20. Ulrich R., Vorberg D. (2009), Estimating the difference limen in 2AFC tasks: pitfalls and improved estimators, Attention, Perception, & Psychophysics, 71(6): 1219–1227, doi: 10.3758/app.71.6.1219.
21. Wilkowski J., Michalowski P., Czarniak P., Górski J., Podziewski P., Szymanowski K. (2014), Influence of spruce, wenge and obeche wood used for electric guitar prototype on selected sound properties, Annals of Warsaw University of Life Sciences – SGGW. Forestry and Wood Technology, 85: 235–240.
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Authors and Affiliations

Jan Jasiński
1
Stanisław Oleś
1
Daniel Tokarczyk
1
Marek Pluta
1

  1. Department of Mechanics and Vibroacoustics, AGH University of Science and Technology, Cracow, Poland
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Abstract

The paper presents a method of eliminating the tonal component of an acoustic signal. The tonal component is approximated by a sinusoidal signal of a given amplitude and frequency. As the parameters of this component: amplitude, frequency and initial phase may be variable, it is important to detect these parameters in subsequent analysis time intervals (frames). If the detection of the parameters is correct, the elimination consists in adding a sinusoidal component with the detected amplitude and frequency to the signal, but the phase shifted by 180 degrees. The accuracy of the reduction depends on the accuracy of parameters detection and their changes.
Detection takes place using the Discrete Fourier Transform, whose length is changed to match the spectrum resolution to the signal frequency. The operation for various methods of synthesis of the compensating signal as well as various window functions were checked. An elimination simulation was performed to analyze the effectiveness of the reduction. The result of the paper is the assessment of the method in narrowband active noise control systems. The method was tested by simulation and then experimentally with real acoustic signals. The level of reduction was from 6.9 to 31.5 dB.

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Bibliography

1. Dabrowski Z., Stankiewicz B. (2013), Methodology of selecting the reference source for an active noise control system in a car, International Journal of Occupational Safety and Ergonomics, 19(1): 117–125, doi: 10.1080/10803548.2013.11076971.
2. Dabrowski Z., Dziurdz J., Górnicka D. (2017), Utilisation of the coherence analysis in acoustic diagnostics of internal combustion engines, Archives of Acoustics, 42(3): 475–481, doi: 10.1515/aoa-2017-0050.
3. Górski P., Morzynski L. (2013), Active noise reduction algorithm based on NOTCH filter and genetic algorithm, Archives of Acoustics, 38(2): 185–190, doi: 10.2478/aoa-2013-0021.
4. ISO 1996-2:2017 (2017), Acoustics – Description, measurement and assessment of environmental noise – Part 2: Determination of sound pressure levels, International Organization for Standardization, Geneva, Switzerland.
5. Kuo S.M., Tahernezhadi M., Ji L. (1997), Frequency- domain periodic active noise control and equalization, IEEE Transactions on Speech and Audio Processing, 5(4): 348–358, doi: 10.1109/89.593309.
6. Kim S., Park Y. (1999), Active control of multi-tonal noise with reference generator based on on-line frequency estimation, Journal of Sound and Vibration, 227(3): 647–666, doi: 10.1006/jsvi.1999.2383.
7. Łuczynski M. (2017), Analysis of the influence of amplitude, frequency and phase errors on effectiveness of noise reduction of multitone signals by active noise cancelling systems, [in:] Postepy akustyki =Advances in Acoustics 2017, Bismor D. [Ed.], pp. 61– 67, Gliwice: Polskie Towarzystwo Akustyczne, Oddział Górnoslaski, doi: 10.1515/aoa-2017-0059.
8. Łuczynski M. (2018), Normal to whisper speech conversion using active tone cancellation – case study, [in:] Postepy akustyki =Advances in acoustics 2018, Marszal J. [Ed.], pp. 62–66, Gdansk: Polskie Towarzystwo Akustyczne, Oddział Gdanski.
9. Łuczynski M. (2019a), Classes of tonality of signals in the aspect of active elimination of tonal components, Vibrations in Physical Systems, 30(1): Article ID 2019126.
10. Łuczynski M. (2019b), Primary study on removing mains hum from recordings by active tone cancellation algorithms, [in:] 146th Convention Audio Engineering Society, March 20–23, 2019 Dublin, Ireland, Convention paper No. 10147, http://www.aes.org/elib/ browse.cfm?elib=20280.
11. Łuczynski M., Brachmanski S. (2017), Mathematical Model of the Acoustic Signal Generated by the Combustion Engine, [in:] 142nd Convention Audio Engineering Society, May 20–23, 2017, Berlin, Germany, Convention paper No. 9717, http://www.aes.org/elib/ browse.cfm?elib=18595.
12. Pawełczyk M. (2008), Active noise control – a review of control-related problems (plenary paper), [in:] 55th Open Seminar on Acoustics, Wrocław–Piechowice 8– 12.09.2008, pp. 65–74.
13. Qiu X., Hansen C.H. (2000), An algorithm for active control of transformer noise with online cancellation path modelling based on perturbation method, Journal of Sound and Vibration, 240(4): 647–665, doi: 10.1006/jsvi.2000.3256.
14. Qiu X., Li X., Ai Y., Hansen C.H. (2002), A waveform synthesis algorithm for active control of transformer noise: implementation, Applied Acoustics, 63(5): 467– 479, doi: 10.1016/S0003-682X(01)00060-3.
15. Rocha R.D. (2014), A Frequency-Domain Method for Active Acoustic Cancellation of Known Audio Sources, A Master Thesis, Faculty of California Polytechnic State University, San Louis Obispo, June 2014, https://digitalcommons.calpoly.edu/cgi/viewcontent.cgi? article=2331&context=theses.
16. Rout N.K., Das D.P., Panda G. (2019), PSO based adaptive narrowband ANC algorithm without the use of synchronization signal and secondary path estimate, Mechanical Systems and Signal Processing, 114: 378– 398, doi: 10.1016/j.ymssp.2018.05.018.
17. Ueda T., Fujii K., Hirobayashi S., Yoshizawa T., Misawa T. (2013), Motion analysis using 3D highresolution frequency analysis, IEEE Transactions on Image Processing, 22(8): 2946–2959, doi: 10.1109/TIP.2012.2228490.
18. Wang J., Huang L., Cheng L. (2005), A study of active tonal noise control for a small axial flow fan, The Journal of the Acoustical Society of America, 117(2): 734–743, doi: 10.1121/1.1848072.
19. Xiao Y., Ma L., Hasegawa K. (2009), Properties of FXLMS-based narrowband active noise control with online secondary-path modeling, IEEE Transactions on Signal Processing, 57(8): 2931–2949, doi: 10.1109/TSP.2009.2020766.
20. Yoshizawa T., Hirobayashi S., Misawa T. (2011), Noise reduction for periodic signals using high resolution frequency analysis, Journal on Audio, Speech, and Music Processing, 2011: 5, doi: 10.1186/1687-4722-2011-426794.
21. Zhang L., Tao J., Qiu X. (2012), Active control of transformer noise with an internally synthesized reference signal, Journal of Sound and Vibration, 331(15): 3466–3475, doi: 10.1016/j.jsv.2012.03.032.
22. Zivanovic M., Roebel A., Rodet X. (2004), A new approach to spectral peak classification, [In:] Proceedings of the 12th European Signal Processing Conference (EUSIPCO), pp. 1277–1280, https://hal.archives-ouvertes.fr/hal-01161188.

