Groutability classification of granular soils with cement grouts

This research aims to develop a methodology for applying the geostatistical method to generate a groutability classification for granular soils. To ensure the precision of the suggested technique, a total of 103 data samples were used. Predicting the groutability of granular soils has always been difficult because of many soil characteristics. As a result, a new two-dimensional graph, the groutability classification of granular soil (GCS) chart, was developed. GCS establishment was based on data analysis of the grain size of soil and cement-based grouts (N-1 and N-2), relative density (D-r) and fines content of the soil (FC), water/cement ratio of grout mixture (w/c), and grouting pressure (P), all of which have a direct impact on the groutability of soil media. The geostatistical method was used to develop and compile the GCS graph based on the aforementioned parameters with the use of coefficient S, which is a coefficient of the scoring set of parameters including P, w/c, D-r, and FC. The validation process was carried out hierarchically, with an additional set of 30 data. The proposed method has a prediction accuracy of roughly 96.7%, demonstrating a helpful tool. The proposed approach can be easily implemented in practical engineering situations because it has a comparable syntax to commonly used formulae. It should be noted that the proposed formula was only tested using the data samples collected, and the applicability of the produced procedure to other situations requires more examination. (C) 2023 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This research aims to develop a methodology for classifying the groutability of granular soils using geostatistical methods. A new graph called the groutability classification of granular soil (GCS) chart was developed based on the analysis of soil grain size, cement-based grouts, relative density, fines content, water/cement ratio, and grouting pressure. The proposed method showed a prediction accuracy of 96.7% and can be easily implemented in practical engineering situations. However, further examination is needed to evaluate its applicability in different scenarios.