Approaches and methods for improving the performance of ionic thermoelectric materials

doi:10.1016/j.cej.2025.160206

Prediction of sound absorption and insulation properties of honeycomb composites embedded with glass fiber and silica aerogel based on backpropagation neural network

2026-05-08

0

PRE

AI

L

Liping Liu

H

Hui Wang

J

Jieyu Xue

Y

Yuanrong Ding

X

Xuhong Yang

R

Ruonan Han

Z

Zhou Chen

Y

Yong Yang *

DOI：10.1016/j.apmt.2026.103260

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Abstract

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● To predict the acoustic performance of honeycomb-embedded structures, a BPNN model is employed. ● Root-mean-square error of sound insulation is 0.68725. ● Root-mean-square error of sound absorption is 0.05.

Keywords:

sound absorption

sound insulation

honeycomb composites

backpropagation neural network

silica aerogel

Prediction of sound absorption and insulation properties of honeycomb composites embedded with glass fiber and silica aerogel based on backpropagation neural network

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