基于机器学习的混凝土中活性化学粉末配合比
优化研究

金属矿山 ›› 2025, Vol. 54 ›› Issue (6): 174-181.

基于机器学习的混凝土中活性化学粉末配合比优化研究

任太印¹　黄运芹¹ 　杨雪锋² 　程凌云¹　徐沛保^2,3

1. 国网安徽省电力有限公司合肥供电公司,安徽合肥 230041;2. 安徽华电工程咨询设计有限公司,安徽合肥 230022; 3. 安徽建筑大学土木工程学院,安徽合肥 230601

出版日期:2025-06-15 发布日期:2025-07-09
通讯作者: 徐沛保(1986—),男,副教授,博士,硕士研究生导师。
作者简介:任太印(1978—),男,高级工程师。
基金资助:
国家自然科学基金项目(编号:12172001);国网安徽省电力有限公司科技项目(编号:5212A0240002)。

Research on the Mix Ratio Optimization of Active Chemical Powders in Concrete Based on Machine Learning

REN Taiyin ¹ 　 HUANG Yunqin¹　 YANG Xuefeng ² 　 CHENG Lingyun ¹　 XU Peibao ^2,3

1. State Grid Anhui Electric Power Co. ,Ltd. ,Hefei Power Supply Company,Hefei 230041,China;2. Anhui Huadian Engineering Consulting Design Co. ,Ltd. ,Hefei 230022,China;3. College of Civil Engineering,Anhui Jianzhu University,Hefei 230601,China

Online:2025-06-15 Published:2025-07-09

摘要/Abstract

摘要： 活性化学粉末在修复混凝土内部微裂纹、提高力学强度、提升耐久性、延长使用寿命、减少维护成本等方面具有重要应用价值。为了获得优异性能的自愈混凝土,研究利用络合剂 SMS、助剂(硅酸铝+硫酸钠,质量比为 1 ∶ 1)、甲酸钙、葡萄糖酸钠为混凝土外加剂进行正交试验。通过抗压强度、劈裂抗拉强度等关键参数对混凝土自愈性能进行评价,研究活性化学粉末对混凝土自愈性能的影响。试验研究表明,不同配比的活性化学粉末和不同程度的损伤度对混凝土强度具有重要的影响。对于多因素复杂的试验结果,研究利用机器学习的方法构建自愈混凝土强度恢复性能预测模型,以起始强度、损伤修复强度为优化目标,结合优劣解距离法提出活性化学成分配合比优化方法,获得自愈混凝土强度恢复性能最优的活性粉末配合比,并进行了试验验证和机理解释。该研究有助于深刻了解活性化学粉末对混凝土自修复性能的影响并指导施工配合比设计。

关键词: 活性化学粉末　压缩与劈裂强度　强度恢复　配合比优化　愈合机理

Abstract: Active chemical powder has important application value in repairing concrete micro-cracks,improving mechanical strength,enhancing durability,prolonging service life and reducing maintenance cost. In order to obtain excellent performance of self-healing concrete,this study uses complexing agent SMS,auxiliary agent (aluminum silicate + sodium sulfate,with a mass ratio of 1 ∶1),calcium formate and sodium gluconate as concrete admixtures for orthogonal experiment. The self-healing properties of concrete are evaluated by key parameters such as compressive strength and splitting tensile strength,and the effect law of active chemical powder on the self-healing properties of concrete is studied. Experimental studies have shown that different proportions of active chemical powder and different degrees of damage have an important influence on the strength of concrete. For the multi-factor complex experimental results,the study uses the method of machine learning to build a self-healing concrete strength recovery performance prediction model,takes the initial strength and damage repair strength as optimization objectives,and combines the good and bad solution distance method to propose the mix ratio optimization method of active chemical components,so as to obtain the mix ratio of active powder with the best strength recovery performance of self-healing concrete. Experimental verification and mechanism explanation have been carried out. This study is helpful to deeply understand the effect of active chemical powder on the self-healing properties of concrete and guide the design of construction mix ratio.

Key words: active chemical powder,compressive and splitting strengths,strength recovery,mix ratio optimization,healing mechanism

中图分类号:

任太印　黄运芹　杨雪锋　程凌云　徐沛保, . 基于机器学习的混凝土中活性化学粉末配合比优化研究[J]. 金属矿山, 2025, 54(6): 174-181.

REN Taiyin 　 HUANG Yunqin 　 YANG Xuefeng 　 CHENG Lingyun 　 XU Peibao , . Research on the Mix Ratio Optimization of Active Chemical Powders in Concrete Based on Machine Learning[J]. Metal Mine, 2025, 54(6): 174-181.

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