Mix proportion optimization of cement flyash-water glass grouting material based on response surface method
Source abstract
Abstract
In the process of tunnel construction and operation, fissure water inrush disasters occur frequently, seriously threatening the safety and construction efficiency of the project. Fracture water inrush accidents often cause significant casualties and property losses. Therefore, the development of an efficient and environmentally friendly new fracture repair material has become a key problem to be solved in the field of tunnel engineering disasters. To study the influence of initial setting time, 7-day compressive strength, and slurry retention rate of cement fly ash–water glass double-liquid grouting material, a response surface regression model was constructed, and the measured values and predicted values were compared and analyzed. Combined with the desirability function, the optimal mix ratio of the double-liquid grouting material was obtained. The results show that this regression model is effective and reliable, and can be used to analyze the test results. In the study of the initial setting time, it was found that there was a significant interaction effect between the two factors AB and AC, which had a significant effect on the initial setting time. In terms of slurry retention rate, the analysis also shows that only the interaction of the two-factor AB has a significant effect on the slurry retention rate. The model predicts that the optimal fly ash content is 41%, V(CF):V(S) is 3.5:1, and the flocculant content is 1%. The absolute value of the relative error between the predicted value of the initial setting time and the retention rate and the experimental value is less than 5%. The regression model can provide a reference for the multi-objective optimization of the mixture ratio of cement fly ash–water glass double liquid fracture sealing material.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Grouting, Rheology, and Soil Mechanics · Concrete and Cement Materials Research · Rock Mechanics and Modeling
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of intelligent construction, Shangqiu Institue of Technology , Shangqiu 476000,
Funding
A Key Sciencetific Research Project of Higher Education Instiitutions in Henan Province
References (25)
Show source-provided references
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