基于RSM优化玄武岩纤维增强磷石膏基复合材料力学性能
收稿日期: 2022-11-18
网络出版日期: 2023-08-25
基金资助
国家自然科学基金项目(52168027);国家自然科学基金项目(51968009);国家自然科学基金项目(12162009);贵州省科技计划项目(［2020］1Y244)
Optimization of mechanical properties of basalt fiber reinforced phosphogypsum-based composites based on RSM
Received date: 2022-11-18
Online published: 2023-08-25
为了探明玄武岩纤维的直径、长度、掺量及其两两交互作用对磷石膏基复合材料力学性能的影响机制并实现其多目标优化，采用Box-Behnken响应面法（RSM）设计实验，并建立了复合材料28 d抗压、抗折强度的多项式回归模型。结果表明，纤维掺量对复合材料力学性能的影响最为显著，而直径与长度的交互作用、长度和掺量的交互作用分别是影响其抗压强度和抗折强度的关键性因素，这主要是源于基体在压缩和弯曲过程中的受力特性和不同参数下纤维在其中所产生的应力效应不同。对纤维参数进行优化得出最优条件：纤维直径为13 μm、长度为9.439 mm、纤维质量分数为1.023%，该条件下复合材料抗压、抗折强度分别为31.878、6.347 MPa，模型验证实验相对误差分别为2.02%和5.09%，模型精确度高，拟合效果好，表明RSM可用于纤维增强石膏基复合材料的强度预测和纤维参数优化。
崔庚寅 , 谢浪 , 陆跃贤 , 孔德文 , 王玲玲 . 基于RSM优化玄武岩纤维增强磷石膏基复合材料力学性能[J]. 无机盐工业, 2023 , 55(8) : 116 -123 . DOI: 10.19964/j.issn.1006-4990.2022-0622
In order to explore the influence mechanism of basalt fiber diameter，length，dosage and their interaction on the mechanical properties of phosphogypsum-based composites（PGCs），and to realize its multi-objective optimization，a test was designed by Box-Behnken response surface methodology（RSM），meanwhile，polynomial regression models of 28 d compressive and flexural strength of composites were established.The results showed that the fiber dosage had the most significant influence on the mechanical properties of the composites，and the interaction between the diameter and length was the key factor affecting the compressive strength，while the interaction of the length and dosage was the key factor affecting their flexural strength，which was due to the different stress characteristics of the matrix in the process of compression and bending，as well as the various stress effects of the fibers in it under different parameters.The optimal conditions were obtained by optimizing the fiber parameters：fiber diameter of 13 μm，length of 9.439 mm，and fiber mass fraction of 1.023%.Under these conditions，the compressive and flexural strengths of the composites were 31.878 MPa and 6.347 MPa，respectively.The relative errors of the model validation experiments were 2.02% and 5.09%，respectively.The model showed a high accuracy and good fitting effect，indicating that RSM could be used to predict the strength and optimize the fiber parameters of fiber reinforced gypsum-based composites.
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