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Authors and Affiliations

Michał Łuczyński
1
Andrzej Dobrucki
1
Stefan Brachmański
1

  1. Wroclaw University of Science and Technology, Chair of Acoustics and Multimedia, Wroclaw, Poland
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Abstract

Various types of passive sonar systems are used to detect submarines. These activities are complex and demanding. Therefore, computer simulations are most often used at the design stage of these systems. For this reason, it is also necessary to simulate the acoustic ambient noise of the sea. The article proposes a new numerical model of surface and quasi-spherical sea noise and presents its statistical parameters. The results of the application of the developed noise model to analyse the received signals of the DIFAR sonobuoy are also presented.
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Bibliography

1. Barclay D.R., Buckingham M.J. (2014), On the spatial properties of ambient noise in the Tonga Trench, including effects of bathymetric shadowing, The Journal of the Acoustical Society of America, 136(5): 2497–2511, doi: 10.1121/1.4896742.
2. Buckingham M.J. (2012), Cross-correlation in bandlimited ocean ambient noise fields, The Journal of the Acoustical Society of America, 131(4): 2643–2657, doi: 10.1121/1.3688506.
3. Burdick W.S. (1984), Underwater Acoustic System Analysis, Prentice-Hall, Englewood Cliffs, NJ.
4. Cohen J. (1988), Statistical Power Analysis for the Behavioral Sciences, 2nd ed., Lawrence Erlbaum Associates, Publishers.
5. Crocker M.J. (1998), Handbook of Acoustics, John Wiley & Sons.
6. Cron B.F., Sherman C.H. (1962), Spatial-correlation functions for various noise models, The Journal of the Acoustical Society of America, 34(11): 1732–1736, doi: 10.1121/1.1909110.
7. Cron B.F., Sherman C.H. (1965), Addendum: Spatial correlation functions for various noise models [J. Acoust. Soc. Am., 34: 1732–1736 (1962)], The Journal of the Acoustical Society of America, 38(4): 885, doi: 10.1121/1.1909826.
8. Franks L.E. (1981), Signal Theory. Revised Edition, Dowden & Culver, Inc.: Stroudsburg, PA.
9. Grelowska G., Kozaczka E., Kozaczka S., Szymczak W. (2013), Underwater noise generated by small ships in the shallow sea, Archives of Acoustics, 38(3): 351–356, doi: 10.2478/aoa-2013-0041.
10. Jagodzinski Z. (1961), Radionavigation Systems [in Polish], Wydawnictwo MON, Warszawa.
11. Klusek Z., Lisimenka A. (2004), Characteristics of underwater noise generated by single breaking wave, Hydroacoustics, 7: 107–114.
12. Klusek Z., Lisimenka A. (2016), Seasonal and diel variability of the underwater noise in the Baltic Sea, The Journal of the Acoustical Society of America, 139(4): 1537–1547, doi: 10.1121/1.4944875.
13. Kochanska I., Nissen I., Marszal J. (2018), A method for testing the wide-sense stationary uncorrelated scattering assumption fulfillment for an underwater acoustic channel, The Journal of the Acoustical Society of America, 143(2): EL116–EL120, doi: 10.1121/1.5023834.
14. Kozaczka E., Grelowska G. (2011), Shipping low frequency noise and its propagation in shallow water, Acta Physica Polonica A, 119(6A): 1009–1012, doi: 10.12693/APhysPolA.119.1009.
15. Lyons R.G. (2004), Understanding Digital Signal Processing, 2nd ed., Prentice Hall, Inc. 16. Mallet A.L. (1975), Underwater Direction Signal Processing System, US Patent No 3,870,989.
17. Ren C., Huang Y. (2020), A spatial correlation model for broadband surface noise, The Journal of the Acoustical Society of America, 147(2): EL99–EL105, doi: 10.1121/10.0000710.
18. Rudnicki M., Marszal J., Salamon R. (2020), Impact of spatial noise correlation on bearing accuracy in DIFAR systems, Archives of Acoustics, 45(4): 709–720, doi: 10.24425/aoa.2020.135277.
19. Salamon R. (2006), Sonar systems [in Polish], Gdanskie Towarzystwo Naukowe, Gdansk, Poland.
20. Schmidt J.H., Schmidt A., Kochanska I. (2018), Multiple-Input Multiple-Output Technique for Underwater Acoustic Communication System, [In:] Proceedings of 2018 Joint Conference – Acoustics, Ustka, Poland, 2018, IEEE Xplore Digital Library, pp. 280– 283, doi: 10.1109/acoustics.2018.8502439.
21. Urick R.J. (1983), Principles of Underwater Sound, 3rd ed., Peninsula Pub.
22. Urick R.J. (1986), Ambient Noise in the Sea, 2nd ed., Peninsula Pub.
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Authors and Affiliations

Mariusz Rudnicki
1
Roman Salamon
1
Jacek Marszal
1

  1. Gdansk University of Technology, Faculty of Electronics, Telecommunications and Informatics, Department of Sonar Systems, Gdansk, Poland
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Abstract

It is well known that nonlinear ultrasound is sensitive to some microstructural characteristics in material. This paper investigates the dependence of the nonlinear ultrasonic characteristic on Al-Cu precipitation in heat-treated 2219-T6 aluminum alloy specimens. The specimens were heat-treated at a constant temperature 155℃ for different exposure times up to 1800 min. The nonlinearity parameter and the changes of precipitates phase were measured for each of the artificially aged specimens. The experimental results show fluctuations in the fractional change in nonlinear parameter (Δβ/β0) and the changes of precipitated phase over the aging time, but with an interesting correlation between the fractional change in nonlinear parameter (Δβ/β0) and the change of precipitate phase over the aging time. Through the experimental data results, the fractional change in nonlinear parameter (Δβ/β0) and the change of precipitate phase over the aging time were fitted curve. Microstructural observations confirmed that those fluctuations are due to the formation and evolution of precipitates that occur in a unique precipitation sequence in this alloy. These results suggest that the nonlinear ultrasonic measurement can be useful for monitoring second phase precipitation in the 2219-T6 aluminum alloy.
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Bibliography

