Renovation of the reverberation room at Ocean University of China based on ODEON simulation

Liheng  Shi; Ju  Lin

doi:10.59400/sv1680

Renovation of the reverberation room at Ocean University of China based on ODEON simulation

Liheng Shi Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
Ju Lin Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, China

Article ID: 1680

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DOI: https://doi.org/10.59400/sv1680

Keywords: reverberation room; ODEON; simulation; diffuser; reverberation time

Abstract

The reverberation room is a crucial laboratory for determining the sound absorption properties of materials. The reverberation room at the Laoshan Campus of Ocean University of China lacks complete acoustic design. Using computer-aided simulations, defects in the sound field can be clearly revealed and the design proposals’ effectiveness can be pre-validated. This study focuses on renovating the reverberation room by conducting acoustic performance tests and constructing a three-dimensional model. Leveraging the advantages of ODEON for simulating sound fields, it analyzes the uniformity of sound field diffusion, considering not only reverberation time distribution but also linear decay curves and deviations in sound pressure level distribution. Subsequently, the room undergoes simulated renovation in accordance with national standards of China and international standards, and diffusion body design schemes, including semi-cylindrical and semi-conical hard wall diffusers and suspended plexiglass diffusers, are compared through simulations to arrive at the final optimized renovation plan. The simulations show that the deviation in sound field uniformity can be reduced to less than 1.5 dB after renovation, and the reverberation time is also significantly extended. These findings can inform the actual renovation of the Laoshan Campus reverberation room and serve as a reference for other reverberation room renovations and indoor acoustic simulations.

References

[1]Long M. Architectural acoustics, 2nd ed. Boston: Academic Press; 2014.

[2]Xiang DQ, Wang Z, Chen JJ. Acoustic design of a reverberation chamber. Appl. Acoust. 1991; 32(2): 83-91.

[3]Qiu X, Zhu Q, Wang S, et al. A case study on the new reverberation room built in University of Technology Sydney. In: Proceedings of the 23rd International Congress on Acoustics (ICA 2019); 2019.

[4]Masih DAA, Jalal NK, Mohammed MNA, et al. Assessment of Acoustical Characteristics for Recent Mosque Buildings in Erbil City of Iraq. Aro. 2021; 9(1): 51-66.

[5]Fu S, Guo Z, Teng Z, et al. An application study on ODEON simulation to control the sound quality of multi-functional gymnasium. Period. Ocean Univ. China. 2016; 46(5): 132-7.

[6]Nowoswiat A, Olechowska M. Experimental Validation of the Model of Reverberation Time Prediction in a Room. Buildings-Basel. 2022; 12(3).

[7]Abd-Elbasseer M, Mohamed HK. Performance Evaluation and Effectiveness of the Reverberation Room. Sound Vib. 2021; 55(1): 43-55.

[8]Drabek P, Zalesak M. Reverberation chamber and its verification for acoustic measurements. In: Proceedings of 20th International Conference on Circuits, Systems, Communications and Computers (CSCC 2016); 2016.

[9]Bakhtiar YH, Indrawati S, Suyatno. Evaluation of reverberation chamber relation to reverberation time and distribution of sound pressure level with ISO 354 as standard in building physics laboratory of physics department ITS. In: Proceedings of 9th International Conference on Physics and Its Applications (ICOPIA 2019); 2019.

[10]Everest FA, Pohlmann KC. Master handbook of acoustics, 5th ed. New York: McGraw-Hill; 2009.

[11]Marko H, Kristian J, Hrvoje D. Methods of Measuring the Reverberation Time. In: Proceedings of 3rd Congress of the Alps Adria Acoustics Association; 2007.

[12]Tohyama M. Acoustic signals and hearing. Boston: Academic Press; 2020.

[13]Beranek L, Mellow T. Acoustics, 2nd ed. Boston: Academic Press; 2019.

[14]ISO. Acoustics—Measurement of room acoustic parameters. Switzerland: International Organization for Standardization; 2009.

[15]Salim N, Tauhid Ahmad NH, Amir Tan A, et al. Reverberation Time Measurement for ANGKASA’s High Intensity Acoustic Chamber. Appl. Mech. Mater. 2015; 793: 615-9.

[16]Grosveld FW. Characterization of the reverberation chamber at the NASA Langley Structural Acoustics Loads and Transmission (SALT) facility. NASA; 2013.

[17]Ivančević B, Jambrošić K, Maletić M. Characteristics of Reverberation Time Measuring Signals. In: Proceedings of 44th International Symposium Electronics in Marine; 2002.

[18]Healy A. Development of reverberation rooms for the measurement of sound absorption [Master’s thesis]. University of Canterbury: New Zealand; 2019.

[19]Wu S, Zhang S, Ge J. Principles of architectural acoustic design, 2nd ed. Beijing: China Architecture & Building Press; 2019.

[20]Lyu Y, Gao Y, Fan K. Acoustic design of the diffuser in reverberation chamber and numerical simulation. Urban. Mass. Transit. 2019; 22(02): 98-102.

Published

2024-11-15

How to Cite

Shi, L., & Lin, J. (2024). Renovation of the reverberation room at Ocean University of China based on ODEON simulation. Sound & Vibration, 59(1), 1680. https://doi.org/10.59400/sv1680

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