The Optimization Study of Karst-Filling Clay-Cement Grout Based on Orthogonal Experiment and Regression Analysis

基于正交试验和回归分析的岩溶充填粘土水泥浆优化研究

阅读:1

Abstract

During shield tunnel construction, karst development along the tunnel axis and in the surrounding area frequently poses a significant threat to engineering safety. To address this challenge, this study proposes multiple grouting systems and systematically analyzes the key mechanical properties of five grout formulations through orthogonal experiments, identifying the optimal formulations for engineering applications. A predictive model was established using linear regression, and its accuracy was validated through independent single-factor experiments. The results indicate the following: (1) Water content is the primary factor influencing fluidity, with its significance varying by system composition. The lake mud-cement grout exhibits the highest compressive pstrength. Moderate sand addition enhances strength, but excessive amounts significantly reduce fluidity. Additives demonstrate system dependency: HY-4 effectively improves fluidity, while sodium silicate significantly increases strength but reduces fluidity. (2) The developed model demonstrates good goodness of fit, with coefficients of determination (R(2)) ranging from 0.74 to 0.95, without significant autocorrelation or multicollinearity. Validation experiments confirm the model's high predictive accuracy, with overall trends consistent with the measured data. (3) The lake mud-cement grout (A3B1C3) is recommended for reinforcement projects prioritizing stability, achieving a 28-day compressive strength of 4.74 MPa. The on-site wet clay-cement grout (A2B3C1) is suitable for high-permeability formations, with a strength of 1.1 MPa and a fluidity of 292.5 mm, both exceeding standard requirements. The findings provide optimized formulations and theoretical references for grouting reinforcement in karst tunnel projects.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。