1. Balasubramaniam K., Valluri J.S., Prakash R.V. (2011), Creep damage characterization using a low amplitude nonlinear ultrasonic technique, Materials Characterization, 62(3): 275–286, doi: 10.1016/j.matchar.2010.11.007.
2. Benal M.M., Shivanand H.K. (2007), Effects of reinforcements content and ageing durations on wear characteristics of Al (6061) based hybrid composites, Wear, 262(5–6): 759–763, doi: 10.1016/j.wear.2006.08.022.
3. Buha J., C R.N., Crosky A.G., Hono K. (2007), Secondary precipitation in an Al-Mg-Si-Cu alloy, Acta Materialia, 55(9): 3015–3024, doi: 10.1016/j.actamat.2007.01.006.
4. Cantrell J.H., Yost W.T. (1997), Effect of precipitate coherency strains on acoustic harmonic generation, Journal of Applied Physics, 81(7): 2957–2962, doi: 10.1063/1.364327.
5. Cantrell J.H., Yost W.T. (2000), Determination of precipitate nucleation and growth rates from ultrasonic harmonic generation, Applied Physics Letters, 77(13): 1952–1954, doi: 10.1063/1.1311951.
6. Cantrell J.H., Zhang X.G. (1998), Nonlinear acoustic response from precipitate-matrix misfit in a dislocation network, Journal of Applied Physics, 84(10): 5469–5472, doi: 10.1063/1.368309.
7. Dace G.E., Thompson R.B., Brasche L.J.H., Rehbein D.K., Buck O. (1991), Nonlinear acoustics, a technique to determine microstructural changes in materials, [in:] Review of Progress in Quantitative Nondestructive Evaluation, Thompson D.O., Chimenti D.E. [Eds], Vol. 10B, pp. 1685–1692, Springer, Boston, MA, doi: 10.1007/978-1-4615-3742-7_71.
8. Demir H., Gündüz S. (2009), The effects of aging on machinability of 6061 aluminium alloy, Materials & Design, 30(5): 1480–1483, doi: 10.1016/j.matdes.2008.08.007.
9. Edwards G.A., Stiller K., Dunlop G.L., Couper M.J. (1998), The precipitation sequence in Al-Mg-Si alloys, Acta Materialia, 46(11): 3893–3904, doi: 10.1016/S1359-6454(98)00059-7.
10. Fang X., Song M., Li K., Du Y. (2010), Precipitation sequence of an aged Al-Mg-Si alloy, Journal of Mining and Metallurgy B: Metallurgy, 46(2): 171–180, doi: 10.2298/JMMB1002171F.
11. Granato A., Lüke K. (1956), Theory of mechanical damping due to dislocations, Journal of Applied Physics, 27(6): 583–593, doi: 10.1063/1.1722436.
12. Hikata A., Chick B.B., Elbaum C. (1965), Dislocation contribution to the second harmonic generation of ultrasonic waves, Journal of Applied Physics, 36(1): 229–236, doi: 10.1063/1.1713881.
13. Kim C.S., Jhang K.Y. (2012), Fatigue-induced micro-damage characterization of austenitic stainless steel 316 using innovative nonlinear acoustics, Chinese Physics Letters, 29(6): 060702, doi: 10.1088/0256-307x/29/6/060702.
14. Kim J., Jhang K.Y. (2013), Evaluation of ultrasonic nonlinear characteristics in heat-treated aluminum alloy (Al-Mg-Si-Cu), Advances in Materials Science and Engineering, 2013: Article ID 407846, doi: 10.1155/2013/407846.
15. Kim J., Song D.G., Jhang K.Y. (2016), Absolute measurement and relative measurement of ultrasonic nonlinear parameters, Research in Nondestructive Evaluation, 28(4): 211–225 doi: 10.1080/09349847.2016.1174322.
16. Li P., Yost W.T., Cantrell J.H., Salama K. (1985), Dependence of acoustic nonlinearity parameter on second phase precipitates of aluminum alloys, IEEE 1985 Ultrasonics Symposium, pp. 1113–1115, doi: 10.1109/ULTS-YM.1985.198690.
17. Metya A., Ghosh M., Parida N., Sagar S.P. (2008), Higher harmonic analysis of ultrasonic signal for ageing behaviour study of C-250 grade maraging steel, NDT & E International, 41(6): 484–489, doi: 10.1016/j.ndteint.2008.01.008.
18. Miao W.F., Laughlin D.E. (1999), Precipitation hardening in aluminum alloy 6022, Scripta Materialia, 40(7): 873–878, doi: 10.1016/S1359-6462(99)00046-9.
19. Mondal C., Mukhopadhyay A., Sarkar R. (2010), A study on precipitation characteristics induced str- ength variation by nonlinear ultrasonic parameter, Journal of Applied Physics, 108(12): 124910, doi: 10.1063/1.3524526.
20. Ozturk F., Sisman A., Toros S., Kilic S., Picu R.C. (2010), Influence of aging treatment on mechanical properties of 6061 aluminum alloy, Materials & Design, 31(2): 972–975, doi: 10.1016/j.matdes.2009.08.017.
21. Park J., Kim M., Chi B., Jang C. (2013), Corre- lation of metallurgical analysis & higher harmonic ul- trasound response for long term isothermally aged and crept FM steel for USC TPP turbine rotors, NDT & E International, 54: 159–165, doi: 10.1016/j.ndteint.2012.10.008.
22. Rajasekaran S., Udayashankar N.K., Nayak J. (2012), T4 and T6 treatment of 6061 Al-15 Vol.% SiCP composite, ISRN Materials Science, 2012: 1–5, doi: 10.5402/2012/374719.
23. Ren G., Kim J., Jhang K.Y. (2015), Relationship between second- and third-order acoustic nonlinear parameters in relative measurement, Ultrasonics, 56: 539–544, doi: 10.1016/j.ultras.2014.10.009.
24. Siddiqui R.A., Abdullah H.A., Al-Belushi K.R. (2000), Influence of aging parameters on the mechani- cal properties of 6063 aluminium alloy, Journal of Materials Processing Technology, 102(1–3): 234–240, doi: 10.1016/S0924-0136(99)00476-8.
25. Troeger L.P., Starke, Jr E.A. (2000), Microstructural and mechanical characterization of a superplas- tic 6xxx aluminum alloy, Materials Science and Engineering: A, 277(1–2): 102–113, doi: 10.1016/S0921-5093(99)00543-2.
26. Viswanath A., Rao B.P.C., Mahadevan S., Parameswaran P., Jayakumar T., Raj B. (2011), Nondestructive assessment of tensile properties of cold worked AISI type 304 stainless steel using nonlin- ear ultrasonic technique, Journal of Materials Processing Technology, 211(3): 538–544, doi: 10.1016/j.jmatprotec.2010.11.011.
27. Xiang Y., Deng M., Xuan F.Z. (2014), Thermal degradation evaluation of HP40Nb alloy steel after long term service using a nonlinear ultrasonic technique, Journal of Nondestructive Evaluation, 33: 279– 287, doi: 10.1007/s10921-013-0222-8.
28. Yassar R.S., Field D.P., Weiland H. (2011), Transmission electron microscopy and differential scan- ning calorimetry studies on the precipitation sequence in an Al-Mg-Si alloy: AA6022, Journal of Materials Research, 20(10): 2705–2711, doi: 10.1557/JMR.2005.0330.
29. You J., Wu Y.X., Gong H., Ahmad A.S, Lei Y. (2019), Determination of the influence of post – heat treatment on second-phase of Al 2219-T6 alloy using ultrasonic non-linear measurement technique, Insight – Non-Destructive Testing and Condition Monitoring, 61(4): 209–213, doi: 10.1784/insi.2019.61.4.209.
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Authors and Affiliations

Jun You
1 2 3
Yunxin Wu
1 4 2 3
Hai Gong
1 4 2 3

  1. Research Institute of Light Alloys, Central South University, Changsha, 410083, China
  2. Nonferrous Metal Oriented Advanced Structural Material and Manufacturing Cooperative Innovation Center, Central South University, Changsha, 410083, China
  3. State Key Laboratory of High-Performance Complex Manufacturing, Central South University, Changsha, 410083, China
  4. School of Mechanical and Electrical Engineering, Central South University, Changsha, 410083, China
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Abstract

Microphone array with minimum variance (MVDR) beamformer is a commonly used method for ambient noise suppression. Unfortunately, the performance of the MVDR beamformer is poor in a real reverberant room due to multipath wave propagation. To overcome this problem, we propose three improvements. Firstly, we propose end-fire microphone array that has been shown to have a better directivity index than the corresponding broadside microphone array. Secondly, we propose the use of unidirectional microphones instead of omnidirectional ones. Thirdly, we propose an adaptation of its adaptive algorithm during the pause of speech, which improves its robustness against the room reverberation and deviation from the optimal receiving direction. The performance of the proposed microphone array was theoretically analyzed using a diffuse noise model. Simulation analysis was performed for combined diffuse and coherent noise using the image model of the reverberant room. Real room tests were conducted using a four-microphone array placed in a small office room. The theoretical analysis and the real room tests showed that the proposed solution considerably improves speech quality.
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Authors and Affiliations

Zoran Šarić
1
ORCID: ORCID
Miško Subotić
1
Ružica Bilibajkić
1
Marko Barjaktarović
2
Nebojša Zdravković
3

  1. Laboratory of Acoustics, Life Activities Advancement Center, Serbia
  2. Faculty of Electrical Engineering, University of Belgrade, Serbia
  3. Faculty of Medical Sciences, University of Kragujevac, Serbia
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Abstract

In this paper, we investigate a problem on reflection and transmission of plane-waves at an interface between two dissimilar half-spaces of a transversely isotropic micropolar piezoelectric material. The entire model is assumed to rotate with a uniform angular velocity. The governing equations of rotating and transversely isotropic micropolar piezoelectric medium are specialized in a plane. Plane-wave solutions of two-dimensional coupled governing equations show the possible propagation of three coupled plane-waves. For an incident plane-wave at an interface between two dissimilar half-spaces, three reflected and three transmitted waves propagate with distinct speeds. The connections between the amplitude ratios of reflected and transmitted waves are obtained. The expressions for the energy ratios of reflected and transmitted waves are also obtained. A numerical example of the present model is considered to illustrate the effects of rotation on the speeds and energy ratios graphically.
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Authors and Affiliations

Baljeet Singh
1
Asha Sangwan
2
Jagdish Singh
3

  1. Department of Mathematics, Post Graduate Government College, Sector 11, Chandigarh, 160011, India
  2. Department of Mathematics, Government College, Sampla, Rohtak, 124001, Haryana, India
  3. Department of Mathematics, Maharshi Dayanand University, Rohtak, 124001, Haryana, India
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Abstract

The problem of reducing noise in transportation is an important research field to prevent accidents and to provide a civilised environment for people. A material that has recently attracted attention in research to reduce noise is acoustic metamaterial, and most of the research projects so far have been limited to the case of static media without flow. We have studied the sound transmission properties of the acoustic metamaterials with turbulent flow to develop the acoustic metamaterials that are used in transportation. In this paper, the effects of geometrical structure, convection, and eddy on sound propagation in the acoustic metamaterials with turbulent flow are investigated, and the relationships between them are analysed. The effects of convection and eddy reduce the resonant strength of the sound transmission loss resulting from the unique geometry of the acoustic metamaterials, but move the resonant frequencies to opposite directions. In addition, when the convective effect and the eddy effect of the airflow, as well as the intrinsic interaction effect generated from the unique geometrical structure of the acoustic metamaterials cannot be ignored, they exhibit competition phenomena with each other, resulting in a widening of the resonance peak. As a result, these three effects cause the shift of the resonance frequency of the sound transmission loss and the widening of the resonance peak. The results of this study show that even in the case of turbulent flow, the metamaterials can be used for transportation by properly controlling its geometric size and shape.
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Bibliography

