Characterization and Modeling of Corn Stalk Fibers tied with Clay using Support Vector Regression Algorithms

ABSTRACT

Several research groups are recently focusing on natural fibers as components of construction materials, contributing to the search for sustainable solutions that reduce the ecological footprint of buildings. Many of these fibers are proposed as acoustic absorbers to replace man-made fibers widely used to reduce reverberation in rooms, such as fiberglass and stone wool, which consume a lot of energy in their production and are not biodegradable. In this article, the acoustic absorption of fiber panels composed of corn stalk fibers and clay – both environmentally friendly materials – is studied, considering samples of 6 mm, 12 mm, and 24 mm thickness. Three percentages of water were used for the kneading of the clay. A support vector machine model has been calculated to predict the behavior of this composite material. 24 mm sample with 6% of water returns values of the acoustic absorption coefficient between 0.6 and 0.8 in the frequency range from 750 to 1600 Hz. 6 mm samples with 16% and 26% of water result in values of the acoustic absorption coefficient near one at 4500 Hz and 4750 Hz, respectively. The simulation performed with the support vector machine model returned Pearson’s correlation coefficient values of 0.997, demonstrating excellent generalization and prediction ability of the model.

摘要

一些研究小组最近将天然纤维作为建筑材料的组成部分，致力于寻找减少建筑生态足迹的可持续解决方案. 其中许多纤维被提议用作吸声材料，以取代广泛用于减少室内混响的人造纤维，如玻璃纤维和石棉，这些纤维在生产过程中消耗大量能源，而且不可生物降解. 本文以6mm、12mm和24mm厚的试样为研究对象，研究了由玉米秸秆纤维和粘土组成的纤维板的吸声性能. 用3%的水来捏粘土. 计算了一个支持向量机模型来预测这种复合材料的性能. 含6%水的24mm样品在750至1600 Hz的频率范围内返回0.6至0.8之间的吸声系数值. 含水量为16%和26%的6mm样品在4500hz和4750hz时的吸声系数分别接近1. 用支持向量机模型进行仿真，得到的Pearson相关系数为0.997，表明该模型具有良好的泛化和预测能力.

关键词:

• 天然材料
• 吸声系数
• 向量机回归模型
• 声学测量

KEYWORDS:

• Natural materials
• sound absorption coefficient
• vector machine regression model
• acoustic measurements

Disclosure statement

No potential competing interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, VPR, upon reasonable request.