基于响应面分析的纤维泡沫混凝土多目标优化

doi:10.12068/j.issn.1005-3026.2025.20230340

摘要/Abstract

摘要：

泡沫混凝土可作为初期支护和二次衬砌之间的变形预留层，抵抗高地应力深埋隧道围岩流变变形.通过掺入纤维可进一步改善其压缩性能及延性，并在一定纤维特征条件下解决抗压强度低的问题.利用正交试验及响应面Box-Behnken设计法，系统探究纤维质量分数、长度、种类等特征因素对泡沫混凝土抗压强度与弹性模量的影响，并构建特征回归模型对配合比进行优化.结果表明：响应面法建立回归模型具有较高的可信度.在多种纤维特征中，纤维质量分数对泡沫混凝土的抗压强度和弹性模量影响最大，同时多特征之间的交互作用对抗压强度影响较大，而对弹性模量影响较小，且纤维长度和纤维种类的交互作用对其抗压强度影响最为显著.此外，通过最大化抗压强度和最小化弹性模量的目标进行模型配合比优化，得出最优配合比的相对误差绝对值均小于5%.该模型可为此工程背景下不同纤维特征的泡沫混凝土参数优化提供参考.

关键词: 隧道预留层, 泡沫混凝土, Box-Behnken设计, 响应面法, 多目标优化

Abstract:

Foam concrete severs as a deformation reserve layer between the initial support and the secondary lining， effectively resisting the rheological deformation of the surrounding rock in deeply buried tunnels with high-ground stress. The incorporation of fibers enhances its compressive performance and ductility， addressing the issue of low compressive strength under specific fiber characteristics. Orthogonal test and Box-Behnken design method of response surface were used to systematically investigate the effects of various characteristics such as fiber mass fraction， length， and types， on the compressive strength and elastic modulus of foam concrete. A characteristic regression model was developed to optimize the mix ratio. The results show that the regression model established by the response surface method demonstrates high accuracy and reliability. Among the various fiber characteristics， the fiber mass fraction has the greatest impact on both the compressive strength and elastic modulus of foam concrete. Meanwhile， the interaction among multiple characteristics significantly influences compressive strength while slightly impacts elastic modulus. Particularly， the interaction between fiber length and fiber type has the most obvious impact on compressive strength. Furthermore， by maximizing the compressive strength and minimizing the elastic modulus， the optimized mix ratio result derived from the model shows that the absolute values of the relative errors are less than 5%. The small relative errors indicate that the proposed model can provide support for the multi-objective optimization of foam concrete with different fiber characteristics in the project application.

Key words: tunnel reserve layer, foam concrete, Box-Behnken design（BBD）, response surface method, multi-objective optimization

中图分类号:

TU 5

王述红, 李皓然, 尹宏, 贡藩. 基于响应面分析的纤维泡沫混凝土多目标优化[J]. 东北大学学报（自然科学版）, 2025, 46(6): 122-130.

Shu-hong WANG, Hao-ran LI, Hong YIN, Fan GONG. Multi-objective Optimization of Fiber Foam Concrete Based on Response Surface Analysis[J]. Journal of Northeastern University(Natural Science), 2025, 46(6): 122-130.

图/表 16

参考文献 21

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性质参数	说明
外观	黑色液体
稀释倍数	40
使用温度/℃	5~60
溶解性	用水稀释为均匀液体，静置24 h不分层、不沉底

性质参数	说明
外观	黑色液体
稀释倍数	40
使用温度/℃	5~60
溶解性	用水稀释为均匀液体，静置24 h不分层、不沉底

纤维种类	密度	单丝直径	弹性模量	抗拉强度
纤维种类	g·cm^-3	μm	GPa	MPa
BF	2.63~2.65	7~15	91.0~110.0	3 000~4 800
PVA	1.29	15.09	40.0	1 830
PP	0.91	32.70	4.2	469

纤维种类	密度	单丝直径	弹性模量	抗拉强度
纤维种类	g·cm^-3	μm	GPa	MPa
BF	2.63~2.65	7~15	91.0~110.0	3 000~4 800
PVA	1.29	15.09	40.0	1 830
PP	0.91	32.70	4.2	469

水平	因素
	纤维种类	纤维长度	纤维质量分数
	纤维种类	mm	%
1	BF	3	0.1
2	PVA	6	0.2
3	PP	9	0.3