1. Ananthan V., Bernicke P., Akkermans R., Hu T., Liu P. (2020), Effect of porous material on trailing edge sound sources of a lifting airfoil by zonal oversetles, Journal of Sound and Vibration, 480: 115386, doi: 10.1016/j.jsv.2020.115386.
2. Bok E., Park J.J., Choi H., Han C.K., Wright O.B., Lee S.H. (2018), Metasurface for water-to-air sound transmission, Physical Review Letters, 120(4): 044302, doi: 10.1103/PhysRevLett.120.044302.
3. Brookea D.C., Umnova O., Leclaire P., Dupont T. (2020), Acoustic metamaterial for low frequency sound absorption in linear and nonlinear regimes, Journal of Sound and Vibration, 485: 115585, doi: 10.1016/j.jsv.2020.115585.
4. Carpio A.R., Avallone F., Ragni D., Snellen M., van der Zwaag S. (2019), Mechanisms of broadband noise generation on metal foam edges, Physics of Fluids, 31(10): 105110, doi: 10.1063/1.5121248.
5. Chaitanya P., Joseph P., Ayton L.J. (2020), Leading edge profiles for the reduction of airfoil interaction noise, AIAA Journal, 58(3): 1118–1129, doi: 10.2514/1.J058456.
6. Deuse M., Sandberg R.D. (2020), Different noise generation mechanisms of a controlled diffusion aerofoil and their dependence on Mach number, Journal of Sound and Vibration, 476: 115317, doi: 10.1016/j.jsv.2020.115317.
7. Du L., Holmberg A., Karlsson M., Åbom M. (2016), Sound amplification at a rectangular t-junction with merging mean flows, Journal of Sound and Vibration, 367: 69–83, doi: 10.1016/j.jsv.2015.12.042.
8. Fan L., Chen Z., Zhang S., Ding J., Li X., Zhang H. (2015), An acoustic metamaterial composed of multi-layer membrane-coated perforated plates for low-frequency sound insulation, Applied Physics Letters, 106(15): 151908, doi: 10.1063/1.4918374.
9. Gikadi J., Föller S., Sattelmayer T. (2014), Impact of turbulence on the prediction of linear aeroacoustic interactions: Acoustic response of a turbulent shear layer, Journal of Sound and Vibration, 333(24): 6548–6559, doi: 10.1016/j.jsv.2014.06.033.
10. Gu Z., Gao H., Liu T., Li Y., Zhu J. (2020), Dopant-modulated sound transmission with zero index acoustic metamaterials, The Journal of the Acoustical Society of America, 148(3): 1636–1641, doi: 10.1121/10.0001962.
11. Jiang X., Li Y., Zhang L.K. (2017), Thermoviscous effects on sound transmission through a metasurface of hybrid resonances, The Journal of the Acoustical Society of America, 141(4): EL363–EL368, doi: 10.1121/1.4979682.
12. Jung J.W., Kim J.E., Lee J.W. (2018), Acoustic metamaterial panel for both uid passage and broadband soundproofing in the audible frequency range, Applied Physics Letters, 112(4): 041903, doi: 10.1063/1.5004605.
13. Kundu P.K., Cohen I.M., Dowling D. (2012), Fluid mechanics, 5th ed., pp. 564–571, Elsevier, doi: 10.1016/C2009-0-63410-3.
14. Kusano K., Yamada K., Furukawa M. (2020), Aeroacoustic simulation of broadband sound generated from low-Mach-number flows using a lattice Boltzmann method, Journal of Sound and Vibration, 467: 115044, doi: 10.1016/j.jsv.2019.115044.
15. Li Y., Assouar B.M. (2016), Acoustic metasurfacebased perfect absorber with deep subwavelength thickness, Applied Physics Letters, 108(6): 063502, doi: 10.1063/1.4941338.
16. Lu K., Wu J., Guan D., Gao N., Jing L. (2016), A lightweight low-frequency sound insulation membrane- type acoustic metamaterial, AIP Advances, 6(2): 025116, doi: 10.1063/1.4942513.
17. Menter F. (1994), Two-equation eddy-viscosity turbulence models for engineering applications, AIAA Journal, 32(8): 1598–1605, doi: 10.2514/3.12149.
18. Nardini M., Sandberg R.D., Schlanderer S.C. (2020), Computational study of the effect of structural compliance on the noise radiated from an elastic trailing-edge, Journal of Sound and Vibration, 485: 115533, doi: 10.1016/j.jsv.2020.115533.
19. Ostashev V.E., Wilson D.K. (2016), Acoustics in Moving Inhomogeneous Media, 2ed., pp. 27–62, Taylor and Francis, doi: 10.1201/b18922.
20. Park J.J., Park C.M., Lee K.J., Lee S.H. (2015), Acoustic superlens using membrane-based metamaterials, Applied Physics Letters, 106(5): 051901, doi: 10.1063/1.4907634.
21. Pierce A.D. (2019), Acoustics: An Introduction to Its Physical Principles and Applications, 3rd ed., pp. 68– 70, Springer, doi: 10.1007/978-3-030-11214-1.
22. Qu S., Sheng P. (2020), Minimizing indoor sound energy with tunable metamaterial surfaces, Physical Review Applied, 14(3): 034060, doi: 10.1103/PhysRevApplied.14.034060.
23. Romani G., Ye Q.Q., Avallone F., Ragni D., Casalino D. (2020), Numerical analysis of fan noise for the NOVA boundary-layer ingestion configuration, Aerospace Science and Technology, 96: 105532, doi: 10.1016/j.ast.2019.105532.
24. Su H., Zhou X., Xu X., Hu G. (2014), Experimental study on acoustic subwavelength imaging of holeystructured metamaterials by resonant tunnelling, The Journal of the Acoustical Society of America, 135(4): 1686–1691, doi: 10.1121/1.4868395.
25. Sui N., Yan X., Huang T.Y., Xu J., Yuan F.G., Jing Y. (2015), A lightweight yet sound-proof honeycomb acoustic metamaterial, Applied Physics Letters, 106(17): 171905, doi: 10.1063/1.4919235.
26. Szoke M., Fiscaletti D., Azarpeyvand M. (2018), Effect of inclined transverse jets on trailing-edge noise generation, Physics of Fluids, 30(8): 085110, doi: 10.1063/1.5044380.
27. Szoke M., Fiscaletti D., Azarpeyvand M. (2020), Uniform flow injection into a turbulent boundary layer for trailing edge noise reduction, Physics of Fluids, 32(8): 085104, doi: 10.1063/5.0013461.
28. Tang H., Lei Y.L., Li X.Z. (2019), An acoustic source model for applications in low Mach number turbulent flows, such as a large-scale wind turbine blade, Energies, 12(23): 4596, doi: 10.3390/en12234596.
29. Wang X., Zhao H., Luo X., Huang Z. (2016), Membrane-constrained acoustic metamaterials for low frequency sound insulation, Applied Physics Letters, 108(4): 041905, doi: 10.1063/1.4940717.
30. Wang Y., Thompson D., Hu Z. (2019), Effect of wall proximity on the flow over a cube and the implications for the noise emitted, Physics of Fluids, 31(7): 077101, doi: 10.1063/1.5096072.
31. Yang Z.J. et al. (2015), Topological acoustics, Physical Review Letters, 114(11): 114301, doi: 10.1103/Phys RevLett.114.114301.
32. Yao H., Davidson L. (2019), Vibro-acoustics response of a simplified glass window excited by the turbulent wake of a quarter-spherocylinder body, The Journal of the Acoustical Society of America, 145(5): 3163–3176, doi: 10.1121/1.5109548.
33. Zheng M.Y., Park C., Liu X.N., Zhu R., Hu G.K., Kim Y.Y. (2020), Non-resonant metasurface for broadband elastic wave mode splitting, Applied Physics Letters, 116(17): 171903, doi: 10.1063/5.0005408.
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Authors and Affiliations

Myong Chol Pak
1
Kwang-Il Kim
1
Hak Chol Pak
1
Kwon Ryong Hong
2

  1. Department of Physics, Kim Il Sung University, Taesong District, Pyongyang, Democratic People’s Republic of Korea
  2. Institute of Natural Sciences, Kim Il Sung University, Taesong District, Pyongyang, Democratic People’s Republic of Korea
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Abstract

Numerical models allow structural characteristics to be obtained by solving mathematical formulations. The sound absorption capacity of a material can be acquired by numerically simulating an impedance tube and using the method governed by ISO 10534-2. This study presents a procedure of obtaining sound pressure using two microphones and as outline condition, at one end of the tube, the impedance of fiber samples extracted from the pseudostem of banana plants. The numerical methodology was conducted in the ANSYS® Workbench software. The sound absorption coefficient was obtained in the MATLAB® software using as input data the sound pressure captured in the microphones and applying the mathematical formulations exposed in this study. For the validation of the numerical model, the results were compared with the sound absorption coefficients of the fiber sample collected from an experimental procedure and also with the results of a microperforated panel developed by Maa (1998). According to the results, the methodology presented in this study showed effective results, since the largest absolute and relative errors were 0.001 and 3.162%, respectively.
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Bibliography

