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Investigation and prediction of mechanical properties of hot water treated jute/poly(lactic acid) composite laminates using response surface methodology and genetic algorithm
Polymer Composites ( IF 5.2 ) Pub Date : 2022-06-23 , DOI: 10.1002/pc.26780
Weixing Zhang 1 , Chunxia He 1
Affiliation  

The main objective of this work was to estimate the usefulness of response surface methodology (RSM) and genetic algorithm (GA) in modeling and predicting the strength of jute/poly(lactic acid) (PLA) composite laminates. Firstly, the impact of the hot water treatment on the thermal, molecular structure, and morphological characterizations as well as kinetic analysis of jute fibers were performed by Thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM). The FTIR results showed that the hot water treatments reduced the content of lignin, hemicellulose, and impurities of the fibers. Hot water treated fibers exhibited higher thermal stabilities compared with untreated fibers as shown with TGA results. The SEM results showed effect contact surface area improved after the hot water treatment, leading to better mechanical properties of bio-composites. Secondly, the influences of the ply orientation, plies and fiber content on the tensile strength and flexural strength of the hot water treated fibers composites were evaluated by RSM. RSM with the Box Behnken Design was utilized to establish the quadratic models of two objectives in response to input parameters. Analysis of variance (ANOVA) was used to determine percentage contribution of various parameters on two quality objectives. According to the ANOVA results, ply orientation had the most important impact on tensile strength while the ply orientation-fiber content interaction had the most important impact on flexural strength. Finally, multi-objective optimization was carried out to maximize tensile strength and flexural strength using the desirability function and GA. The optimized results both showed an acceptable relative error between experimental and optimized values.

中文翻译:

利用响应面法和遗传算法研究和预测热水处理黄麻/聚乳酸复合层压板的力学性能

这项工作的主要目的是估计响应面法 (RSM) 和遗传算法 (GA) 在建模和预测黄麻/聚乳酸 (PLA) 复合层压板强度方面的有用性。首先,通过热重分析 (TGA)、傅里叶变换红外光谱 (FTIR)、扫描电子显微镜 (SEM) 对热水处理对黄麻纤维的热学、分子结构和形态表征以及动力学分析的影响进行了分析。 . FTIR 结果表明,热水处理降低了纤维中木质素、半纤维素和杂质的含量。与未处理的纤维相比,热水处理的纤维表现出更高的热稳定性,如 TGA 结果所示。SEM结果表明热水处理后接触表面积提高,使生物复合材料具有更好的力学性能。其次,通过RSM评估了层取向、层数和纤维含量对热水处理纤维复合材料的拉伸强度和弯曲强度的影响。使用带有 Box Behnken 设计的 RSM 来建立两个目标的二次模型以响应输入参数。方差分析 (ANOVA) 用于确定各种参数对两个质量目标的贡献百分比。根据方差分析结果,层取向对拉伸强度的影响最为重要,而层取向-纤维含量的相互作用对弯曲强度的影响最为重要。最后,使用期望函数和遗传算法进行多目标优化以最大化拉伸强度和弯曲强度。
更新日期:2022-06-23
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