Intelligent prediction method of setting time of ground polymer grouting material
地聚合物注浆材料凝结时间智能预测方法

摘要

地聚合物注浆材料作为一种新型绿色胶凝材料，其凝结时间直接影响到工程施工的安全性与效率。由于配比、温度、湿度及活性矿物特性等多因素共同作用，传统经验法难以实现准确预测。为解决该问题，本文提出一种基于智能建模的凝结时间预测方法。通过收集实验数据，采用机器学习算法对关键影响因子进行特征提取与关联分析，构建凝结时间预测模型，并在多组实验中进行验证。结果表明，该方法预测精度高、适应性强，能够为工程注浆工艺参数设计与施工控制提供有效参考，提升地聚合物注浆材料的应用可靠性与工程可控性。

Abstract

As a novel green cementitious material, the setting time of geopolymer grouting materials directly impacts construction safety and efficiency. Traditional empirical methods struggle to achieve accurate predictions due to complex factors including mix proportions, temperature, humidity, and active mineral characteristics. To address this challenge, this study proposes an intelligent modeling-based setting time prediction method. Through experimental data collection and machine learning algorithms for feature extraction and correlation analysis of key influencing factors, a setting time prediction model was developed and validated through multiple experiments.
Results demonstrate that this method exhibits high prediction accuracy and strong adaptability, providing effective references for grouting process parameter design and construction control. This enhances the application reliability and engineering controllability of geopolymer grouting materials.