1. ASTM E1050:2019, Standard test method for impedance and absorption of acoustical materials using a tube, two microphones and a digital frequency analysis system.
2. ASTM E354:2003, Acoustics – measurement of sound absorption in a reverberation room.
3. Bóden H., Abom M. (1986), Influence of errors on the two-microphone method for measuring acoustic properties in ducts, The Journal of the Acoustical Society of America, 79(2): 541–549, doi: 10.1121/1.393542.
4. Ming-hui G., Qing-quan H., Jin-man W., Haipeng Y. (2010), The modeling and simulation analysis of wooden perforated panel absorption structure, Noise & Vibration Wordwide, 41(10): 72–75, doi: 10.1260/0957-4565.41.10.72.
5. Howard C.Q., Cazzolato B.S. (2014), Acoustic Analyses using MATLAB® and ANSYS®, Boca Raton: CRC Press, Taylor & Francis Group.
6. ISO 10534-1:1996, Acoustic – Determination of sound absorption coefficient and impedance in impedance tubes – Part 1: Method using standing wave ratio.
7. ISO 10534-2:1998, Acoustics – Determination of sound absorption coefficient and impedance in impedance tubes. Part 2: Transfer-function method.
8. ISO 354:2003, Measurement of sound absorption in a reverberant room.
9. Kinsler L.E., Frey A.R., Coppens A.B., Sanders J.V. (2000), Fundamentals of Acoustics, Hoboken: John Wiley & Sons, New York.
10. Lara L.T., Boaventura W.C., Pasqual A.M. (2016), Improving the estimated acoustic absorption curves in impedance tubes by using wavelet-based denoising methods, Congresso Iberoamericano de Acústica, Buenos Aires, Argentina, 22, 1–10.
11. Maa D.Y. (1998), Potential of microperforated panel absorber, The Journal of the Acoustical Society of America, 104(5): 2861–2866, doi: 10.1121/1.423870.
12. Rienstra S.W., Hirschberg A. (2014), An Introduction to Acoustics, Eindhoven University of Technology, Netherlands.
13. Silva G.C.C., Nunes M.A.A., Almeida Jr A.B., Lopes R.V. (2013), Acoustic design and construction of an impedance tube for experimental characterization of sound absorbed materials [in Portuguese: Projeto Acústico e Construção de um Tubo de Impedância para Caracterização Experimental de Materiais com Absorção Sonora], [in:] XVIII Congresso de Iniciação Científica da UnB, Brasília, Brazil.
14. Soriano H.L. (2009), Finite Elements – Formulation and Application in Static and Dynamic Structures [in Portuguese: Elementos Finitos – Formulação e Aplicação na Estática e Dinâmica das Estruturas], Rio de Janeiro: Editora Ciência Moderna Ltda.
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Authors and Affiliations

Cláudia Ohana Borges Mendes
1
Maria Alzira De Araújo Nunes
1

  1. Graduate Program in Engineering Materials Integrity, University of Brasília-UnB, College UnB Gama-FGA Área Especial de Indústria Projeção A, Setor Leste, CEP:72.444-240, Gama, Distrito Federal, Brazil
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Abstract

Lined ducts with porous materials are found in many industrial applications. To understand and simulate the acoustic behaviour of these kinds of materials, their intrinsic physical parameters must be identified. Recent studies have shown the reliability of the inverse approach for the determination of these parameters. Therefore, in the present paper, two inverse techniques are proposed: the first is the multilevel identification method based on the simplex optimisation algorithm and the second one is based on the genetic algorithm. These methods are used of the physical parameters of a simulated case of a porous material located in a duct by the computation of its acoustic transfer, scattering, and power attenuation. The results obtained by these methods are compared and discussed to choose the more efficient one.
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Bibliography

1. Alba J., delRey R., Ramis J., Arenas J.P. (2011), An inverse method to obtain porosity, fiber diameter and density of fibrous sound absorbing materials, Archives of Acoustics, 36(3): 561–574, doi: 10.2478/v10168-011-0040-x.
2. Allard J.F., Attalla N. (2009), Propagation of Sound in Porous Media, Wiley.
3. Allard J.F., Champoux Y. (1992), New empirical equations for sound propagation in rigid frame fibrous materials, The Journal of the Acoustical Society of America, 91(6): 3346–3353, doi: 10.1121/1.402824.
4. Attalla Y., Panneton R. (2005), Inverse acoustical characterization of open cell porous media using impedance tube measurements, Canadian Acoustics, 33(1): 11–24.
5. Attenborough K. (1983), Acoustical characteristics of rigid porous absorbents and granular materials, The Journal of the Acoustical Society of America, 73(3): 85–99, doi: 10.1121/1.389045.
6. Attenborough K. (1987), On the acoustic slow wave in air-filled granular media, The Journal of the Acoustical Society of America, 81(1): 93–102, doi: 10.1121/1.394938.
7. Benjdidia M., Akrout A., Taktak M., Hammami L., Haddar M. (2014), Thermal effect on the acoustic behavior of an axisymmetric lined duct, Applied Acoustics, 86: 138–145, doi: 10.1016/j.apacoust.2014.03.004.
8. Ben Souf M.A., Kessentini A., Bareille O., Taktak M., Ichchou M.N., Haddar M. (2017), Acoustical scattering identification with local impedance through a spectral approach, Compte Rendus Mécanique, 345(5): 301–316, doi: 10.1016/j.crme.2017.03.006.
9. Bérengier M., Stinson M.R., Daigle G.A., Hamet J.F. (1997), Porous road pavements: acoustical characterization and propagation effects, The Journal of the Acoustical Society of America, 101(1): 155–162, doi: 10.1121/1.417998.
10. Chazot J.D., Zhang E., Antoni J. (2012), Characterization of poroelastic materials with a Bayesian approach, The Journal of the Acoustical Society of America, 131(6): 4584–4595, doi: 10.1121/1.3699236.
11. Delany M.E., Bazley E.N. (1970), Acoustical properieties of fibrous absorbent materials, Applied Acoustics, 3: 105–116, doi: 10.1016/0003-682X(70)90031-9.
12. Dhief R., Makni A., Taktak M., Chaabane M., Haddar M. (2020), Investigation on the effects of acoustic liner variation and geometry discontinuities on the acoustic performance of lined ducts, Archives of Acoustics, 45(1): 49–66, doi: 10.24425/aoa.2020.132481.
13. Garoum M., Simon F. (2005), Characterization of non-consolidated cork crumbs as a basic sound absorber raw material, [in:] 12th International Congress on Sound and Vibration, Lisbon, Portugal.
14. Garoum M., Tajayouti M. (2007), Inverse estimation of non acoustical parameters of absorbing materials using genetic algorithms, [in:] 19th International Congress on Acoustics, Madrid, Spain.
15. Goldberg D. (1989), Genetic Algorithms for Search, Optimization and Machine Learning, Addison-Wesley, Reading. 16. Hamet J.F., Bérengier M. (1993), Acoustical characteristics of porous pavements – a new phenomenological model, [in:] Inter-Noise ‘93, Leuven, Belgium.
17. Hentati T., Bouazizi L., Taktak M., Trabelsi H., Haddar M. (2016), Multi-levels inverse identification of physical parameters of porous materials, Applied Acoustics, 108: 26–30, doi: 10.1016/j.apacoust.2015.09.013.
18. Hess H.M., Attenborough K., Heap N.W. (1990), Ground characterization by short-range propagation measurements, The Journal of the Acoustical Society of America, 87(5): 1975–1986, doi: 10.1121/1.399325.
19. Johnson D.L., Koplik J., Dashen R. (1987), Theory of dynamic permeability and tortuosity in fluidsaturated porous media, Journal of Fluid Mechanics, 176: 379–402, doi: 10.1017/S0022112087000727.
20. Kani M. et al. (2019), Acoustic performance evaluation for ducts containing porous material, Applied Acoustics, 147: 15–22, doi: 10.1016/j.apacoust.2018.08.002.
21. Kessentini A.,Taktak M., Ben Souf M.A., Bareille O., Ichchou M.N., Haddar M. (2016), Computation of the scattering matrix of guided acoustical propagation by the Wave Finite Elements approach, Applied Acoustics, 108: 92–100, doi: 10.1016/j.apacoust.2015.09.004.
22. Lafarge D., Lemarinier P., Allard J.F. (1997), Dynamic compressibility of air in porous structures at audible frequencies, The Journal of the Acoustical Society of America, 102(4): 1995–2006, doi: 10.1121/1.419690.
23. Lagarias J.C., Reeds J.A., Wright M.H., Wright P.E. (1998), Convergence properties of the Nelder- Mead Simplex method in low dimensions, SIAM Journal of optimization, 9(1): 112–147, doi: 10.1137/S1052623496303470.
24. Leclaire P., Kelders L., Lauriks W., Melon M., Brown N., Castagnède B. (1996), Determination of the viscous and thermal characteristic lengths of plastic foams by ultrasonic measurements in helium and air, Journal of Applied Physics, 80(4): 2009–2012, doi: 10.1063/1.363817.
25. Mareze P.H., Lenzi A. (2011), Characterization and optimization of rigid – frame porous material, [in:] 18th International Congress on Sound and Vibration, Rio De Janeiro, Brazil.
26. Masmoudi A., Makni A., Taktak M., Haddar M. (2017), Effect of geometry and impedance variation on the acoustic performance of a porous material lined duct, Journal of Theoretical and Applied Mechanics, 55(2): 679–694, doi: 10.15632/jtam-pl.55.2.679.
27. Miki Y. (1990), Acoustical properties of porous materials – modifications of Delany-Bazley models, Journal of the Acoustical Society of Japan, 11(1): 19–24, doi: 10.1250/ast.11.19.
28. Othmani C., Hentati T., Taktak M., Elnady T., Fakhfakh T., Haddar M. (2015), Effect of liner characteristics on the acoustic performance of duct systems, Archives of Acoustics, 40(1): 117–127, doi: 10.1515/aoa-2015-0014.
29. Panneton R., Olny X. (2006), Acoustical determination of the parameters governing viscous dissipation in porous media, The Journal of the Acoustical Society of America, 119(4): 2027–2040, doi: 10.1121/1.2169923.
30. Sellen N., Galland M.A., Hilberunner O. (2020), Identification of the characteristic parameters of porous media using active control, [in:] 8th AIAA/CEAS Aeroacoustics Conference, USA.
31. Shravage P., Bonfiglio P., Pompoli F. (2008), Hybrid inversion technique for predicting geometrical parameters of porous materials, [in:] Acoustics’ 08, Paris, France, pp. 2545–2549.
32. Taktak M., Ville J.M., Haddar M., Gabard G., Foucart F. (2010), An indirect method for the characterization of locally reacting liners, The Journal of the Acoustical Society of America, 127(6): 3548–3559, doi: 10.1121/1.3365250.
33. Ying H. (2010), Development of passive/active hybrid panels for acoustics [in French: Développement de panneaux hybrides passifs/actifs pour l’acoustique], Phd Thesis, Ecole Centrale de Lyon.
34. Zielinski T.G. (2012), Inverse identification and microscopic estimation of parameters for models of sound absorption in porous ceramics, [in:] International Conference on Noise and Vibration Engineering/International Conference on Uncertainty in Structural Dynamics, 17–19 September, Leuven, Belgium.
35. Zielinski T.G. (2014), A methodology for a robust inverse identification of model parameters for porous sound absorbing materials, [in:] International Conference on Noise and Vibration Engineering/International Conference on Uncertainty in Structural Dynamics, 15–17 September, Leuven, Belgium.
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Authors and Affiliations

