Analysis of acoustic performance of glass fiber felts after water absorption and their estimation results by artificial neural network

Wang, Fei; Chen, Zhaofeng; Wu, Cao; Yang, Yong; Zhang, Duanyin; Li, Shun

doi:10.1080/00405000.2019.1678559

Cited by 8 publications

(3 citation statements)

References 14 publications

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“…It has become an important adsorbent in the field of chemistry and an important new, lightweight, and energy-saving composite multifunctional carrier. It can be used for insulation [ 8 ], fire prevention [ 9 , 10 ], heat insulation [ 11 , 12 , 13 ], sound insulation [ 14 , 15 , 16 ], adsorption [ 17 , 18 ], and as a polymer precursor [ 19 , 20 , 21 ]. It is widely used in plastics, rubber, chemicals, aerospace, and other fields.…”

Section: Introductionmentioning

confidence: 99%

Recent Progress in Modifications, Properties, and Practical Applications of Glass Fiber

Song

et al. 2023

Molecules

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As a new member of the silica-derivative family, modified glass fiber (MGF) has attracted extensive attention because of its excellent properties and potential applications. Surface modification of glass fiber (GF) greatly changes its performance, resulting in a series of changes to its surface structure, wettability, electrical properties, mechanical properties, and stability. This article summarizes the latest research progress in MGF, including the different modification methods, the various properties, and their advanced applications in different fields. Finally, the challenges and possible solutions were provided for future investigations of MGF.

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Section: Introductionmentioning

confidence: 99%

Recent Progress in Modifications, Properties, and Practical Applications of Glass Fiber

Song

et al. 2023

Molecules

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“…With the development of intelligent algorithms and neural networks, more and more researchers are choosing neural networks to predict the acoustic properties of materials. Artificial neural networks (ANN) [ 22 , 23 , 24 , 25 , 26 , 27 ], radial basis function neural networks (RBF) [ 9 ], and generalized regression neural networks (GRNN) [ 28 ], are commonly used to predict sound absorption coefficients.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the Sound Absorption Coefficient of Three-Layer Aluminum Foam by Hybrid Neural Network Optimization Algorithm

Guo

Lisi

et al. 2022

Materials

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The combination of multilayer aluminum foam can have high sound absorption coefficients (SAC) at low and medium frequencies, and predicting its absorption coefficient can help the optimal structural design. In this study, a hybrid EO-GRNN model was proposed for predicting the sound absorption coefficient of the three-layer composite structure of the aluminum foam. The generalized regression neural network (GRNN) model was used to predict the sound absorption coefficient of three-layer composite structural aluminum foam due to its outstanding nonlinear problem-handling capability. An equilibrium optimization (EO) algorithm was used to determine the parameters in the neuronal network. The prediction results show that this method has good accuracy and high precision. The calculation result shows that this proposed hybrid model outperforms the single GRNN model, the GRNN model optimized by PSO (PSO-GRNN), and the GRNN model optimized by FOA(FOA-GRNN). The prediction results are expressed in terms of root mean square error (RMSE), absolute error, and relative error, and this method performs well with an average RMSE of only 0.011.

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“…It was an excellent sound absorbing and heat insulation material, mainly used in different kinds of cabins of vessels, aircraft, vehicles and constructions [1, 2], etc. The corresponding sound absorption [3, 4], heat insulation properties [5] and the porous structure of felts were widely researched. The porous structure of the glass fiber felt was helpful to discharge the moisture in the cabin, protected the humidity environment in the cabin, and ensured the normal operation of precision instruments.…”

Section: Introductionmentioning

confidence: 99%

Comparison of the physical properties of heat-treated and hydrophobic modified glass fiber felt

Wang

et al. 2021

Journal of Industrial Textiles

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The glass fiber felt owned opening pore structure and chemical stability, which was widely used in various of cabins of vessels, aircraft, vehicles, etc. The surface characteristics of fiber affected the drainage performance of felt, thus affecting the temperature and humidity environment in the cabin. In this paper, the physical properties of heat-treated and hydrophobic modified glass fiber felt were studied and compared. After heat treatment, the surface sizing agents were removed and the felt surface became smoother. The water contact angle (WCA) of all heated felt was 0°. The residual water of 1.5 cm and 0.5 cm felt decreased by 27% and 15%, respectively, while that of 2.5 cm felt increased 324%. The excellent drainage performance could be obtained by reducing the heated felt thickness. However, the tensile strength of felt decreased by 35%–45%. In addition, the fiber diameter, the thickness, and average pore size of heated felt all decreased. After hydrophobic modification, abundant nano particles adhered to the felt surface, making the surface of felt rough. The WCAs of 2.5 cm, 1.5 cm and 0.5 cm hydrophobic modified felt were 152°, 141°, 144°, respectively. The residual water decreased by more than 60%, indicating that the drainage performance of felt could be significantly improved. The tensile strength of felt was increased by 30%–40%. The fiber diameter increased, but the thickness and the average pore size of felt decreased. Compared with the heat treatment, the hydrophobic modification could obtain excellent drainage performance and increased the felt tensile strength, which was suitable for more occasions.

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Analysis of acoustic performance of glass fiber felts after water absorption and their estimation results by artificial neural network

Cited by 8 publications

References 14 publications

Recent Progress in Modifications, Properties, and Practical Applications of Glass Fiber

Recent Progress in Modifications, Properties, and Practical Applications of Glass Fiber

Prediction of the Sound Absorption Coefficient of Three-Layer Aluminum Foam by Hybrid Neural Network Optimization Algorithm

Comparison of the physical properties of heat-treated and hydrophobic modified glass fiber felt

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