scholarly journals Acoustic characterization of an on-site machining operation

2021 ◽  
Vol 39 ◽  
pp. 101-106
Author(s):  
Christopher Langrand ◽  
Antoine Albert ◽  
Maxime Masset
1997 ◽  
Author(s):  
Anatoliy N. Ivakin ◽  
Darrell R. Jackson

2017 ◽  
Vol 122 (8) ◽  
pp. 084103 ◽  
Author(s):  
E. Smirnova ◽  
A. Sotnikov ◽  
S. Ktitorov ◽  
H. Schmidt

2021 ◽  
pp. 004051752110238
Author(s):  
Oluwafemi P Akinmolayan ◽  
James M Manimala

Silica nanoparticle-impregnated Kevlar (SNK) fabric has better specific ballistic performance in comparison to its neat counterparts. For multifunctional structural applications using lightweight composites, combining this improved ballistic functionality with an acoustic functionality is desirable. In this study, acoustic characterization of neat and SNK samples is conducted using the normal-incidence impedance tube method. Both the absorption coefficient and transmission loss (TL) are measured in the 60–6000 Hz frequency range. The influence of parameters such as number of layers of neat or treated fabric, percentage by weight of nanoparticle addition, spacing between fabric layers, and residual porosity is examined. It is found that while absorption decreases with an increase in nanoparticle addition for frequencies above about 2500 Hz, increasing the number of layers shifts peak absorption to lower frequencies. By introducing an air-gap behind the fabric layer, dominant low-frequency (1000–3000 Hz) absorption peaks are obtained that correlate well with natural modes of mass-equivalent thin plates. Examining the influence of residual porosity by laminating the SNK samples reveals that it contributes to about 30–50% of the total absorption. Above about 1500 Hz, 3–5 dB of TL increase is obtained for SNK samples vis-à-vis the neat samples. TL is found to increase beyond that of the neat sample above a threshold frequency when an air-gap is introduced between two SNK layers. With an increase in the weight of nanoparticle addition, measured TL tends to be closer to mass law predictions. This study demonstrates that SNK fabric could provide improved acoustic performance in addition to its ballistic capabilities, making it suitable for multifunctional applications and could form the basis for the development of simplified models to predict the structural acoustic response of such nanoparticle–fabric composites.


2021 ◽  
Vol 11 (13) ◽  
pp. 5924
Author(s):  
Elisa Levi ◽  
Simona Sgarbi ◽  
Edoardo Alessio Piana

From a circular economy perspective, the acoustic characterization of steelwork by-products is a topic worth investigating, especially because little or no literature can be found on this subject. The possibility to reuse and add value to a large amount of this kind of waste material can lead to significant economic and environmental benefits. Once properly analyzed and optimized, these by-products can become a valuable alternative to conventional materials for noise control applications. The main acoustic properties of these materials can be investigated by means of a four-microphone impedance tube. Through an inverse technique, it is then possible to derive some non-acoustic properties of interest, useful to physically characterize the structure of the materials. The inverse method adopted in this paper is founded on the Johnson–Champoux–Allard model and uses a standard minimization procedure based on the difference between the sound absorption coefficients obtained experimentally and predicted by the Johnson–Champoux–Allard model. The results obtained are consistent with other literature data for similar materials. The knowledge of the physical parameters retrieved applying this technique (porosity, airflow resistivity, tortuosity, viscous and thermal characteristic length) is fundamental for the acoustic optimization of the porous materials in the case of future applications.


Author(s):  
Paolo La Torraca ◽  
Luca Larcher ◽  
Paolo Lugli ◽  
Marco Bobinger ◽  
Francisco J. Romero ◽  
...  

Langmuir ◽  
2002 ◽  
Vol 18 (2) ◽  
pp. 405-412 ◽  
Author(s):  
Alexander K. Hipp ◽  
Giuseppe Storti ◽  
Massimo Morbidelli

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