Kani Marwa
1 2
Amine Makni
1
Mohamed Taktak
1 2
Mabrouk Chaabane
2
Mohamed Haddar
1

  1. Laboratory of Mechanics, Modeling and Productivity (LA2MP), National School of Engineers of Sfax, University of Sfax, Tunisia
  2. Faculty of Sciences of Sfax, University of Sfax, Tunisia
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Abstract

The aim of the paper is to experimentally determine the scattering matrix S of an example reflective muffler of cylindrical geometry for Helmholtz number exceeding the plane wave propagation. Determining the scattering matrix of an acoustic systems is a new and increasingly used approach in the assessment of reduction of noise propagating inside duct-like elements of heating, ventilation and air conditioning systems (HVAC). The scattering matrix of an acoustic system provides all necessary information on the propagation of wave through it. In case of the analysed reflective silencer, considered as a two-port system, the noise reduction was determined by calculating the transmission loss parameter (TL) based on the scattering matrix (S). Measurements were carried out in two planes of the cross-section of pipes connected to the muffler.

The paper presents results of the scattering matrix evaluation for the wave composed of the plane wave (mode (0,0)) and the first radial mode (0,1), each of which was generated separately using the self-designed and constructed single-mode generator. The gain of proceeding measurements for single modes stems from the fact that theoretically, calculation of the S-matrix does not require, as will be presented in the paper, calculation of the measurement data inverse matrix. Moreover, if single mode sound fields are well determined, it ensures error minimization. The presented measurement results refer to an example of a duct like system with a reflective muffler for which the scattering matrix S was determined. The acoustic phenomena inside such a system can be scaled by the parameter ka.
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Bibliography

1. Åbom M. (1991), Measurement of the scatteringmatrix of acoustical two-ports, Mechanical System and Signal Processing, 5(2): 89–104, doi: 10.1016/0888- 3270(91)90017-Y.
2. Åbom M., Karlsson M. (2010), Can acoustic multiport models be used to predict whistling, 16th AIAA/ CEAS Aeroacoustics Conference, 5: 4285–4292.
3. Atig M., Dalmont J.P., Gilbert J. (2004), Termination of open-end cylindrical tubes at high sound pressure level, Computes Rendus Mecanique, 332(4): 299– 304, doi: 10.1016/j.crme.2004.02.008.
4. Auger J.M., Ville J.M. (1990), Measurement of linear impedance based on the determination of duct eigenvalues by a Fourier-Lommel’s transform, The Journal of the Acoustical Society of America, 88(1): 19–22, doi: 10.1121/1.399942.
5. Auregan Y., Farooqui M., Groby J.P. (2016), Low frequency sound attenuation in a flow duct using a thin slow sound material, The Journal of the Acoustical Society of America, 139(5): 149–153, doi: 10.1121/ 1.4951028.
6. Chen X.X., Zhang X., Morfey C.L., Nelson P.A. (2004), A numerical method for computation of sound radiation from an unflanged duct, Journal of Sound and Vibration, 270(3): 573–586, doi: 10.1016/ j.jsv.2003.09.055.
7. Dalmont J.P., Nederveen C.J., Joly N. (2001), Radiation impedance of tubes with different flanges: numerical and experimental investigations, Journal of Sound and Vibration, 244(3): 505–534, doi: 10.1006/ jsvi.2000.3487.
8. Gerges S.N.Y., Jordan R., Thieme F.A., Bento Coelho J.L., Arenas J.P. (2005), Muffler modeling by transfer matrix method and experimental verification, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 27(2): 132–140, doi: 10.1590/S1678-58782005000200005.
9. Hocter S.T. (1999), Exact and approximate directivity patterns of the sound radiated from a cylindrical duct, Journal of Sound and Vibration, 227(2): 397– 407, doi: 10.1006/jsvi.1999.2351.
10. Hocter S.T. (2000), Sound radiated from a cylindrical duct with Keller’s geometrical theory, Journal of Sound and Vibration, 231(5): 1243–1256, doi: 10.1006/jsvi.1999.2739.
11. Joseph P., Morfey C.L. (1999), Multimode radiation from an unflanged, semi-infinite circular duct, The Journal of the Acoustical Society of America, 105(5): 2590–2600, doi: 10.1121/1.426875.
12. Jurkiewicz J., Snakowska A., Gorazd Ł. (2012), Experimental verification of the theoretical model of sound radiation from an unflanged duct with low mean flow, Archives of Acoustics, 37(2): 227–236, doi: 10.2478/v10168-012-0030-7.
13. Lavrentjev J., Abom M., Boden H. (1995), A measurement method for determining the source data of acoustic two-port sources, Journal of Sound and Vibration, 183(3): 517–531, doi: 10.1006/jsvi.1995.0268.
14. Lee J.K., Oh K.S., Lee J.W. (2020), Methods for evaluating in-duct noise attenuation performance in a muffler design problem, Journal of Sound and Vibration, 464: 114982, doi: 10.1016/j.jsv.2019.114982.
15. Lidoine S., Batard H., Troyes S., Delnevo A., Roger M. (2001), Acoustic radiation modelling of aeroengine intake comparison between analytical and numerical methods, 7th AIAA/CEAS Aeroacoustics Conference and Exhibit, Maastricht, doi: 10.2514/ 6.2001-2140.
16. Munjal M.L. (1987), Acoustics of Ducts and Mufflers with Application to Exhaust and Ventilation System Design, New York: John Wiley & Sons.
17. Sack S., Abom M., Efraimsson G. (2016), On acoustic multi-port characterisation including higher order modes, Acta Acustica United with Acustica, 102(5): 834–850, doi: 10.3813/AAA.918998.
18. Selamet A., Dickey N.S., Novak J.M. (1994), The Herschel-Quincke tube: A theoretical, computational, and experimental investigation, The Journal of the Acoustical Society of America, 96(5): 3177–3185, doi: 10.1121/1.411255.
19. Sinayoko S., Joseph P., McAlpine A. (2010), Multimode radiation from an unflanged, semi-infinite circular duct with uniform flow, The Journal of the Acoustical Society of America, 127(4): 2159–2168, doi: 10.1121/1.3327814.
20. Sitel A., Ville J.M., Foucart F. (2006), Multiload procedure to measure the acoustic scattering matrix of a duct discontinuity for higher order mode propagation conditions, The Journal of the Acoustical Society of America, 120(5): 2478–2490, doi: 10.1121/1.2354040.
21. Snakowska A., Gorazd Ł., Jurkiewicz J., Kolber K. (2016), Generation of a single cylindrical duct mode using a mode synthesizer, Applied Acoustics, 114: 56–70, doi: 10.1016/j.apacoust.2016.07.007.
22. Snakowska A., Jurkiewicz J. (2010), Efficiency of energy radiation from an unflanged cylindrical duct in case of multimode excitation, Acta Acustica united with Acustica, 96(3): 416–424, doi: 10.3813/AAA.918294.
23. Snakowska A., Jurkiewicz J. (2021), A new approach to the theory of acoustic multi-port networks with multimode wave and its application to muffler analysis, Journal of Sound and Vibration, 490: 115722, doi: 10.1016/j.jsv.2020.115722.
24. Snakowska A., Jurkiewicz J., Gorazd Ł. (2017), A hybrid method for determination of the acoustic impedance of an unflanged cylindrical duct for multimode wave, Journal of Sound and Vibration, 396: 325–339, doi: 10.1016/j.jsv.2017.02.040.
25. Song B. H., Bolton J.S. (2000), A transfer-matrix approach for estimating the characteristic impedance and wave numbers of limp and rigid porous materials, The Journal of the Acoustical Society of America, 107(3): 1131–1152, doi: 10.1121/1.428404.
26. Su J., Rupp J., Garmory A., Carrotte J.F. (2015), Measurements and computational fluid dynamics predictions of the acoustic impedance of orifices, Journal of Sound and Vibration, 352: 174–191, doi: 10.1016/ j.jsv.2015.05.009.
27. Zorumski W.E. (1973), Generalized radiation impedances and reflection coefficients of circular and annular ducts, The Journal of the Acoustical Society of America, 54(6): 1667–1673, doi: 10.1121/1.1914466.
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Authors and Affiliations

