Sound Absorption Properties of the Patented Wood, Lightweight Stabilised Blockboard
Author:
Roziņš Rihards1, Brencis Raitis1, Spulle Uldis1, Spulle-Meiere Ivanda1
Affiliation:
1. Latvia University of Life Sciences and Technologies , 2 Liela street , Jelgava , Latvia
Abstract
Abstract
It is well known that wood tends to shrink and swell as the relative humidity of the air changes. There have been, and still are, attempts to make dimensionally stable wood panels such as Dendrolight®. The physical-mechanical, operational, including acoustic, properties of this material have been significantly improved compared to traditional wood-based panels. However, the production of this material requires very specific processing equipment and a large energy investment. The developers of this material in Latvia invented and patented wood, Lightweight Stabilised Blockboard (LSB). In order for this material to be used in the production of various products, it is necessary to clarify its characteristic, technological, as well as operational properties. The study gathers information about the sound absorption properties of various natural and wood materials, characteristics, and the sound absorption of the studied material at different sound frequencies. The reviewed sources of information indicate that nowadays there are still problems in sound conduction and absorption and isolation issues are being addressed in building acoustics. The production of samples and the determination of sound absorption were carried out using a developed methodology developed in accordance with regulatory requirements. The data obtained in the practical study were compared with the relevant indicators of the Dendrolight® and wood-based panels used for building structures and to determine their compliance with the requirements set forth in the standards ISO 10534-2 and ISO 11654. Research data show that LSB corresponds to E sound absorption class in some of the investigated frequencies.
Publisher
Walter de Gruyter GmbH
Reference27 articles.
1. Arzola-Villegas, X., Báez, C., Lakes, R., Stone, D.S., O’Dell, J., Shevchenko, P., Xiao, X., De Carlo, F. & Jakes, J.E. (2023). Convolutional Neural Network for Segmenting Micro-X-ray Computed Tomography Images of Wood Cellular Structures. Applied Sciences, 13, 8146-8161. DOI: 10.3390/app13148146. 2. Bies, A.D. & Hansen, C.H. (2009). Engineering Noise Control: Theory and Practice. CRC Press: London. 3. Bies, D.A., Hansen C. & Howard C. (2017). Engineering Noise Control, Fifth Edition. CRC Press: Boca Raton. 4. Cao, L., Fu, Q., Si, Y., Ding, B. & Yu, J. (2018). Porous materials for sound absorption. Composites Communications, 10, 25–35. DOI: 10.1016/j.coco.2018.05.001. 5. Dukarska, D., Walkiewicz, J., Derkowski, A. & Mirski, R. (2022). Properties of Rigid Polyurethane Foam Filled with Sawdust from Primary Wood Processing. Materials, 15, 5361-5379. DOI: 10.3390/ma15155361.
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