Łukasz Gorazd
1

  1. AGH University of Science and Technology, Faculty of Mechanical Engineering and Robotics, Kraków, Poland
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Abstract

A study was carried to assess the effect of traffic noise pollution on the work efficiency of shopkeepers in Indian urban areas. For this, an extensive literature survey was done on previous research done on similar topics. It was found that personal characteristics, noise levels in an area, working conditions of shopkeepers, type of task they are performing are the most significant factors to study effects on work efficiency. Noise monitoring, as well as a questionnaire survey, was done in Surat city to collect desired data. A total of 17 parameters were considered for assessing work efficiency under the influence of traffic noise. It is recommended that not more than 6 parameters should be considered for ANFIS modeling hence, before opting for the ANFIS modeling, most affecting parameters to work efficiency under the influence of traffic noise, was chosen by Structural Equation Model (SEM). As a result of the SEM model, two ANFIS prediction models were developed to predict the effect on work efficiency under the influence of traffic noise. R squared for model 1, for training data was 0.829 and for testing data, it was 0.727 and R squared for model 2 for training data was 0.828 and for testing data, it was 0.728. These two models can be used satisfactorily for predicting work efficiency under traffic noise environment for open shutter shopkeepers in tier II Indian cities.
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Bibliography

1. Aliabadi M., Golmohammadi R., Khotanlou H., Mansoorizadeh M., Salarpour A. (2015), Artificial neural networks and advanced fuzzy techniques for predicting noise level in the industrial embroidery workrooms, Applied Artificial Intelligence, 29(8): 766–785, doi: 10.1080/08839514.2015.1071090.
2. Azadeh A., Saberi M., Rouzbahman M., Valianpour F. (2015), A neuro-fuzzy algorithm for assessment of health, safety, environment and ergonomics in a large petrochemical plant, Journal of Loss Prevention in the Process Industries, 34: 100–114, doi: 10.1016/j.jlp.2015.01.008.
3. Banerjee D. (2012), Research on road traffic noise and human health in India: review of literature from 1991 to current, Noise & Health, 14(58): 113–118, doi: 10.4103/1463-1741.97255.
4. Bell P. (1980), Effects of heat, noise, and provocation on retaliatory evaluative behavior, Journal of Social Psychology, 110(1): 97–100, doi: 10.1080/00224545.1980.9924227.
5. Central Pollution Control Board, New Delhi, India (2002), Ambient Air Quality Standards in Respect of Noise.
6. Eriksson C., Nilsson M.E., Pershagen G. (2013), Environmental noise and health – Current knowledge and research needs, Swedish Environmetal Protection Agency Report 6553, Stockholm.
7. Ghosh S., Biswas S., Sarkar D., Sarkar P.P. (2014), A novel neuro-fuzzy classification technique for data mining, Egyptian Informatics Journal, 15(3): 129–147, doi: 10.1016/j.eij.2014.08.001.
8. Hancock P.A., Vasmatzidis I. (1998), Human occupational and performance limits under stress: The thermal environment as a prototypical example, Ergonomics, 41(8): 1169–1191, doi: 10.1080/001401398186469.
9. Ivoševic J., Bucak T., Andraši P. (2018), Effects of interior aircraft noise on pilot performance, Applied Acoustics, 139: 8–13, doi: 10.1016/j.apacoust.2018.04.006.
10. Khambete A.K., Christian R.A. (2014), Predicting efficiency of treatment plant by multi parameter aggregated index, Journal of Environmental Research and Development, 8(3): 530–539.
11. Liu W., Zhao T., Zhou W., Tang J. (2018), Safety risk factors of metro tunnel construction in China: An integrated study with EFA and SEM, Safety Science, 105: 98–113, doi: 10.1016/j.ssci.2018.01.009.
12. Mallick Z., Kaleel A.H., Siddiqui A.N. (2009), An expert system for predicting the effects of noise pollution on grass trimming task using fuzzy modeling, International Journal of Applied Environmental Sciences, 4(4): 389–403.
13. Norris M., Lecavalier L. (2010), Evaluating the use of exploratory factor analysis in developmental disability psychological research, Journal of Autism and Developmental Disorders, 40(1): 8–20, doi: 10.1007/ s10803-009-0816-2.
14. Pal D., Bhattacharya D. (2012), Effect of road traffic noise pollution on human work efficiency in government offices, private organizations, and commercial business centres in Agartala City using fuzzy expert system: A case study, Advances in Fuzzy Systems, 2012: Article ID 828593, doi: 10.1155/2012/828593.
15. Quartieri J., Mastorakis N.E., Guarnaccia C., Troisi A., D’Ambrosio S., Iannone G. (2009), Road intersections noise impact on urban environment quality, [in:] Recent Advances in Applied and Theoretical Mechanics. Proceedings of the 5th WSEAS International Conference on Applied and Theoretical Mechanics(MECHANICS’09), Puerto de la Cruz, Tenerife, Spain, pp. 162–171), WSEAS Press.
16. Rashid T. (2012), Fuzzy logic and neuro fuzzy models for direct current motors, International Journal of Engineering Inventions, 1(7): 68–75.
17. Recio A., Linares C., Banegas J.R., Díaz J. (2016), Road traffic noise effects on cardiovascular, respiratory, and metabolic health: An integrative model of biological mechanisms, Environmental Research, 146: 359– 370, doi: 10.1016/j.envres.2015.12.036.
18. Singh R., Ho L.J., Tan H.L., Bell P.A. (2007), Attitudes, personal evaluations, cognitive evaluation and interpersonal attraction: On the direct, indirect and reverse-causal effects, British Journal of Social Psychology, 46: 19–42, doi: 10.1348/014466606X104417.
19. Tandel B., Macwan J.E.M. (2017), Road traffic noise exposure and hearing impairment among traffic policemen in Surat, Western India, Journal of The Institution of Engineers (India), Series A, 98: 101–105, doi: 10.1007/s40030-017-0210-6.
20. Thompson B. (2004), Exploratory and Confirmatory Factor Analysis: Understanding Concepts and Applications, American Psychological Association,Washington DC.
21. Tiwari S., Babbar R., Kaur G. (2018), Performance evaluation of two ANFIS models for predicting water quality index of River Satluj (India), Advances in Civil Engineering, 2018: Article ID 8971079, doi: 10.1155/2018/8971079.
22. Yadav M., Tandel B. (2019), Exposure effect study of traffic noise on roadside shopkeepers in Surat City, Indian Journal of Environmental Protection, 39: 1038– 1045.
23. Yadav M., Tandel B. (2021), Structural equation model-based selection and strength Co-relation of variables for work performance efficiency under traffic noise exposure, Archives of Acoustics, 46(1): 155–166, doi: 10.24425/aoa.2021.136569.
24. Zaheeruddin (2006), Modelling of noise-induced annoyance: a neuro-fuzzy approach, 2006 IEEE International Conference on Industrial Technology, 2006, pp. 2686–2691, doi: 10.1109/ICIT.2006.372676.
25. Zaheeruddin, Garima (2006), A neuro-fuzzy approach for prediction of human work efficiency in noisy environment, Applied Soft Computing, 6(3): 283–294, doi: 10.1016/j.asoc.2005.02.001.
26. Zaheeruddin, Jain V.K. (2008), An expert system for predicting the effects of speech interference due to noise pollution on humans using fuzzy approach, Expert Systems with Applications, 35, 1978–1988, doi: 10.1016/j.eswa.2007.08.104.
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Authors and Affiliations

Manoj Yadav
1
ORCID: ORCID
Bhaven Tandel
1

  1. Civil Engineering Department, S. V. National Institute of Technology, Surat, India
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Abstract

In this paper, a four-pole system matrix for evaluating acoustic performance (STL) is derived using a decoupled numerical method. During the optimization process, a simulated annealing (SA) method, which is a robust scheme utilized to search for the global optimum by imitating a physical annealing process, is used. Prior to dealing with a broadband noise, to recheck the SA method’s reliability, the STL’s maximization relative to a one-tone noise (400Hz) is performed. To assure the accuracy of muffler’s mathematical model, a theoretical analysis of one-diffuser muffler is also confirmed by an experimental data. Subsequently, the optimal results of three kinds of mufflers (muffler A: one diffuser; muffler B: two diffusers; muffler C: three diffusers) have also been compared. Results reveal that the acoustical performance of mufflers will increase when the number of diffusers installed at the muffler inlet increases
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Bibliography

1. Bie D.A., Hansen C.H. (1988), Engineering Noise Control: Theory and Practice, Unwin Hyman, London.
2. Chang Y.C., Yeh L.J., Chiu M.C. (2004), Numerical studies on constrained venting system with side inlet/outlet mufflers by GA optimization, Acta Acustica united with Acustica, 90(6): 1159–1169.
3. Chang Y.C., Yeh L.J., Chiu M.C. (2005a), Shape optimization on double-chamber mufflers using genetic algorithm, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 219(1): 31–42, doi: 10.1243/095440605X8351.
4. Chang Y.C., Yeh L.J., Chiu M.C., Lai G.J. (2005b), Shape optimization on constrained singlelayer sound absorber by using GA method and mathematical gradient methods, Journal of Sound and Vibration, 1286(4–5): 941–961, doi: 10.1016/j.jsv.2004.10.039.
5. Chiu M.C. (2009a), Optimization of equipment allocation and sound-barriers shape in a multi-noise plant by using simulated annealing, Noise & Vibration Worldwide, 40(7): 23–35, doi: 10.1260/095745609788921857.
6. Chiu M.C. (2009b), Simulated annealing optimization on multi-chamber mufflers hybridized with perforated plug-inlet under space constraints, Archives of Acoustics, 34(3): 305–343.
7. Chiu M.C. (2010a), Numerical optimization of a threechamber muffler hybridized with a side inlet and a perforated tube by SA method, Journal of Marine Science and Technology, 18(4): 484–495, doi: 10.51400/2709-6998.1897.
8. Chiu M.C. (2010b), Optimal design of multi-chamber mufflers hybridized with perforated intruding inlets and resonated tube using simulated annealing, Journal of Vibration and Acoustics, 132(5): Article ID 054503, doi: 10.1115/1.4001514.
9. Chiu M.C. (2012), Noise elimination of a multi-tone broadband noise with hybrid Helmholtz mufflers using a simulated annealing method, Archives of Acoustics, 37(4): 489–498, doi: 10.2478/v10168-012-0061-0.
10. Chiu M.C. (2013), Numerical assessment for a broadband and tuned noise using hybrid mufflers and a simulated annealing method, Journal of Sound and Vibration, 332(12): 2923–2940, doi: 10.1016/j.jsv.2012.12.039.
11. Chiu M.C. (2014a), Acoustical treatment of multi-tone broadband noise with hybrid side-branched mufflers using a simulated annealing method, Journal of Low Frequency Noise Vibration and Active Control, 33(1): 79–112, doi: 10.1260/0263-0923.33.1.79.
12. Chiu M.C. (2014b), Optimal design on one-layer closefitting acoustical hoods using a simulated annealing method, Journal of Marine Science and Technology, 22(2): 211–217, doi: 10.6119/JMST-013-0503-1.
13. Chiu M.C., Chang Y.C. (2014), An assessment of high-order-mode analysis and shape optimization of expansion chamber mufflers, Archives of Acoustics, 39(4): 489–499, doi: 10.2478/aoa-2014-0053.
14. Kirkpatrick S., Gelatt C.D., Vecchi M.P. (1983), Optimization by simulated annealing, Science, 220 (4598): 671–680, doi: 10.1126/science.220.4598.671.
15. Metropolis A., Rosenbluth W., Rosenbluth M.N., Teller H., Teller E. (1953), Equation of static calculations by fast computing machines, The Journal of Chemical Physics, 21(6): 1087–1092, doi: 10.1063/1.1699114.
16. Munjal M.L. (1987), Acoustics of Ducts and Mufflers with Application to Exhaust and Ventilation System Design, John Wiley & Sons, New York.
17. Munjal M.L., Rao K.N., Sahasrabudhe A.D. (1987), Aeroacoustic analysis of perforated muffler components, Journal of Sound and Vibration, 114(2): 173– 188, doi: 10.1016/S0022-460X(87)80146-3.
18. Peat K.S. (1988), A numerical decoupling analysis of perforated pipe silencer elements, Journal of Sound and Vibration, 123(2), 199–212.
19. Sullivan J.W. (1979a), A method of modeling perforated tube muffler components I: theory, The Journal of the Acoustic Society of America, 66(3): 772–778, doi: 10.1121/1.383679.
20. Sullivan J.W. (1979b), A method of modeling perforated tube muffler components II: theory, The Journal of the Acoustic Society of America, 66(3): 779–788, doi: 10.1121/1.383680.
21. Sullivan J.W., Crocker M.J. (1978), Analysis of concentric tube resonators having unpartitioned cavities, The Journal of the Acoustic Society of America, 64(1): 207–215, doi: 10.1121/1.381963.
22. Yeh L.J., Chang Y.C., Chiu M.C., Lai G.J. (2004), GA optimization on multi-segments muffler under space constraints, Applied Acoustics, 65(5): 521–543, doi: 10.1016/j.apacoust.2003.10.010.
23. Yeh L.J., Chang Y.C., Chiu M.C. (2006), Numerical studies on constrained venting system with reactive mufflers by GA optimization, International Journal for Numerical Methods in Engineering, 65(8): 1165–1185, doi: 10.1002/nme.1476.
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Authors and Affiliations

Min-Chie Chiu
1
Ho-Chih Cheng
2

  1. Department of Mechanical and Materials Engineering, Tatung University, Taiwan, R.O.C.
  2. Department of Intelligent Automation Engineering, Chung Chou University of Science and Technology, Taiwan, R.O.C.

Abstract

The paper contains the abstracts of papers presented during 67th Open Seminar on Acoustics September 14–17, 2021.
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